2 x AMD EPYC 9684X 96-Core testing with a AMD Titanite_4G (RTI1007B BIOS) and ASPEED on Ubuntu 23.10 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 2403274-NE-9684XMARC65
{
"title": "9684x-march ",
"last_modified": "2024-03-27 15:04:14",
"description": "2 x AMD EPYC 9684X 96-Core testing with a AMD Titanite_4G (RTI1007B BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.",
"systems": {
"PRE": {
"identifier": "PRE",
"hardware": {
"Processor": "2 x AMD EPYC 9684X 96-Core @ 2.55GHz (192 Cores \/ 384 Threads)",
"Motherboard": "AMD Titanite_4G (RTI1007B BIOS)",
"Chipset": "AMD Device 14a4",
"Memory": "1520GB",
"Disk": "3201GB Micron_7450_MTFDKCB3T2TFS + 257GB Flash Drive",
"Graphics": "ASPEED",
"Network": "Broadcom NetXtreme BCM5720 PCIe"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.5.0-25-generic (x86_64)",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "640x480"
},
"user": "phoronix",
"timestamp": "2024-03-27 00:14:41",
"client_version": "10.8.4",
"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,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-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/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 performance (Boost: Enabled)",
"cpu-microcode": "0xa10113e",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.11.6",
"security": "gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of Safe RET + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced \/ Automatic IBRS IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"a": {
"identifier": "a",
"hardware": {
"Processor": "2 x AMD EPYC 9684X 96-Core @ 2.55GHz (192 Cores \/ 384 Threads)",
"Motherboard": "AMD Titanite_4G (RTI1007B BIOS)",
"Chipset": "AMD Device 14a4",
"Memory": "1520GB",
"Disk": "3201GB Micron_7450_MTFDKCB3T2TFS + 257GB Flash Drive",
"Graphics": "ASPEED",
"Network": "Broadcom NetXtreme BCM5720 PCIe"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.5.0-25-generic (x86_64)",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "640x480"
},
"user": "phoronix",
"timestamp": "2024-03-27 02:15:31",
"client_version": "10.8.4",
"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,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-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/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 performance (Boost: Enabled)",
"cpu-microcode": "0xa10113e",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.11.6",
"security": "gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of Safe RET + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced \/ Automatic IBRS IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"b": {
"identifier": "b",
"hardware": {
"Processor": "2 x AMD EPYC 9684X 96-Core @ 2.55GHz (192 Cores \/ 384 Threads)",
"Motherboard": "AMD Titanite_4G (RTI1007B BIOS)",
"Chipset": "AMD Device 14a4",
"Memory": "1520GB",
"Disk": "3201GB Micron_7450_MTFDKCB3T2TFS + 257GB Flash Drive",
"Graphics": "ASPEED",
"Network": "Broadcom NetXtreme BCM5720 PCIe"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.5.0-25-generic (x86_64)",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "640x480"
},
"user": "phoronix",
"timestamp": "2024-03-27 12:04:05",
"client_version": "10.8.4",
"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,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-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/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 performance (Boost: Enabled)",
"cpu-microcode": "0xa10113e",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.11.6",
"security": "gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of Safe RET + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced \/ Automatic IBRS IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
}
},
"results": {
"6fa0bb21f313981869d5b7153599c8cd97c5852a": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: BMW27 - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 7.54999999999999982236431605997495353221893310546875,
"test_run_times": [
8.07000000000000028421709430404007434844970703125
]
},
"a": {
"value": 7.54999999999999982236431605997495353221893310546875,
"test_run_times": [
8.589999999999999857891452847979962825775146484375
]
},
"b": {
"value": 7.480000000000000426325641456060111522674560546875,
"test_run_times": [
8.019999999999999573674358543939888477325439453125
]
}
}
},
"9974b636362d9b68a14abd18b674acca424c3a28": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/junkshop.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Junkshop - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 11.4000000000000003552713678800500929355621337890625,
"test_run_times": [
12.1199999999999992184029906638897955417633056640625
]
},
"a": {
"value": 11.4399999999999995026200849679298698902130126953125,
"test_run_times": [
12.17999999999999971578290569595992565155029296875
]
},
"b": {
"value": 11.6099999999999994315658113919198513031005859375,
"test_run_times": [
12.32000000000000028421709430404007434844970703125
]
}
}
},
"d642e29ba0ab924a63605dc5d18ef3966c809dce": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Classroom - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 18.030000000000001136868377216160297393798828125,
"test_run_times": [
18.550000000000000710542735760100185871124267578125
]
},
"a": {
