Apple M1 Max testing with a Apple MacBook Pro and Apple M1 Max on macOS 12.1 via the Phoronix Test Suite.
sys76-kudu-ML: AMD Ryzen 9 5900HX testing with a System76 Kudu (1.07.09RSA1 BIOS) and AMD Cezanne on Pop 21.10 via the Phoronix Test Suite.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2202161-NE-MBPM1MAXM40
{
"title": "MBP M1 Max Machine Learning, sys76-kudu-ML",
"last_modified": "2022-02-16 16:01:39",
"description": "Apple M1 Max testing with a Apple MacBook Pro and Apple M1 Max on macOS 12.1 via the Phoronix Test Suite.\n\nsys76-kudu-ML: AMD Ryzen 9 5900HX testing with a System76 Kudu (1.07.09RSA1 BIOS) and AMD Cezanne on Pop 21.10 via the Phoronix Test Suite.",
"systems": {
"MBP M1 Max Machine Learning": {
"identifier": "MBP M1 Max Machine Learning",
"hardware": {
"Processor": "Apple M1 Max (10 Cores)",
"Motherboard": "Apple MacBook Pro",
"Memory": "64GB",
"Disk": "1859GB",
"Graphics": "Apple M1 Max",
"Monitor": "Color LCD"
},
"software": {
"OS": "macOS 12.1",
"Kernel": "21.2.0 (arm64)",
"OpenCL": "OpenCL 1.2 (Nov 13 2021 00:45:09)",
"Compiler": "GCC 13.0.0 + Clang 13.0.0",
"File-System": "APFS",
"Screen Resolution": "3456x2234"
},
"user": "chrisf",
"timestamp": "2022-02-16 14:41:37",
"client_version": "10.8.2",
"data": {
"environment-variables": "XPC_FLAGS=0x0",
"python": "Python 2.7.18 + Python 3.8.9"
}
},
"ML Tests": {
"identifier": "ML Tests",
"hardware": {
"Processor": "AMD Ryzen 9 5900HX @ 3.30GHz (8 Cores \/ 16 Threads)",
"Motherboard": "System76 Kudu (1.07.09RSA1 BIOS)",
"Chipset": "AMD Renoir\/Cezanne",
"Memory": "16GB",
"Disk": "Samsung SSD 970 EVO Plus 500GB",
"Graphics": "AMD Cezanne (2100\/400MHz)",
"Audio": "AMD Renoir Radeon HD Audio",
"Network": "Realtek RTL8125 2.5GbE + Intel Wi-Fi 6 AX200"
},
"software": {
"OS": "Pop 21.10",
"Kernel": "5.15.15-76051515-generic (x86_64)",
"Desktop": "GNOME Shell 40.5",
"Display Server": "X Server 1.20.13",
"OpenGL": "4.6 Mesa 21.2.2 (LLVM 12.0.1)",
"Vulkan": "1.2.182",
"Compiler": "GCC 11.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1080"
},
"user": "chrisf",
"timestamp": "2022-02-15 18:57:17",
"client_version": "10.8.2",
"data": {
"compiler-configuration": "--build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=\/build\/gcc-11-ZPT0kp\/gcc-11-11.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-11-ZPT0kp\/gcc-11-11.2.0\/debian\/tmp-gcn\/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v",
"cpu-scaling-governor": "acpi-cpufreq schedutil (Boost: Enabled)",
"cpu-microcode": "0xa50000c",
"graphics-2d-acceleration": "GLAMOR",
"bar1-visible-vram": "512 MB",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.9.7",
"security": "itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full AMD retpoline IBPB: conditional IBRS_FW STIBP: always-on RSB filling + srbds: Not affected + tsx_async_abort: Not affected"
}
}
},
"results": {
"027b727fa677092a17f23987f3e8bffbb344e960": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: alexnet",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 29.8900000000000005684341886080801486968994140625,
"raw_values": [
29.8900000000000005684341886080801486968994140625,
29.879999999999999005240169935859739780426025390625,
29.8900000000000005684341886080801486968994140625
],
"min_result": [
"29.79"
],
"max_result": [
"31.07"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 6.32000000000000028421709430404007434844970703125,
"raw_values": [
6.269999999999999573674358543939888477325439453125,
6.339999999999999857891452847979962825775146484375,
6.3499999999999996447286321199499070644378662109375
],
"min_result": [
"5.95"
],
"max_result": [
"7.49"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"f02b4dd054d58c9fc80ede586f5019041d1c6f41": {
"identifier": "pts\/mnn-1.3.0",
"title": "Mobile Neural Network",
"app_version": "1.2",
"description": "Model: MobileNetV2_224",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 10.67699999999999960209606797434389591217041015625,
"raw_values": [
10.330999999999999516830939683131873607635498046875,
9.4689999999999994173549566767178475856781005859375,
10.474000000000000198951966012828052043914794921875,
10.425000000000000710542735760100185871124267578125,
10.977000000000000312638803734444081783294677734375,
11.0690000000000008384404281969182193279266357421875,
11.1669999999999998152588887023739516735076904296875,
11.025999999999999801048033987171947956085205078125,
11.150999999999999801048033987171947956085205078125
],
"min_result": [
"5.12"
],
"max_result": [
"61.59"
],
"test_run_times": [
265.26999999999998181010596454143524169921875,
216.8899999999999863575794734060764312744140625,
212.280000000000001136868377216160297393798828125,
199.539999999999992041921359486877918243408203125,
195.1200000000000045474735088646411895751953125,
194.969999999999998863131622783839702606201171875,
194.8799999999999954525264911353588104248046875,
192.830000000000012505552149377763271331787109375,
236.830000000000012505552149377763271331787109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -arch -isysroot"
}
}
},
"ML Tests": {
"value": 2.387000000000000010658141036401502788066864013671875,
"raw_values": [
2.36399999999999987920773492078296840190887451171875,
2.4230000000000000426325641456060111522674560546875,
2.374000000000000110134124042815528810024261474609375
],
"min_result": [
"2.24"
],
"max_result": [
"17.04"
],
"test_run_times": [
85.8900000000000005684341886080801486968994140625,
84.409999999999996589394868351519107818603515625,
83.9200000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl"
}
}
}
}
},
"66f321c870403470f20e0b0e903d2e9e7a63a07e": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: resnet50",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 43.0799999999999982946974341757595539093017578125,
"raw_values": [
43.090000000000003410605131648480892181396484375,
43.090000000000003410605131648480892181396484375,
43.0499999999999971578290569595992565155029296875
],
"min_result": [
"42.9"
],
"max_result": [
"45.66"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 13.1199999999999992184029906638897955417633056640625,
"raw_values": [
13.019999999999999573674358543939888477325439453125,
13.1300000000000007815970093361102044582366943359375,
13.21000000000000085265128291212022304534912109375
],
"min_result": [
"12.27"
],
"max_result": [
"15.04"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"4cf07016210c8ab5faad2c70962a5795859db414": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: googlenet",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 24.89999999999999857891452847979962825775146484375,
"raw_values": [
24.89999999999999857891452847979962825775146484375,
24.89999999999999857891452847979962825775146484375,
24.89999999999999857891452847979962825775146484375
],
"min_result": [
"24.82"
],
"max_result": [
"25.79"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 8.730000000000000426325641456060111522674560546875,
"raw_values": [
8.25,
8.839999999999999857891452847979962825775146484375,
9.089999999999999857891452847979962825775146484375
],
"min_result": [
"7.89"
],
"max_result": [
"10.64"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"75beb2659645ca70295fb171a8e7ea52a3ed12b7": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: resnet18",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 16.800000000000000710542735760100185871124267578125,
"raw_values": [
16.82000000000000028421709430404007434844970703125,
16.780000000000001136868377216160297393798828125,
16.800000000000000710542735760100185871124267578125
],
"min_result": [
"16.69"
],
"max_result": [
"18.25"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 6.089999999999999857891452847979962825775146484375,
"raw_values": [
6.1699999999999999289457264239899814128875732421875,
6.1699999999999999289457264239899814128875732421875,
5.94000000000000039079850466805510222911834716796875
],
"min_result": [
"5.63"
],
"max_result": [
"7.52"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"9a364e7e68f3a6c56e4b13b3722291125e56ca5c": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: alexnet",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 29.92999999999999971578290569595992565155029296875,
"raw_values": [
30.03999999999999914734871708787977695465087890625,
29.879999999999999005240169935859739780426025390625,
29.879999999999999005240169935859739780426025390625
],
"min_result": [
"29.79"
],
"max_result": [
"31.03"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 14.550000000000000710542735760100185871124267578125,
"raw_values": [
14.519999999999999573674358543939888477325439453125,
14.46000000000000085265128291212022304534912109375,
14.660000000000000142108547152020037174224853515625
],
"min_result": [
"13.9"
],
"max_result": [
"33.49"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"a36b5095f85071410e5caf3f1b39abe8e2aeea9e": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: mobilenet",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 20.300000000000000710542735760100185871124267578125,
"raw_values": [
20.3299999999999982946974341757595539093017578125,
20.28999999999999914734871708787977695465087890625,
20.280000000000001136868377216160297393798828125
],
"min_result": [
"20.23"
],
"max_result": [
"21.48"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 10.269999999999999573674358543939888477325439453125,
"raw_values": [
10.2599999999999997868371792719699442386627197265625,
10.1300000000000007815970093361102044582366943359375,
10.42999999999999971578290569595992565155029296875
],
"min_result": [
"9.59"
],
"max_result": [
"17.84"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"6e8fe2d6cd6e4622a7afe7f24238b260271dc83d": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: googlenet",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 24.96000000000000085265128291212022304534912109375,
"raw_values": [
25.1099999999999994315658113919198513031005859375,
24.8900000000000005684341886080801486968994140625,
24.8900000000000005684341886080801486968994140625
],
"min_result": [
"24.82"
],
"max_result": [
"25.91"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 13.7400000000000002131628207280300557613372802734375,
"raw_values": [
14.1099999999999994315658113919198513031005859375,
13.17999999999999971578290569595992565155029296875,
13.92999999999999971578290569595992565155029296875
],
"min_result": [
"12.47"
],
"max_result": [
"28.56"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"2a4e1e20c19933ee1c0d9d7435bf28ed95ee5ea9": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: resnet50",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 43.159999999999996589394868351519107818603515625,
"raw_values": [
43.28999999999999914734871708787977695465087890625,
43.090000000000003410605131648480892181396484375,
43.10000000000000142108547152020037174224853515625
],
"min_result": [
"42.92"
],
"max_result": [
"44.81"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 25.1700000000000017053025658242404460906982421875,
"raw_values": [
25.059999999999998721023075631819665431976318359375,
25.280000000000001136868377216160297393798828125,
25.160000000000000142108547152020037174224853515625
],
"min_result": [
"23.91"
],
"max_result": [
"41.27"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"ff2b3704f0c9efff2a280795a755dac887a98102": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: efficientnet-b0",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 8.6899999999999995026200849679298698902130126953125,
"raw_values": [
8.7799999999999993605115378159098327159881591796875,
8.6699999999999999289457264239899814128875732421875,
8.6300000000000007815970093361102044582366943359375
],
"min_result": [
"8.59"
],
"max_result": [
"9.15"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 5.21999999999999975131004248396493494510650634765625,
"raw_values": [
5.20999999999999996447286321199499070644378662109375,
5.20999999999999996447286321199499070644378662109375,
5.230000000000000426325641456060111522674560546875
],
"min_result": [
"4.86"
],
"max_result": [
"20.63"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"f5d5356d49370b73a5647e00bd24e4f17b3b41ab": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: mnasnet",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 5.4000000000000003552713678800500929355621337890625,
"raw_values": [
5.45999999999999996447286321199499070644378662109375,
5.37000000000000010658141036401502788066864013671875,
5.37000000000000010658141036401502788066864013671875
],
"min_result": [
"5.35"
],
"max_result": [
"5.68"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 3.25,
"raw_values": [
3.310000000000000053290705182007513940334320068359375,
3.229999999999999982236431605997495353221893310546875,
3.20000000000000017763568394002504646778106689453125
],
"min_result": [
"2.82"
],
"max_result": [
"16.82"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"49afe88ae7a157f2ac4897ce56bf66f17d2a8181": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: yolov4-tiny",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 30.3299999999999982946974341757595539093017578125,
"raw_values": [
30.3599999999999994315658113919198513031005859375,
30.42999999999999971578290569595992565155029296875,
30.199999999999999289457264239899814128875732421875
],
"min_result": [
"29.85"
],
"max_result": [
"32.58"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 18.82000000000000028421709430404007434844970703125,
"raw_values": [
18.989999999999998436805981327779591083526611328125,
19.46000000000000085265128291212022304534912109375,
18.019999999999999573674358543939888477325439453125
],
"min_result": [
"17.12"
],
"max_result": [
"24.45"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"9fa66c5172c217e7ea40a4e1feb0ce56af954deb": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: vgg16",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 70.8900000000000005684341886080801486968994140625,
"raw_values": [
70.93000000000000682121026329696178436279296875,
70.849999999999994315658113919198513031005859375,
70.8799999999999954525264911353588104248046875
],
"min_result": [
"70.59"
],
"max_result": [
"73.62"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 43.99000000000000198951966012828052043914794921875,
"raw_values": [
43.93999999999999772626324556767940521240234375,
43.89999999999999857891452847979962825775146484375,
44.1400000000000005684341886080801486968994140625
],
"min_result": [
"43.17"
],
"max_result": [
"45.59"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"188bd8cea18f37dd99f31201db8388d99b594507": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: mnasnet",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 5.37000000000000010658141036401502788066864013671875,
"raw_values": [
5.37000000000000010658141036401502788066864013671875,
5.37000000000000010658141036401502788066864013671875,
5.37000000000000010658141036401502788066864013671875
],
"min_result": [
"5.35"
],
"max_result": [
"5.62"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 3.890000000000000124344978758017532527446746826171875,
"raw_values": [
3.779999999999999804600747665972448885440826416015625,
3.9900000000000002131628207280300557613372802734375
],
"min_result": [
"3.56"
],
"max_result": [
"5.01"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"6f76ab2d29cb7d56c3ec4c068d9cd0a82d4c61f6": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: blazeface",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 1.649999999999999911182158029987476766109466552734375,
"raw_values": [
1.6699999999999999289457264239899814128875732421875,
1.6399999999999999023003738329862244427204132080078125,
1.6399999999999999023003738329862244427204132080078125
],
"min_result": [
"1.64"
],
"max_result": [
"1.72"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 1.1999999999999999555910790149937383830547332763671875,
"raw_values": [
1.1999999999999999555910790149937383830547332763671875,
1.1799999999999999378275106209912337362766265869140625,
1.20999999999999996447286321199499070644378662109375
],
"min_result": [
"1.16"
],
"max_result": [
"1.78"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"4a673deb7415ad5326c4cc7e87d42c176c6f6d81": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 5.29999999999999982236431605997495353221893310546875,
"raw_values": [
5.30999999999999960920149533194489777088165283203125,
5.29000000000000003552713678800500929355621337890625,
5.29000000000000003552713678800500929355621337890625
],
"min_result": [
"5.28"
],
"max_result": [
"5.98"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 3.87999999999999989341858963598497211933135986328125,
"raw_values": [
3.7599999999999997868371792719699442386627197265625,
3.95000000000000017763568394002504646778106689453125,
3.939999999999999946709294817992486059665679931640625
],
"min_result": [
"3.49"
],
"max_result": [
"5.25"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"bdb9d562d49ad4554019fc2ed349bfc30a99fea5": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: regnety_400m",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 7.19000000000000039079850466805510222911834716796875,
"raw_values": [
7.17999999999999971578290569595992565155029296875,
7.19000000000000039079850466805510222911834716796875,
7.19000000000000039079850466805510222911834716796875
],
"min_result": [
"7.15"
],
"max_result": [
"7.72"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 5.28000000000000024868995751603506505489349365234375,
"raw_values": [
5.20999999999999996447286321199499070644378662109375,
5.2400000000000002131628207280300557613372802734375,
5.38999999999999968025576890795491635799407958984375
],
"min_result": [
"4.68"
],
"max_result": [
"6.44"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"4ad49da525e8369540fae21c24b97299c5dea12d": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: squeezenet_ssd",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 20.550000000000000710542735760100185871124267578125,
"raw_values": [
20.469999999999998863131622783839702606201171875,
20.629999999999999005240169935859739780426025390625,
20.559999999999998721023075631819665431976318359375
],
"min_result": [
"20.39"
],
"max_result": [
"22.13"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 15.3599999999999994315658113919198513031005859375,
"raw_values": [
14.8800000000000007815970093361102044582366943359375,
15.1300000000000007815970093361102044582366943359375,
16.059999999999998721023075631819665431976318359375
],
"min_result": [
"14.17"
],
"max_result": [
"22.53"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"83f625f75ff15cb2eb6d2d0d20ce79295b3cb817": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU-v2-v2 - Model: mobilenet-v2",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 5.3300000000000000710542735760100185871124267578125,
"raw_values": [
5.38999999999999968025576890795491635799407958984375,
5.29999999999999982236431605997495353221893310546875,
5.29999999999999982236431605997495353221893310546875
],
"min_result": [
"5.27"
],
"max_result": [
"5.61"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 3.9900000000000002131628207280300557613372802734375,
"raw_values": [
3.979999999999999982236431605997495353221893310546875,
4.019999999999999573674358543939888477325439453125,
3.970000000000000195399252334027551114559173583984375
],
"min_result": [
"3.71"
],
"max_result": [
"19.11"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"368631f5b00755d6644a846cd53ef658272b18e7": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU-v3-v3 - Model: mobilenet-v3",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 4.36000000000000031974423109204508364200592041015625,
"raw_values": [
4.4199999999999999289457264239899814128875732421875,
4.339999999999999857891452847979962825775146484375,
4.3300000000000000710542735760100185871124267578125
],
"min_result": [
"4.32"
],
"max_result": [
"4.61"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 3.410000000000000142108547152020037174224853515625,
"raw_values": [
3.359999999999999875655021241982467472553253173828125,
3.4199999999999999289457264239899814128875732421875,
3.439999999999999946709294817992486059665679931640625
],
"min_result": [
"3.11"
],
"max_result": [
"17.47"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"762a4cada6215c2945e8ee113c3f4e19c18265e1": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: mobilenet",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 20.32000000000000028421709430404007434844970703125,
"raw_values": [
20.3599999999999994315658113919198513031005859375,
20.28999999999999914734871708787977695465087890625,
20.300000000000000710542735760100185871124267578125
],
"min_result": [
"20.23"
],
"max_result": [
"21.33"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 15.949999999999999289457264239899814128875732421875,
"raw_values": [
15.8499999999999996447286321199499070644378662109375,
16.129999999999999005240169935859739780426025390625,
15.8699999999999992184029906638897955417633056640625
],
"min_result": [
"14.92"
],
"max_result": [
"35.66"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"09301b5cee05cca0ef3b4629ca92e2649d596ef0": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: shufflenet-v2",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 3.470000000000000195399252334027551114559173583984375,
"raw_values": [
3.5099999999999997868371792719699442386627197265625,
3.45000000000000017763568394002504646778106689453125,
3.45000000000000017763568394002504646778106689453125
],
"min_result": [
"3.43"
],
"max_result": [
"3.84"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 2.75,
"raw_values": [
2.680000000000000159872115546022541821002960205078125,
2.770000000000000017763568394002504646778106689453125,
2.810000000000000053290705182007513940334320068359375
],
"min_result": [
"2.48"
],
"max_result": [
"16.13"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"3834a3949f88e1b709c3b6b08f03f0116dc3d62e": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: blazeface",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 1.6399999999999999023003738329862244427204132080078125,
"raw_values": [
1.6399999999999999023003738329862244427204132080078125,
1.6399999999999999023003738329862244427204132080078125,
1.6399999999999999023003738329862244427204132080078125
],
"min_result": [
"1.63"
],
"max_result": [
"1.79"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 1.350000000000000088817841970012523233890533447265625,
"raw_values": [
1.3400000000000000799360577730112709105014801025390625,
1.37999999999999989341858963598497211933135986328125,
1.3400000000000000799360577730112709105014801025390625
],
"min_result": [
"1.17"
],
"max_result": [
"2.43"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"03fc807c327798b5f5ca294f88a5b13e01cb9695": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: yolov4-tiny",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 30.239999999999998436805981327779591083526611328125,
"raw_values": [
30.199999999999999289457264239899814128875732421875,
30.230000000000000426325641456060111522674560546875,
30.28999999999999914734871708787977695465087890625
],
"min_result": [
"29.85"
],
"max_result": [
"31.87"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 24.969999999999998863131622783839702606201171875,
"raw_values": [
24.780000000000001136868377216160297393798828125,
25.17999999999999971578290569595992565155029296875,
24.96000000000000085265128291212022304534912109375
],
"min_result": [
"23.9"
],
"max_result": [
"38.98"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"7dd771a2e9d4e9e9e17d191992c1ba93c7615c5b": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: efficientnet-b0",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 8.71000000000000085265128291212022304534912109375,
"raw_values": [
8.71000000000000085265128291212022304534912109375,
8.7400000000000002131628207280300557613372802734375,
8.6699999999999999289457264239899814128875732421875
],
"min_result": [
"8.6"
],
"max_result": [
"9.43"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 10.07000000000000028421709430404007434844970703125,
"raw_values": [
10.1400000000000005684341886080801486968994140625,
9.9399999999999995026200849679298698902130126953125,
10.1199999999999992184029906638897955417633056640625
],
"min_result": [
"9.06"
],
"max_result": [
"11.43"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"4d6d66ee11d99aafe7c9e062653321cf2159473d": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU - Model: shufflenet-v2",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 3.45999999999999996447286321199499070644378662109375,
"raw_values": [
3.479999999999999982236431605997495353221893310546875,
3.45000000000000017763568394002504646778106689453125,
3.45999999999999996447286321199499070644378662109375
],
"min_result": [
"3.44"
],
"max_result": [
"3.82"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 3.020000000000000017763568394002504646778106689453125,
"raw_values": [
2.95000000000000017763568394002504646778106689453125,
2.95000000000000017763568394002504646778106689453125,
3.160000000000000142108547152020037174224853515625
],
"min_result": [
"2.54"
],
"max_result": [
"4.38"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"51abd4929df75e3dcbfba4af5ba252eb8327a2db": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: squeezenet_ssd",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 20.530000000000001136868377216160297393798828125,
"raw_values": [
20.550000000000000710542735760100185871124267578125,
20.440000000000001278976924368180334568023681640625,
20.60000000000000142108547152020037174224853515625
],
"min_result": [
"20.37"
],
"max_result": [
"21.53"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 18.559999999999998721023075631819665431976318359375,
"raw_values": [
18.269999999999999573674358543939888477325439453125,
18.739999999999998436805981327779591083526611328125,
18.67999999999999971578290569595992565155029296875
],
"min_result": [
"17.64"
],
"max_result": [
"34.93"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"d229b69a267629e59086d1e6f9b973f8d54cc8d5": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"description": "Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 4.3499999999999996447286321199499070644378662109375,
"raw_values": [
4.3499999999999996447286321199499070644378662109375,
4.3499999999999996447286321199499070644378662109375,
4.339999999999999857891452847979962825775146484375
],
"min_result": [
"4.32"
],
"max_result": [
"4.63"
],
"test_run_times": [
104.909999999999996589394868351519107818603515625,
104.9800000000000039790393202565610408782958984375,
104.7900000000000062527760746888816356658935546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 4.69000000000000039079850466805510222911834716796875,
"raw_values": [
4.9199999999999999289457264239899814128875732421875,
4.5,
4.660000000000000142108547152020037174224853515625
],
"min_result": [
"4.29"
],
"max_result": [
"5.94"
],
"test_run_times": [
73.43000000000000682121026329696178436279296875,
70.280000000000001136868377216160297393798828125,
71.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"dc2e7ba663d0011059ab2127b57d934f229136cf": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: resnet18",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 16.82000000000000028421709430404007434844970703125,
"raw_values": [
16.8900000000000005684341886080801486968994140625,
16.780000000000001136868377216160297393798828125,
16.780000000000001136868377216160297393798828125
],
"min_result": [
"16.69"
],
"max_result": [
"17.58"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 15.7799999999999993605115378159098327159881591796875,
"raw_values": [
16.219999999999998863131622783839702606201171875,
14.9199999999999999289457264239899814128875732421875,
16.199999999999999289457264239899814128875732421875
],
"min_result": [
"14.59"
],
"max_result": [
"30.81"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"f41746e3e148ad03772d747b2588b658cb4af74b": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: regnety_400m",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 7.17999999999999971578290569595992565155029296875,
"raw_values": [
7.17999999999999971578290569595992565155029296875,
7.17999999999999971578290569595992565155029296875,
7.19000000000000039079850466805510222911834716796875
],
"min_result": [
"7.14"
],
"max_result": [
"8.13"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 6.9000000000000003552713678800500929355621337890625,
"raw_values": [
6.95000000000000017763568394002504646778106689453125,
6.80999999999999960920149533194489777088165283203125,
6.92999999999999971578290569595992565155029296875
],
"min_result": [
"6.35"
],
"max_result": [
"21.53"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"a5baa9967d51c1b662fd258dd75934a359bb88cc": {
"identifier": "pts\/ncnn-1.3.0",
"title": "NCNN",
"app_version": "20210720",
"arguments": "-1",
"description": "Target: CPU - Model: vgg16",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 71.0100000000000051159076974727213382720947265625,
"raw_values": [
71.2999999999999971578290569595992565155029296875,
70.900000000000005684341886080801486968994140625,
70.81999999999999317878973670303821563720703125
],
"min_result": [
"70.58"
],
"max_result": [
"74.44"
],
"test_run_times": [
105.75,
104.7399999999999948840923025272786617279052734375,
104.849999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -arch -isysroot"
}
}
},
"ML Tests": {
"value": 71.969999999999998863131622783839702606201171875,
"raw_values": [
71.8299999999999982946974341757595539093017578125,
72.280000000000001136868377216160297393798828125,
71.7999999999999971578290569595992565155029296875
],
"min_result": [
"69.95"
],
"max_result": [
"94.76"
],
"test_run_times": [
74.93000000000000682121026329696178436279296875,
74.280000000000001136868377216160297393798828125,
74.659999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -rdynamic -lgomp -lpthread"
}
}
}
}
},
"6e4a1114ac4c4b97f28942fcfc77f0071864290c": {
"identifier": "pts\/mlpack-1.0.2",
"title": "Mlpack Benchmark",
"arguments": "SCIKIT_LINEARRIDGEREGRESSION",
"description": "Benchmark: scikit_linearridgeregression",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 2.100000000000000088817841970012523233890533447265625,
"raw_values": [
2.09613800048829990174681370262987911701202392578125,
2.092653989791899871164559954195283353328704833984375,
2.122283935546899868995751603506505489349365234375
],
"test_run_times": [
41.75999999999999801048033987171947956085205078125,
41.10000000000000142108547152020037174224853515625,
41.31000000000000227373675443232059478759765625
]
}
}
},
"d99f55e37cf79cb02f548b43c73d0851e1d39fea": {
"identifier": "pts\/mlpack-1.0.2",
"title": "Mlpack Benchmark",
"arguments": "SCIKIT_SVM",
"description": "Benchmark: scikit_svm",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 17.60000000000000142108547152020037174224853515625,
"raw_values": [
17.6106095314030000054117408581078052520751953125,
17.621352910995000229377183131873607635498046875,
17.570944547652999290221487171947956085205078125
],
"test_run_times": [
20.989999999999998436805981327779591083526611328125,
21.010000000000001563194018672220408916473388671875,
20.96000000000000085265128291212022304534912109375
]
}
}
},
"a4ef571508e0145a960b428b4500ad810557312e": {
"identifier": "pts\/mlpack-1.0.2",
"title": "Mlpack Benchmark",
"arguments": "SCIKIT_QDA",
"description": "Benchmark: scikit_qda",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 65.68999999999999772626324556767940521240234375,
"raw_values": [
65.696218013763001408733543939888477325439453125,
65.6326816082000021879139239899814128875732421875,
65.7387859821320006403766456060111522674560546875
],
"test_run_times": [
105.090000000000003410605131648480892181396484375,
104.900000000000005684341886080801486968994140625,
105.3599999999999994315658113919198513031005859375
]
}
}
},
"082e91ee6f9fd09c616b9f84f2ff189d752ff466": {
"identifier": "pts\/mlpack-1.0.2",
"title": "Mlpack Benchmark",
"arguments": "SCIKIT_ICA",
"description": "Benchmark: scikit_ica",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 48.39999999999999857891452847979962825775146484375,
"raw_values": [
48.62524271011400145425795926712453365325927734375,
48.20602369308500101396930404007434844970703125,
48.3630189895630024921047152020037174224853515625
],
"test_run_times": [
51.39999999999999857891452847979962825775146484375,
50.719999999999998863131622783839702606201171875,
50.89999999999999857891452847979962825775146484375
]
}
}
},
"aa599b9ca22f592b874b83447a00bad8daf8df13": {
"identifier": "pts\/ecp-candle-1.1.0",
"title": "ECP-CANDLE",
"app_version": "0.4",
"arguments": "P3B2",
"description": "Benchmark: P3B2",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 730.7359999999999899955582804977893829345703125,
"test_run_times": [
730.740000000000009094947017729282379150390625
]
}
}
},
"784b2256ba16b03fd1ed0346f969767fb14f12da": {
"identifier": "pts\/ecp-candle-1.1.0",
"title": "ECP-CANDLE",
"app_version": "0.4",
"arguments": "P3B1",
"description": "Benchmark: P3B1",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 1463.721999999999979991116560995578765869140625,
"test_run_times": [
1463.720000000000027284841053187847137451171875
]
}
}
},
"0ab6893d03032537d0c3b9e7cfa51380d902b4b0": {
"identifier": "pts\/ecp-candle-1.1.0",
"title": "ECP-CANDLE",
"app_version": "0.4",
"arguments": "P1B2",
"description": "Benchmark: P1B2",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 37.50999999999999801048033987171947956085205078125,
"test_run_times": [
37.50999999999999801048033987171947956085205078125
]
}
}
},
"e4303cae225e2ec652192e4b2613635d07aa2f13": {
"identifier": "pts\/plaidml-1.0.4",
"title": "PlaidML",
"arguments": "--no-fp16 --no-train resnet50 CPU",
"description": "FP16: No - Mode: Inference - Network: ResNet 50 - Device: CPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 6.87999999999999989341858963598497211933135986328125,
"raw_values": [
6.9199999999999999289457264239899814128875732421875,
6.8499999999999996447286321199499070644378662109375,
6.87999999999999989341858963598497211933135986328125
],
"test_run_times": [
330.92000000000001591615728102624416351318359375,
315.56000000000000227373675443232059478759765625,
314.18000000000000682121026329696178436279296875
]
}
}
},
"1be2d4009f744b1d7120ff0ea4b0f1cd272189a8": {
"identifier": "pts\/plaidml-1.0.4",
"title": "PlaidML",
"arguments": "--no-fp16 --no-train vgg16 CPU",
"description": "FP16: No - Mode: Inference - Network: VGG16 - Device: CPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 12.4700000000000006394884621840901672840118408203125,
"raw_values": [
12.3599999999999994315658113919198513031005859375,
12.42999999999999971578290569595992565155029296875,
12.6099999999999994315658113919198513031005859375
],
"test_run_times": [
237.490000000000009094947017729282379150390625,
173.81999999999999317878973670303821563720703125,
171.400000000000005684341886080801486968994140625
]
}
}
},
"27fa9c3aaa8ef41529aae90c8d65409753629079": {
"identifier": "pts\/tnn-1.1.0",
"title": "TNN",
"app_version": "0.3",
"arguments": "-dt NAIVE -mp ..\/benchmark\/benchmark-model\/squeezenet_v1.1.tnnproto",
"description": "Target: CPU - Model: SqueezeNet v1.1",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 222.325999999999993406163412146270275115966796875,
"raw_values": [
222.2450000000000045474735088646411895751953125,
222.15100000000001045918907038867473602294921875,
222.582999999999998408384271897375583648681640625
],
"min_result": [
"221.49"
],
"max_result": [
"224.65"
],
"test_run_times": [
15.5800000000000000710542735760100185871124267578125,
15.57000000000000028421709430404007434844970703125,
15.5999999999999996447286321199499070644378662109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -pthread -fvisibility=hidden -fvisibility=default -O3 -rdynamic -ldl"
}
}
}
}
},
"3ed6d242abf08fed45c4dd9ff72d8124554e671d": {
"identifier": "pts\/tnn-1.1.0",
"title": "TNN",
"app_version": "0.3",
"arguments": "-dt NAIVE -mp ..\/benchmark\/benchmark-model\/shufflenet_v2.tnnproto",
"description": "Target: CPU - Model: SqueezeNet v2",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 55.433999999999997498889570124447345733642578125,
"raw_values": [
54.40100000000000335376171278767287731170654296875,
55.36800000000000210320649784989655017852783203125,
56.5330000000000012505552149377763271331787109375
],
"min_result": [
"54.24"
],
"max_result": [
"57.06"
],
"test_run_times": [
3.8300000000000000710542735760100185871124267578125,
3.890000000000000124344978758017532527446746826171875,
3.979999999999999982236431605997495353221893310546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -pthread -fvisibility=hidden -fvisibility=default -O3 -rdynamic -ldl"
}
}
}
}
},
"d09f5c078364ff22b89265c123eb04d064d62da7": {
"identifier": "pts\/tnn-1.1.0",
"title": "TNN",
"app_version": "0.3",
"arguments": "-dt NAIVE -mp ..\/benchmark\/benchmark-model\/mobilenet_v2.tnnproto",
"description": "Target: CPU - Model: MobileNet v2",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 249.477000000000003865352482534945011138916015625,
"raw_values": [
249.919999999999987494447850622236728668212890625,
248.681999999999987949195201508700847625732421875,
249.82900000000000773070496506989002227783203125
],
"min_result": [
"247.22"
],
"max_result": [
"255.16"
],
"test_run_times": [
17.53999999999999914734871708787977695465087890625,
17.469999999999998863131622783839702606201171875,
17.530000000000001136868377216160297393798828125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -pthread -fvisibility=hidden -fvisibility=default -O3 -rdynamic -ldl"
}
}
}
}
},
"4e309e0b2e86e695a4c888e5921e869c6e657838": {
"identifier": "pts\/tnn-1.1.0",
"title": "TNN",
"app_version": "0.3",
"arguments": "-dt NAIVE -mp ..\/benchmark\/benchmark-model\/densenet.tnnproto",
"description": "Target: CPU - Model: DenseNet",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 2736.1729999999997744453139603137969970703125,
"raw_values": [
2734.95699999999987994669936597347259521484375,
2735.7979999999997744453139603137969970703125,
2737.7640000000001236912794411182403564453125
],
"min_result": [
"2687.97"
],
"max_result": [
"2827.52"
],
"test_run_times": [
192.039999999999992041921359486877918243408203125,
191.94999999999998863131622783839702606201171875,
191.979999999999989768184605054557323455810546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -pthread -fvisibility=hidden -fvisibility=default -O3 -rdynamic -ldl"
}
}
}
}
},
"8db9907e629338ade7ede8c85eac49b7921db511": {
"identifier": "pts\/caffe-1.5.0",
"title": "Caffe",
"app_version": "2020-02-13",
"arguments": "--model=..\/models\/bvlc_googlenet\/deploy.prototxt -iterations 1000",
"description": "Model: GoogleNet - Acceleration: CPU - Iterations: 1000",
"scale": "Milli-Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 868758,
"raw_values": [
867869,
868934,
869471
],
"test_run_times": [
868.6799999999999499777914024889469146728515625,
869.740000000000009094947017729282379150390625,
870.26999999999998181010596454143524169921875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas"
}
}
}
}
},
"bc6942049de8e145216bdb58030e8f2ebe11427c": {
"identifier": "pts\/caffe-1.5.0",
"title": "Caffe",
"app_version": "2020-02-13",
"arguments": "--model=..\/models\/bvlc_googlenet\/deploy.prototxt -iterations 200",
"description": "Model: GoogleNet - Acceleration: CPU - Iterations: 200",
"scale": "Milli-Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 173671,
"raw_values": [
173960,
174018,
173036
],
"test_run_times": [
174.75,
174.81000000000000227373675443232059478759765625,
173.81999999999999317878973670303821563720703125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas"
}
}
}
}
},
"8aa5e9bf39252f5e08e824518f8f910984ee12a0": {
"identifier": "pts\/caffe-1.5.0",
"title": "Caffe",
"app_version": "2020-02-13",
"arguments": "--model=..\/models\/bvlc_googlenet\/deploy.prototxt -iterations 100",
"description": "Model: GoogleNet - Acceleration: CPU - Iterations: 100",
"scale": "Milli-Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 86567,
"raw_values": [
86747,
86566,
86389
],
"test_run_times": [
87.5400000000000062527760746888816356658935546875,
87.349999999999994315658113919198513031005859375,
87.18000000000000682121026329696178436279296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas"
}
}
}
}
},
"cca8410813e7ff3de8f5157d23b8ff02715d83bf": {
"identifier": "pts\/caffe-1.5.0",
"title": "Caffe",
"app_version": "2020-02-13",
"arguments": "--model=..\/models\/bvlc_alexnet\/deploy.prototxt -iterations 1000",
"description": "Model: AlexNet - Acceleration: CPU - Iterations: 1000",
"scale": "Milli-Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 325884,
"raw_values": [
325390,
325438,
326823
],
"test_run_times": [
325.70999999999997953636921010911464691162109375,
325.75,
327.1399999999999863575794734060764312744140625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas"
}
}
}
}
},
"0f53816e9035bfae2a33fe0b18da962f0d6b6e84": {
"identifier": "pts\/caffe-1.5.0",
"title": "Caffe",
"app_version": "2020-02-13",
"arguments": "--model=..\/models\/bvlc_alexnet\/deploy.prototxt -iterations 200",
"description": "Model: AlexNet - Acceleration: CPU - Iterations: 200",
"scale": "Milli-Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 65986,
"raw_values": [
65911,
65740,
66306
],
"test_run_times": [
66.219999999999998863131622783839702606201171875,
66.0499999999999971578290569595992565155029296875,
66.6299999999999954525264911353588104248046875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas"
}
}
}
}
},
"8809d1cc89793c60a334f093bac06f6d4c80154f": {
"identifier": "pts\/caffe-1.5.0",
"title": "Caffe",
"app_version": "2020-02-13",
"arguments": "--model=..\/models\/bvlc_alexnet\/deploy.prototxt -iterations 100",
"description": "Model: AlexNet - Acceleration: CPU - Iterations: 100",
"scale": "Milli-Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 33496,
"raw_values": [
33446,
33473,
33569
],
"test_run_times": [
33.780000000000001136868377216160297393798828125,
33.78999999999999914734871708787977695465087890625,
33.88000000000000255795384873636066913604736328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fPIC -O3 -rdynamic -lglog -lgflags -lprotobuf -lpthread -lsz -lz -ldl -lm -llmdb -lopenblas"
}
}
}
}
},
"fd1c35dce606e4556e6c75611dc03b6045835336": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=inception_resnet_v2.tflite",
"description": "Model: Inception ResNet V2",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 2479080,
"raw_values": [
2476730,
2479930,
2480580
],
"test_run_times": [
126.56999999999999317878973670303821563720703125,
126.4200000000000017053025658242404460906982421875,
126.4599999999999937472239253111183643341064453125
]
}
}
},
"7471926c423ed1e3c36c3d5ab372003c88873f4a": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=mobilenet_v1_1.0_224_quant.tflite",
"description": "Model: Mobilenet Quant",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 141174,
"raw_values": [
141105,
141237,
141181
],
"test_run_times": [
60.71000000000000085265128291212022304534912109375,
60.60000000000000142108547152020037174224853515625,
60.5799999999999982946974341757595539093017578125
]
}
}
},
"ff14b6016c9fc696e403f9e532362c01e6564fb7": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=mobilenet_v1_1.0_224.tflite",
"description": "Model: Mobilenet Float",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 127818,
"raw_values": [
127626,
128167,
127661
],
"test_run_times": [
60.56000000000000227373675443232059478759765625,
60.530000000000001136868377216160297393798828125,
60.5499999999999971578290569595992565155029296875
]
}
}
},
"4e47784b678508ad5f522adb3d9437ebf2d2dc4f": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=nasnet_mobile.tflite",
"description": "Model: NASNet Mobile",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 152186,
"raw_values": [
152578,
152481,
151498
],
"test_run_times": [
60.67999999999999971578290569595992565155029296875,
60.71000000000000085265128291212022304534912109375,
60.61999999999999744204615126363933086395263671875
]
}
}
},
"c54f0992c37a5943d696b0042b8e19e02c23c54d": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=inception_v4.tflite",
"description": "Model: Inception V4",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 2749623,
"raw_values": [
2753040,
2748260,
2747570
],
"test_run_times": [
140.669999999999987494447850622236728668212890625,
140.099999999999994315658113919198513031005859375,
140.06000000000000227373675443232059478759765625
]
}
}
},
"cd3416e44240b77943cbb384c7ea44c2a9614cb4": {
"identifier": "pts\/tensorflow-lite-1.0.0",
"title": "TensorFlow Lite",
"app_version": "2020-08-23",
"arguments": "--graph=squeezenet.tflite",
"description": "Model: SqueezeNet",
"scale": "Microseconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 189764,
"raw_values": [
189572,
189772,
189949
],
"test_run_times": [
60.719999999999998863131622783839702606201171875,
60.75999999999999801048033987171947956085205078125,
60.61999999999999744204615126363933086395263671875
]
}
}
},
"5ad888f375ec25c1c2dd5ac240aeb6063bb2ccd4": {
"identifier": "pts\/rnnoise-1.0.2",
"title": "RNNoise",
"app_version": "2020-06-28",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 16.13700000000000045474735088646411895751953125,
"raw_values": [
16.167000000000001591615728102624416351318359375,
16.135000000000001563194018672220408916473388671875,
16.1099999999999994315658113919198513031005859375
],
"test_run_times": [
16.1700000000000017053025658242404460906982421875,
16.129999999999999005240169935859739780426025390625,
16.1099999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CC",
"compiler": "gcc",
"compiler-options": "-O2 -pedantic -fvisibility=hidden"
}
}
}
}
},
"2a93457bdaa9b0c15e64208f35216483a11a675f": {
"identifier": "pts\/rbenchmark-1.0.3",
"title": "R Benchmark",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 0.1292999999999999982680520815847557969391345977783203125,
"raw_values": [
0.1292107411641700009941047255779267288744449615478515625,
0.128820490779110008450203395113931037485599517822265625,
0.12982003109730000378618797185481525957584381103515625
],
"test_run_times": [
20.6400000000000005684341886080801486968994140625,
20.690000000000001278976924368180334568023681640625,
20.6700000000000017053025658242404460906982421875
],
"details": {
"install-footnote": "R scripting front-end version 4.0.4 (2021-02-15)"
}
}
}
},
"af6599136e056cb3603a463b96c4f0dbdda7e8b5": {
"identifier": "pts\/lczero-1.6.0",
"title": "LeelaChessZero",
"app_version": "0.28",
"arguments": "-b blas",
"description": "Backend: BLAS",
"scale": "Nodes Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 563,
"raw_values": [
579,
544,
567,
580,
551,
566,
557
],
"test_run_times": [
365.259999999999990905052982270717620849609375,
361.740000000000009094947017729282379150390625,
365.29000000000002046363078989088535308837890625,
363.93999999999999772626324556767940521240234375,
363.1299999999999954525264911353588104248046875,
364.58999999999997498889570124447345733642578125,
359.990000000000009094947017729282379150390625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-flto -pthread"
}
}
}
}
},
"293b4cf3607ecd2b75c44445b755a72ec8815954": {
"identifier": "pts\/deepspeech-1.0.0",
"title": "DeepSpeech",
"app_version": "0.6",
"arguments": "CPU",
"description": "Acceleration: CPU",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
1.649999999999999911182158029987476766109466552734375,
0.0200000000000000004163336342344337026588618755340576171875,
0.0200000000000000004163336342344337026588618755340576171875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status."
}
},
"ML Tests": {
"value": 74.4404300000000063164407038129866123199462890625,
"raw_values": [
74.11763999999999441570253111422061920166015625,
74.4980199999999967985786497592926025390625,
74.7056199999999961391949909739196300506591796875
],
"test_run_times": [
50.590000000000003410605131648480892181396484375,
48.840000000000003410605131648480892181396484375,
49.030000000000001136868377216160297393798828125
]
}
}
},
"12916313a24be49739ae0974e3763b30474b135e": {
"identifier": "pts\/numpy-1.2.1",
"title": "Numpy Benchmark",
"scale": "Score",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
1.0800000000000000710542735760100185871124267578125,
0.70999999999999996447286321199499070644378662109375,
0.6999999999999999555910790149937383830547332763671875
],
"details": {
"error": "The test run did not produce a result. The test run did not produce a result. The test run did not produce a result."
}
},
"ML Tests": {
"value": 422.44999999999998863131622783839702606201171875,
"raw_values": [
423.240000000000009094947017729282379150390625,
423.3500000000000227373675443232059478759765625,
420.76999999999998181010596454143524169921875
],
"test_run_times": [
187.460000000000007958078640513122081756591796875,
188.56000000000000227373675443232059478759765625,
187.509999999999990905052982270717620849609375
]
}
}
},
"e6e0b4c00cc7fd68fbaee78fa2a80305e55e35a8": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--matmul --batch=inputs\/matmul\/shapes_transformer --cfg=u8s8f32 --engine=cpu",
"description": "Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 2.986590000000000078017592386459000408649444580078125,
"raw_values": [
2.965240000000000097912788987741805613040924072265625,
2.996989999999999820801122041302733123302459716796875,
2.997549999999999936761696517351083457469940185546875
],
"min_result": [
"2.72"
],
"test_run_times": [
12.0999999999999996447286321199499070644378662109375,
12.089999999999999857891452847979962825775146484375,
12.1099999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"8027ad26272973b77fdbb7b3fd95b00d0faaa2e2": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--rnn --batch=inputs\/rnn\/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu",
"description": "Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.0200000000000000004163336342344337026588618755340576171875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 2237.65000000000009094947017729282379150390625,
"raw_values": [
2244.25,
2422.6199999999998908606357872486114501953125,
2214.80999999999994543031789362430572509765625,
2223.579999999999927240423858165740966796875,
2225.17999999999983629095368087291717529296875,
2237.739999999999781721271574497222900390625,
2225.5,
2219.739999999999781721271574497222900390625,
2201.09000000000014551915228366851806640625,
2207.760000000000218278728425502777099609375,
2244.38999999999987267074175179004669189453125,
2232.1999999999998181010596454143524169921875,
2218.09000000000014551915228366851806640625,
2210.170000000000072759576141834259033203125
],
"min_result": [
"2174.76"
],
"test_run_times": [
78.219999999999998863131622783839702606201171875,
79.0100000000000051159076974727213382720947265625,
78.31999999999999317878973670303821563720703125,
78.43999999999999772626324556767940521240234375,
78.3900000000000005684341886080801486968994140625,
78.3799999999999954525264911353588104248046875,
77.93000000000000682121026329696178436279296875,
78.6400000000000005684341886080801486968994140625,
78.4800000000000039790393202565610408782958984375,
78.3299999999999982946974341757595539093017578125,
78.3299999999999982946974341757595539093017578125,
78.340000000000003410605131648480892181396484375,
77.8900000000000005684341886080801486968994140625,
79.18000000000000682121026329696178436279296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"ea815f8562712ff4b1b5fe6a20bc5429895c24a8": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--rnn --batch=inputs\/rnn\/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu",
"description": "Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 3577,
"raw_values": [
3585.28000000000020008883439004421234130859375,
3577.510000000000218278728425502777099609375,
3568.21999999999979991116560995578765869140625
],
"min_result": [
"3514.72"
],
"test_run_times": [
82.93000000000000682121026329696178436279296875,
82.909999999999996589394868351519107818603515625,
82.8599999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"86ffad59ff08fea12140e0d791917f162f9a38e5": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--matmul --batch=inputs\/matmul\/shapes_transformer --cfg=f32 --engine=cpu",
"description": "Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 4.5934299999999996799715518136508762836456298828125,
"raw_values": [
4.58340000000000014068746168049983680248260498046875,
4.59494000000000024641622076160274446010589599609375,
4.6019600000000000505906427861191332340240478515625
],
"min_result": [
"4.39"
],
"test_run_times": [
12.1400000000000005684341886080801486968994140625,
12.1400000000000005684341886080801486968994140625,
12.1300000000000007815970093361102044582366943359375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"d3e5b4589c59ce5069d8c24bebf659cf520df4f4": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--rnn --batch=inputs\/rnn\/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu",
"description": "Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 2228.170000000000072759576141834259033203125,
"raw_values": [
2221.829999999999927240423858165740966796875,
2221.84000000000014551915228366851806640625,
2240.84000000000014551915228366851806640625
],
"min_result": [
"2189.62"
],
"test_run_times": [
78.6700000000000017053025658242404460906982421875,
78.5199999999999960209606797434389591217041015625,
78.7600000000000051159076974727213382720947265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"a14e0d1294d1b9bc014d2a812680c50c4774f6ab": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--rnn --batch=inputs\/rnn\/perf_rnn_training --cfg=u8s8f32 --engine=cpu",
"description": "Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 3587.170000000000072759576141834259033203125,
"raw_values": [
3581.170000000000072759576141834259033203125,
3595.170000000000072759576141834259033203125,
3585.15999999999985448084771633148193359375
],
"min_result": [
"3527.15"
],
"test_run_times": [
82.840000000000003410605131648480892181396484375,
82.8299999999999982946974341757595539093017578125,
82.9800000000000039790393202565610408782958984375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"1056386ab27f2a97245162efb0c112593abb37e3": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--rnn --batch=inputs\/rnn\/perf_rnn_inference_lb --cfg=f32 --engine=cpu",
"description": "Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 2219.1300000000001091393642127513885498046875,
"raw_values": [
2216.920000000000072759576141834259033203125,
2220.920000000000072759576141834259033203125,
2219.5500000000001818989403545856475830078125
],
"min_result": [
"2182.15"
],
"test_run_times": [
78.030000000000001136868377216160297393798828125,
78.599999999999994315658113919198513031005859375,
78.469999999999998863131622783839702606201171875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"3b7f605c1f6eb3cbd6c396204910eac87afa500e": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--rnn --batch=inputs\/rnn\/perf_rnn_training --cfg=f32 --engine=cpu",
"description": "Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 3579,
"raw_values": [
3581.53000000000020008883439004421234130859375,
3590.34000000000014551915228366851806640625,
3565.1199999999998908606357872486114501953125
],
"min_result": [
"3519.93"
],
"test_run_times": [
82.7399999999999948840923025272786617279052734375,
82.9500000000000028421709430404007434844970703125,
82.81000000000000227373675443232059478759765625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"bf2aa441de2e4e5e1a78fd96f602aad004e05868": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--deconv --batch=inputs\/deconv\/shapes_3d --cfg=u8s8f32 --engine=cpu",
"description": "Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 3.247840000000000060254023992456495761871337890625,
"raw_values": [
3.298529999999999962057017910410650074481964111328125,
3.206679999999999974846787154092453420162200927734375,
3.238309999999999799769057062803767621517181396484375
],
"min_result": [
"2.76"
],
"test_run_times": [
3.029999999999999804600747665972448885440826416015625,
3.04000000000000003552713678800500929355621337890625,
3.029999999999999804600747665972448885440826416015625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"ae8b7e0568abefd9886a8bbbcd7fcb754f45339a": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--deconv --batch=inputs\/deconv\/shapes_1d --cfg=u8s8f32 --engine=cpu",
"description": "Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 2.117710000000000203357330974540673196315765380859375,
"raw_values": [
2.10860000000000002984279490192420780658721923828125,
2.12314999999999987068122209166176617145538330078125,
2.1213899999999998868815964669920504093170166015625
],
"min_result": [
"1.91"
],
"test_run_times": [
21.050000000000000710542735760100185871124267578125,
21.050000000000000710542735760100185871124267578125,
21.03999999999999914734871708787977695465087890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"7d4b51bd744f2cf013fa6ea78a2d27ef34d55f2e": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--conv --batch=inputs\/conv\/shapes_auto --cfg=u8s8f32 --engine=cpu",
"description": "Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 23.767399999999998527755451505072414875030517578125,
"raw_values": [
23.78620000000000089812601800076663494110107421875,
23.72200000000000130739863379858434200286865234375,
23.79390000000000071622707764618098735809326171875
],
"min_result": [
"22.9"
],
"test_run_times": [
6.29000000000000003552713678800500929355621337890625,
6.269999999999999573674358543939888477325439453125,
6.269999999999999573674358543939888477325439453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"c6537ae4b209a5dcc398d287f84d05b3b81aa4b6": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--deconv --batch=inputs\/deconv\/shapes_3d --cfg=f32 --engine=cpu",
"description": "Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 6.74558999999999997498889570124447345733642578125,
"raw_values": [
6.72660999999999997811528373858891427516937255859375,
6.7494899999999997675104168592952191829681396484375,
6.7606599999999996697397364187054336071014404296875
],
"min_result": [
"6.52"
],
"test_run_times": [
3.04999999999999982236431605997495353221893310546875,
3.04999999999999982236431605997495353221893310546875,
3.04000000000000003552713678800500929355621337890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"0e6aec1edabc9355255fd369efefb250e54fa125": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--deconv --batch=inputs\/deconv\/shapes_1d --cfg=f32 --engine=cpu",
"description": "Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 8.34788999999999958845364744774997234344482421875,
"raw_values": [
8.2982999999999993434585121576674282550811767578125,
8.39677999999999968849806464277207851409912109375,
8.3485800000000001119815351557917892932891845703125
],
"min_result": [
"4.75"
],
"test_run_times": [
21.089999999999999857891452847979962825775146484375,
21.0799999999999982946974341757595539093017578125,
21.0799999999999982946974341757595539093017578125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"b985cabe3a95170e0ad621ace9c6a145d60bd49a": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--conv --batch=inputs\/conv\/shapes_auto --cfg=f32 --engine=cpu",
"description": "Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 22.79260000000000019326762412674725055694580078125,
"raw_values": [
22.758500000000001506350599811412394046783447265625,
22.859300000000001062971932697109878063201904296875,
22.759899999999998243538357201032340526580810546875
],
"min_result": [
"21.94"
],
"test_run_times": [
6.269999999999999573674358543939888477325439453125,
6.2599999999999997868371792719699442386627197265625,
6.269999999999999573674358543939888477325439453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"8fa2d8c54bce4215b4b901e88ca19e98e0d95359": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--ip --batch=inputs\/ip\/shapes_3d --cfg=u8s8f32 --engine=cpu",
"description": "Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 2.692099999999999937472239253111183643341064453125,
"raw_values": [
2.696509999999999962483343551866710186004638671875,
2.689439999999999830748720341944135725498199462890625,
2.6903600000000000846966941026039421558380126953125
],
"min_result": [
"2.57"
],
"test_run_times": [
9.230000000000000426325641456060111522674560546875,
9.2200000000000006394884621840901672840118408203125,
9.21000000000000085265128291212022304534912109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"a1109653799c2a426be406810ad457dac49e3134": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--ip --batch=inputs\/ip\/shapes_1d --cfg=u8s8f32 --engine=cpu",
"description": "Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 1.6298500000000000209610107049229554831981658935546875,
"raw_values": [
1.6116699999999999359800995080149732530117034912109375,
1.641329999999999955662133288569748401641845703125,
1.6365600000000000147082346302340738475322723388671875
],
"min_result": [
"1.49"
],
"test_run_times": [
15.0800000000000000710542735760100185871124267578125,
15.07000000000000028421709430404007434844970703125,
15.0800000000000000710542735760100185871124267578125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"b3f85fb1447d5c26415525d50cb84e1d3f109399": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--ip --batch=inputs\/ip\/shapes_3d --cfg=f32 --engine=cpu",
"description": "Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 12.0925999999999991274535204865969717502593994140625,
"raw_values": [
12.059200000000000585487214266322553157806396484375,
12.0775000000000005684341886080801486968994140625,
12.1410000000000000142108547152020037174224853515625
],
"min_result": [
"11.92"
],
"test_run_times": [
9.28999999999999914734871708787977695465087890625,
9.28999999999999914734871708787977695465087890625,
9.300000000000000710542735760100185871124267578125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"122a328f33341df04a1a5fb40e4525857cac08be": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--ip --batch=inputs\/ip\/shapes_1d --cfg=f32 --engine=cpu",
"description": "Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
1.189999999999999946709294817992486059665679931640625,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"value": 4.2585499999999996134647517465054988861083984375,
"raw_values": [
4.17739999999999955804241835721768438816070556640625,
4.422109999999999985220711096189916133880615234375,
4.35686999999999979849008013843558728694915771484375,
4.147529999999999716919774073176085948944091796875,
4.20450000000000034816594052244909107685089111328125,
4.2219899999999999096189640113152563571929931640625,
4.27944000000000013272938303998671472072601318359375
],
"min_result": [
"3.88"
],
"test_run_times": [
15.1400000000000005684341886080801486968994140625,
15.1099999999999994315658113919198513031005859375,
15.1099999999999994315658113919198513031005859375,
15.1099999999999994315658113919198513031005859375,
15.1199999999999992184029906638897955417633056640625,
15.1099999999999994315658113919198513031005859375,
15.0999999999999996447286321199499070644378662109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
}
}
}
}
},
"0991aafbc1109a98b492b3685d378e12b6c347d3": {
"identifier": "pts\/opencv-1.1.0",
"title": "OpenCV",
"app_version": "4.5.4",
"arguments": "dnn",
"description": "Test: DNN - Deep Neural Network",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"value": 13787,
"raw_values": [
12490,
12523,
14957,
15100,
13785,
13644,
13681,
14435,
15056,
14259,
14629,
13587,
13871,
11414,
13371
],
"test_run_times": [
13.8699999999999992184029906638897955417633056640625,
13.8499999999999996447286321199499070644378662109375,
16.32000000000000028421709430404007434844970703125,
16.46000000000000085265128291212022304534912109375,
15.1300000000000007815970093361102044582366943359375,
14.9900000000000002131628207280300557613372802734375,
15.0099999999999997868371792719699442386627197265625,
15.7599999999999997868371792719699442386627197265625,
16.39999999999999857891452847979962825775146484375,
15.5800000000000000710542735760100185871124267578125,
15.949999999999999289457264239899814128875732421875,
14.9199999999999999289457264239899814128875732421875,
15.230000000000000426325641456060111522674560546875,
12.7400000000000002131628207280300557613372802734375,
14.7200000000000006394884621840901672840118408203125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fPIC -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -shared"
}
}
}
}
},
"25093c2395a44dd48770613bc25c2b5e932fa9b3": {
"identifier": "pts\/onnx-1.3.0",
"title": "ONNX Runtime",
"app_version": "1.10",
"arguments": "super_resolution\/super_resolution.onnx -e cpu",
"description": "Model: super-resolution-10 - Device: CPU",
"scale": "Inferences Per Minute",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.0299999999999999988897769753748434595763683319091796875,
0.0299999999999999988897769753748434595763683319091796875,
0.0299999999999999988897769753748434595763683319091796875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt"
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onnxruntime\/onnxruntime\/test\/onnx\/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const PATH_CHAR_TYPE*) open file \"super_resolution\/super_resolution.onnx\" failed: No such file or directory"
}
}
}
},
"57ccc459d2b968bbe0b59791535550f3c44146e5": {
"identifier": "pts\/onnx-1.3.0",
"title": "ONNX Runtime",
"app_version": "1.10",
"arguments": "model\/test_shufflenetv2\/model.onnx -e cpu",
"description": "Model: shufflenet-v2-10 - Device: CPU",
"scale": "Inferences Per Minute",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.0299999999999999988897769753748434595763683319091796875,
0.0299999999999999988897769753748434595763683319091796875,
0.0299999999999999988897769753748434595763683319091796875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt"
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onnxruntime\/onnxruntime\/test\/onnx\/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const PATH_CHAR_TYPE*) open file \"model\/test_shufflenetv2\/model.onnx\" failed: No such file or directory"
}
}
}
},
"1934214642cdc2dfbd31424cb41af4d7455dc15e": {
"identifier": "pts\/onnx-1.3.0",
"title": "ONNX Runtime",
"app_version": "1.10",
"arguments": "fcn-resnet101-11\/model.onnx -e cpu",
"description": "Model: fcn-resnet101-11 - Device: CPU",
"scale": "Inferences Per Minute",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.0299999999999999988897769753748434595763683319091796875,
0.0299999999999999988897769753748434595763683319091796875,
0.0299999999999999988897769753748434595763683319091796875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt"
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onnxruntime\/onnxruntime\/test\/onnx\/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const PATH_CHAR_TYPE*) open file \"fcn-resnet101-11\/model.onnx\" failed: No such file or directory"
}
}
}
},
"6da6b09e8df7dbffd8bc61a5a389f630a008e6f3": {
"identifier": "pts\/onnx-1.3.0",
"title": "ONNX Runtime",
"app_version": "1.10",
"arguments": "yolov4\/yolov4.onnx -e cpu",
"description": "Model: yolov4 - Device: CPU",
"scale": "Inferences Per Minute",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.05000000000000000277555756156289135105907917022705078125,
0.0299999999999999988897769753748434595763683319091796875,
0.0299999999999999988897769753748434595763683319091796875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-ffunction-sections -fdata-sections -march=native -mtune=native -O3 -flto -fno-fat-lto-objects -ldl -lrt"
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onnxruntime\/onnxruntime\/test\/onnx\/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const PATH_CHAR_TYPE*) open file \"yolov4\/yolov4.onnx\" failed: No such file or directory"
}
}
}
},
"26d93e7902d709791e1e5e1dac911495394412c1": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/age-gender-recognition-retail-0013\/FP32\/age-gender-recognition-retail-0013.xml -d GPU",
"description": "Model: Age Gender Recognition Retail 0013 FP32 - Device: Intel GPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"d301cb8df76f1c50fb81dff002e4201754c3b997": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/age-gender-recognition-retail-0013\/FP16\/age-gender-recognition-retail-0013.xml -d GPU",
"description": "Model: Age Gender Recognition Retail 0013 FP16 - Device: Intel GPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"9799446e3a0d39f3e68c9a61bff1151085f63adc": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/age-gender-recognition-retail-0013\/FP32\/age-gender-recognition-retail-0013.xml -d CPU",
"description": "Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"a00f227bd7182f2fd6fe142abd4b8d39c28f4364": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/age-gender-recognition-retail-0013\/FP16\/age-gender-recognition-retail-0013.xml -d CPU",
"description": "Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"58d0b359779c1036d007ea3619b94dce36767250": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/person-detection-0106\/FP32\/person-detection-0106.xml -d GPU",
"description": "Model: Person Detection 0106 FP32 - Device: Intel GPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"21a99a25bb3bebf43bb5c08f5237320186c7d449": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/person-detection-0106\/FP16\/person-detection-0106.xml -d GPU",
"description": "Model: Person Detection 0106 FP16 - Device: Intel GPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"6a177f370c74341a739d6b783ff03ca6c2646c1d": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/face-detection-0106\/FP32\/face-detection-0106.xml -d GPU",
"description": "Model: Face Detection 0106 FP32 - Device: Intel GPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0,
0,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"dc1053a8848ed048b486d469b595d565b0523075": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/face-detection-0106\/FP16\/face-detection-0106.xml -d GPU",
"description": "Model: Face Detection 0106 FP16 - Device: Intel GPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0,
0
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"53da1fce0aaaadfc4e5d6887a5407344329d7056": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/person-detection-0106\/FP32\/person-detection-0106.xml -d CPU",
"description": "Model: Person Detection 0106 FP32 - Device: CPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"62474cc0c8c4d942b229a261d1c36d9c30fac5e0": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/person-detection-0106\/FP16\/person-detection-0106.xml -d CPU",
"description": "Model: Person Detection 0106 FP16 - Device: CPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"00229be3e9e451a84857092389adf2a9fd877f15": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/face-detection-0106\/FP32\/face-detection-0106.xml -d CPU",
"description": "Model: Face Detection 0106 FP32 - Device: CPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"2672d93e949e09dd87155b9c4fb5630e9223ffa6": {
"identifier": "pts\/openvino-1.0.4",
"title": "OpenVINO",
"app_version": "2021.1",
"arguments": "-m models\/intel\/face-detection-0106\/FP16\/face-detection-0106.xml -d CPU",
"description": "Model: Face Detection 0106 FP16 - Device: CPU",
"scale": "FPS",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": ""
},
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: .\/openvino: line 2: .\/openvino-github-2021\/bin\/intel64\/Release\/benchmark_app: No such file or directory"
}
}
}
},
"aadc79deffdd3ba388c4abc444ab3e02765cc8b1": {
"identifier": "pts\/tensorflow-1.1.0",
"title": "Tensorflow",
"arguments": "cifar10_train.py --max_steps 1000",
"description": "Build: Cifar10",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"ML Tests": {
"test_run_times": [
2.439999999999999946709294817992486059665679931640625,
1.270000000000000017763568394002504646778106689453125,
1.270000000000000017763568394002504646778106689453125
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: AttributeError: module 'tensorflow' has no attribute 'app'"
}
}
}
},
"a409d1309dc0a0f0a4a05f2d00c44948890c0936": {
"identifier": "pts\/ai-benchmark-1.0.1",
"title": "AI Benchmark Alpha",
"app_version": "0.1.2",
"scale": "Score",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.2600000000000000088817841970012523233890533447265625
],
"details": {
"error": "The test quit with a non-zero exit status. E: SyntaxError: invalid syntax"
}
},
"ML Tests": {
"test_run_times": [
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'tensorflow'"
}
}
}
},
"079aa5817d5bef44bc308e7ae9d753f8a8f89915": {
"identifier": "pts\/numenta-nab-1.1.0",
"title": "Numenta Anomaly Benchmark",
"app_version": "1.1",
"arguments": "-d bayesChangePt",
"description": "Detector: Bayesian Changepoint",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.08000000000000000166533453693773481063544750213623046875,
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
},
"ML Tests": {
"test_run_times": [
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
}
}
},
"6e3eb32d13f90dd05c98187cf34f2437bd2825cf": {
"identifier": "pts\/numenta-nab-1.1.0",
"title": "Numenta Anomaly Benchmark",
"app_version": "1.1",
"arguments": "-d earthgeckoSkyline",
"description": "Detector: Earthgecko Skyline",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
},
"ML Tests": {
"test_run_times": [
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
}
}
},
"b19b34a0bd8b6ebed7bd9d44c213242b88abbe5a": {
"identifier": "pts\/numenta-nab-1.1.0",
"title": "Numenta Anomaly Benchmark",
"app_version": "1.1",
"arguments": "-d windowedGaussian",
"description": "Detector: Windowed Gaussian",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
},
"ML Tests": {
"test_run_times": [
0.070000000000000006661338147750939242541790008544921875,
0.059999999999999997779553950749686919152736663818359375,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
}
}
},
"6e59f9f08ca57efc8f7abce6b6fe6d161fdc3a02": {
"identifier": "pts\/numenta-nab-1.1.0",
"title": "Numenta Anomaly Benchmark",
"app_version": "1.1",
"arguments": "-d relativeEntropy",
"description": "Detector: Relative Entropy",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.08000000000000000166533453693773481063544750213623046875,
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
},
"ML Tests": {
"test_run_times": [
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
}
}
},
"40fb26d4dc900260ca7a9cd2f588a2437aab8d8d": {
"identifier": "pts\/numenta-nab-1.1.0",
"title": "Numenta Anomaly Benchmark",
"app_version": "1.1",
"arguments": "-d expose",
"description": "Detector: EXPoSE",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.450000000000000011102230246251565404236316680908203125,
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
},
"ML Tests": {
"test_run_times": [
0.0899999999999999966693309261245303787291049957275390625,
0.070000000000000006661338147750939242541790008544921875,
0.070000000000000006661338147750939242541790008544921875
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'"
}
}
}
},
"d4cd395254971ce717360cc0086142b6cbbc2290": {
"identifier": "pts\/mnn-1.3.0",
"title": "Mobile Neural Network",
"app_version": "1.2",
"description": "Model: inception-v3",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 58.2530000000000001136868377216160297393798828125,
"raw_values": [
90.5969999999999942019712761975824832916259765625,
64.6219999999999998863131622783839702606201171875,
60.79899999999999948840923025272786617279052734375,
45.22399999999999664623828721232712268829345703125,
44.59700000000000130739863379858434200286865234375,
44.54599999999999937472239253111183643341064453125,
44.59599999999999653255144949071109294891357421875,
44.792000000000001591615728102624416351318359375,
84.5030000000000001136868377216160297393798828125
],
"min_result": [
"30.46"
],
"max_result": [
"200.21"
],
"test_run_times": [
265.26999999999998181010596454143524169921875,
216.8899999999999863575794734060764312744140625,
212.280000000000001136868377216160297393798828125,
199.539999999999992041921359486877918243408203125,
195.1200000000000045474735088646411895751953125,
194.969999999999998863131622783839702606201171875,
194.8799999999999954525264911353588104248046875,
192.830000000000012505552149377763271331787109375,
236.830000000000012505552149377763271331787109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -arch -isysroot"
}
}
},
"ML Tests": {
"value": 31.57600000000000051159076974727213382720947265625,
"raw_values": [
32.39399999999999835154085303656756877899169921875,
31.321000000000001506350599811412394046783447265625,
31.013999999999999346300683100707828998565673828125
],
"min_result": [
"29.6"
],
"max_result": [
"48.32"
],
"test_run_times": [
85.8900000000000005684341886080801486968994140625,
84.409999999999996589394868351519107818603515625,
83.9200000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl"
}
}
}
}
},
"a1e7030f66b94982bc7821cf6072db4c27d93328": {
"identifier": "pts\/mnn-1.3.0",
"title": "Mobile Neural Network",
"app_version": "1.2",
"description": "Model: mobilenet-v1-1.0",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 8.2050000000000000710542735760100185871124267578125,
"raw_values": [
10.7409999999999996589394868351519107818603515625,
8.541000000000000369482222595252096652984619140625,
9.358000000000000540012479177676141262054443359375,
7.474000000000000198951966012828052043914794921875,
7.52099999999999990762944435118697583675384521484375,
7.69099999999999983657517077517695724964141845703125,
7.467999999999999971578290569595992565155029296875,
7.47299999999999986499688020558096468448638916015625,
7.57599999999999962341235004714690148830413818359375
],
"min_result": [
"4.27"
],
"max_result": [
"48.5"
],
"test_run_times": [
265.26999999999998181010596454143524169921875,
216.8899999999999863575794734060764312744140625,
212.280000000000001136868377216160297393798828125,
199.539999999999992041921359486877918243408203125,
195.1200000000000045474735088646411895751953125,
194.969999999999998863131622783839702606201171875,
194.8799999999999954525264911353588104248046875,
192.830000000000012505552149377763271331787109375,
236.830000000000012505552149377763271331787109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -arch -isysroot"
}
}
},
"ML Tests": {
"value": 2.439999999999999946709294817992486059665679931640625,
"raw_values": [
2.404999999999999804600747665972448885440826416015625,
2.444999999999999840127884453977458178997039794921875,
2.471000000000000085265128291212022304534912109375
],
"min_result": [
"2.17"
],
"max_result": [
"18"
],
"test_run_times": [
85.8900000000000005684341886080801486968994140625,
84.409999999999996589394868351519107818603515625,
83.9200000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl"
}
}
}
}
},
"71341d8fdacb736deb926575279eb7292fada1ef": {
"identifier": "pts\/mnn-1.3.0",
"title": "Mobile Neural Network",
"app_version": "1.2",
"description": "Model: SqueezeNetV1.0",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 9.9670000000000005258016244624741375446319580078125,
"raw_values": [
15.03999999999999914734871708787977695465087890625,
10.5250000000000003552713678800500929355621337890625,
10.0540000000000002700062395888380706310272216796875,
9.0690000000000008384404281969182193279266357421875,
9.0009999999999994457766661071218550205230712890625,
9.321999999999999175770426518283784389495849609375,
9.131000000000000227373675443232059478759765625,
8.6059999999999998721023075631819665431976318359375,
8.9550000000000000710542735760100185871124267578125
],
"min_result": [
"4.34"
],
"max_result": [
"49.52"
],
"test_run_times": [
265.26999999999998181010596454143524169921875,
216.8899999999999863575794734060764312744140625,
212.280000000000001136868377216160297393798828125,
199.539999999999992041921359486877918243408203125,
195.1200000000000045474735088646411895751953125,
194.969999999999998863131622783839702606201171875,
194.8799999999999954525264911353588104248046875,
192.830000000000012505552149377763271331787109375,
236.830000000000012505552149377763271331787109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -arch -isysroot"
}
}
},
"ML Tests": {
"value": 4.54600000000000026290081223123706877231597900390625,
"raw_values": [
4.62300000000000022026824808563105762004852294921875,
4.525999999999999801048033987171947956085205078125,
4.4900000000000002131628207280300557613372802734375
],
"min_result": [
"4.32"
],
"max_result": [
"20.48"
],
"test_run_times": [
85.8900000000000005684341886080801486968994140625,
84.409999999999996589394868351519107818603515625,
83.9200000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl"
}
}
}
}
},
"0c6e313d740307fe31abbdae6301a30c33b7f41c": {
"identifier": "pts\/mnn-1.3.0",
"title": "Mobile Neural Network",
"app_version": "1.2",
"description": "Model: resnet-v2-50",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 42.4279999999999972715158946812152862548828125,
"raw_values": [
60.042000000000001591615728102624416351318359375,
59.6009999999999990905052982270717620849609375,
57.49300000000000210320649784989655017852783203125,
36.453000000000002955857780762016773223876953125,
33.59400000000000119371179607696831226348876953125,
33.74000000000000198951966012828052043914794921875,
33.53099999999999880628820392303168773651123046875,
33.4560000000000030695446184836328029632568359375,
33.93999999999999772626324556767940521240234375
],
"min_result": [
"24"
],
"max_result": [
"197.77"
],
"test_run_times": [
265.26999999999998181010596454143524169921875,
216.8899999999999863575794734060764312744140625,
212.280000000000001136868377216160297393798828125,
199.539999999999992041921359486877918243408203125,
195.1200000000000045474735088646411895751953125,
194.969999999999998863131622783839702606201171875,
194.8799999999999954525264911353588104248046875,
192.830000000000012505552149377763271331787109375,
236.830000000000012505552149377763271331787109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -arch -isysroot"
}
}
},
"ML Tests": {
"value": 22.440999999999998948396751075051724910736083984375,
"raw_values": [
22.6039999999999992041921359486877918243408203125,
22.407000000000000028421709430404007434844970703125,
22.31099999999999994315658113919198513031005859375
],
"min_result": [
"21.5"
],
"max_result": [
"43.07"
],
"test_run_times": [
85.8900000000000005684341886080801486968994140625,
84.409999999999996589394868351519107818603515625,
83.9200000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl"
}
}
}
}
},
"05b34d18f424ac328d8bb8f8967b1a9f2c5105da": {
"identifier": "pts\/mnn-1.3.0",
"title": "Mobile Neural Network",
"app_version": "1.2",
"description": "Model: squeezenetv1.1",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 7.27400000000000002131628207280300557613372802734375,
"raw_values": [
9.8770000000000006679101716144941747188568115234375,
6.4580000000000001847411112976260483264923095703125,
6.37399999999999966604491419275291264057159423828125,
7.025999999999999801048033987171947956085205078125,
6.894999999999999573674358543939888477325439453125,
7.217999999999999971578290569595992565155029296875,
7.2590000000000003410605131648480892181396484375,
6.96699999999999963762320476234890520572662353515625,
7.38999999999999968025576890795491635799407958984375
],
"min_result": [
"2.75"
],
"max_result": [
"117.92"
],
"test_run_times": [
265.26999999999998181010596454143524169921875,
216.8899999999999863575794734060764312744140625,
212.280000000000001136868377216160297393798828125,
199.539999999999992041921359486877918243408203125,
195.1200000000000045474735088646411895751953125,
194.969999999999998863131622783839702606201171875,
194.8799999999999954525264911353588104248046875,
192.830000000000012505552149377763271331787109375,
236.830000000000012505552149377763271331787109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -arch -isysroot"
}
}
},
"ML Tests": {
"value": 2.80299999999999993605115378159098327159881591796875,
"raw_values": [
2.786000000000000031974423109204508364200592041015625,
2.81099999999999994315658113919198513031005859375,
2.813000000000000166977542903623543679714202880859375
],
"min_result": [
"2.6"
],
"max_result": [
"17.21"
],
"test_run_times": [
85.8900000000000005684341886080801486968994140625,
84.409999999999996589394868351519107818603515625,
83.9200000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl"
}
}
}
}
},
"1e3818f3718ae477ce1d714764aefe7091cc8f81": {
"identifier": "pts\/mnn-1.3.0",
"title": "Mobile Neural Network",
"app_version": "1.2",
"description": "Model: mobilenetV3",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"value": 9.1519999999999992468247000942938029766082763671875,
"raw_values": [
7.54399999999999959499064061674289405345916748046875,
7.20000000000000017763568394002504646778106689453125,
6.907000000000000028421709430404007434844970703125,
10.1489999999999991331378623726777732372283935546875,
10.125,
10.2189999999999994173549566767178475856781005859375,
10.083999999999999630517777404747903347015380859375,
9.989000000000000767386154620908200740814208984375,
10.150999999999999801048033987171947956085205078125
],
"min_result": [
"3.37"
],
"max_result": [
"58.79"
],
"test_run_times": [
265.26999999999998181010596454143524169921875,
216.8899999999999863575794734060764312744140625,
212.280000000000001136868377216160297393798828125,
199.539999999999992041921359486877918243408203125,
195.1200000000000045474735088646411895751953125,
194.969999999999998863131622783839702606201171875,
194.8799999999999954525264911353588104248046875,
192.830000000000012505552149377763271331787109375,
236.830000000000012505552149377763271331787109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -arch -isysroot"
}
}
},
"ML Tests": {
"value": 1.2019999999999999573674358543939888477325439453125,
"raw_values": [
1.209000000000000074606987254810519516468048095703125,
1.193000000000000060396132539608515799045562744140625,
1.2039999999999999591437926937942393124103546142578125
],
"min_result": [
"1.15"
],
"max_result": [
"10.7"
],
"test_run_times": [
85.8900000000000005684341886080801486968994140625,
84.409999999999996589394868351519107818603515625,
83.9200000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl"
}
}
}
}
},
"1d5e04ee0f7ff85aee1e2bb8b1e3cb4139ce9aa0": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--matmul --batch=inputs\/matmul\/shapes_transformer --cfg=bf16bf16bf16 --engine=cpu",
"description": "Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
},
"error": "The test run did not produce a result. The test run did not produce a result. The test run did not produce a result."
}
}
}
},
"7142176a4bc77f6374ea00ce7f7ff1afbab8b50f": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--deconv --batch=inputs\/deconv\/shapes_3d --cfg=bf16bf16bf16 --engine=cpu",
"description": "Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
},
"error": "The test run did not produce a result. The test run did not produce a result. The test run did not produce a result."
}
}
}
},
"4399d02224793ce417cc9fed89c2bf5ac010e9c5": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--deconv --batch=inputs\/deconv\/shapes_1d --cfg=bf16bf16bf16 --engine=cpu",
"description": "Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
},
"error": "The test run did not produce a result. The test run did not produce a result. The test run did not produce a result."
}
}
}
},
"764a9da79f79bc91b2eab6537f7d72874238eaf2": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--conv --batch=inputs\/conv\/shapes_auto --cfg=bf16bf16bf16 --engine=cpu",
"description": "Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.0200000000000000004163336342344337026588618755340576171875,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
},
"error": "The test run did not produce a result. The test run did not produce a result. The test run did not produce a result."
}
}
}
},
"3ebc08f1632a997c2d4096ce33c3037d73f0010e": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--ip --batch=inputs\/ip\/shapes_3d --cfg=bf16bf16bf16 --engine=cpu",
"description": "Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
},
"error": "The test run did not produce a result. The test run did not produce a result. The test run did not produce a result."
}
}
}
},
"ff41d6b2ca572eee8388a7a39ec38fce8eeab3f1": {
"identifier": "pts\/onednn-1.7.0",
"title": "oneDNN",
"app_version": "2.1.2",
"arguments": "--ip --batch=inputs\/ip\/shapes_1d --cfg=bf16bf16bf16 --engine=cpu",
"description": "Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"MBP M1 Max Machine Learning": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.0200000000000000004163336342344337026588618755340576171875,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"error": "The test quit with a non-zero exit status. The test quit with a non-zero exit status. The test quit with a non-zero exit status. E: onednn: line 6: .\/benchdnn: No such file or directory"
}
},
"ML Tests": {
"test_run_times": [
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375,
0.01000000000000000020816681711721685132943093776702880859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -std=c++11 -fopenmp -msse4.1 -fPIC -pie -ldl -lpthread"
},
"error": "The test run did not produce a result. The test run did not produce a result. The test run did not produce a result."
}
}
}
}
}
}