"value": 18.0799999999999982946974341757595539093017578125,
"test_run_times": [
18.6400000000000005684341886080801486968994140625
]
},
"b": {
"value": 18.03999999999999914734871708787977695465087890625,
"test_run_times": [
18.550000000000000710542735760100185871124267578125
]
}
}
},
"e14b90554ad557bd8220d6925e62f507c49196e0": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Fishy Cat - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 9.96000000000000085265128291212022304534912109375,
"test_run_times": [
10.7799999999999993605115378159098327159881591796875
]
},
"a": {
"value": 9.8499999999999996447286321199499070644378662109375,
"test_run_times": [
10.6500000000000003552713678800500929355621337890625
]
},
"b": {
"value": 9.9399999999999995026200849679298698902130126953125,
"test_run_times": [
10.7599999999999997868371792719699442386627197265625
]
}
}
},
"458a4eb2c6c84b80913e52a3b3e727db73a5af11": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Barbershop - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 67.3799999999999954525264911353588104248046875,
"test_run_times": [
69.81999999999999317878973670303821563720703125
]
},
"a": {
"value": 67.659999999999996589394868351519107818603515625,
"test_run_times": [
69.9599999999999937472239253111183643341064453125
]
},
"b": {
"value": 67.650000000000005684341886080801486968994140625,
"test_run_times": [
69.9800000000000039790393202565610408782958984375
]
}
}
},
"30a7337e8926a086e67a974609766f8885e04e46": {
"identifier": "pts\/blender-4.1.0",
"title": "Blender",
"app_version": "4.1",
"arguments": "-b ..\/pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU",
"description": "Blend File: Pabellon Barcelona - Compute: CPU-Only",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 22.989999999999998436805981327779591083526611328125,
"test_run_times": [
23.690000000000001278976924368180334568023681640625
]
},
"a": {
"value": 23.10000000000000142108547152020037174224853515625,
"test_run_times": [
23.780000000000001136868377216160297393798828125
]
},
"b": {
"value": 23.1099999999999994315658113919198513031005859375,
"test_run_times": [
23.800000000000000710542735760100185871124267578125
]
}
}
},
"59c7fed087ff591e1c14fc2fa2069302338fbf1c": {
"identifier": "pts\/brl-cad-1.6.0",
"title": "BRL-CAD",
"app_version": "7.38.2",
"description": "VGR Performance Metric",
"scale": "VGR Performance Metric",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 5956612,
"test_run_times": [
2174.90999999999985448084771633148193359375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++17 -pipe -fvisibility=hidden -fno-strict-aliasing -fno-common -fexceptions -ftemplate-depth-128 -m64 -ggdb3 -O3 -fipa-pta -fstrength-reduce -finline-functions -flto -ltcl8.6 -lnetpbm -lregex_brl -lz_brl -lassimp -ldl -lm -ltk8.6"
}
}
},
"a": {
"value": 5927564,
"test_run_times": [
2097.6300000000001091393642127513885498046875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++17 -pipe -fvisibility=hidden -fno-strict-aliasing -fno-common -fexceptions -ftemplate-depth-128 -m64 -ggdb3 -O3 -fipa-pta -fstrength-reduce -finline-functions -flto -ltcl8.6 -lnetpbm -lregex_brl -lz_brl -lassimp -ldl -lm -ltk8.6"
}
}
},
"b": {
"value": 5794040,
"test_run_times": [
2092.34999999999990905052982270717620849609375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-std=c++17 -pipe -fvisibility=hidden -fno-strict-aliasing -fno-common -fexceptions -ftemplate-depth-128 -m64 -ggdb3 -O3 -fipa-pta -fstrength-reduce -finline-functions -flto -ltcl8.6 -lnetpbm -lregex_brl -lz_brl -lassimp -ldl -lm -ltk8.6"
}
}
}
}
},
"d0adcab531e05f3db8c970385d100006ac333e7f": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 1 resnet50",
"description": "Device: CPU - Batch Size: 1 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 23.059999999999998721023075631819665431976318359375,
"raw_values": [
23.064308582498998845267124124802649021148681640625
],
"min_result": [
"12.95"
],
"max_result": [
"24.52"
],
"test_run_times": [
51.3599999999999994315658113919198513031005859375
]
},
"a": {
"value": 23.199999999999999289457264239899814128875732421875,
"raw_values": [
23.98400323095300024078824208118021488189697265625,
22.385386961714001330392420641146600246429443359375,
23.310900502645001353130282950587570667266845703125,
22.658367737685001230829584528692066669464111328125,
23.544951095883998704039186122827231884002685546875,
24.060067656796999102652989677153527736663818359375,
23.726918747092998529524265904910862445831298828125,
22.010256630612001771396535332314670085906982421875,
23.548575374529999493233844987116754055023193359375,
24.010682262673999076696418342180550098419189453125,
24.015754907247998772845676285214722156524658203125,
22.832300026656998426233258214779198169708251953125,
21.57623260463299885714150150306522846221923828125,
23.053124368342000849452233524061739444732666015625,
23.229685572472998700277457828633487224578857421875
],
"min_result": [
"12.21"
],
"max_result": [
"25.13"
],
"test_run_times": [
49.8900000000000005684341886080801486968994140625,
52.780000000000001136868377216160297393798828125,
50.88000000000000255795384873636066913604736328125,
52.159999999999996589394868351519107818603515625,
50.5499999999999971578290569595992565155029296875,
49.409999999999996589394868351519107818603515625,
50.1099999999999994315658113919198513031005859375,
53.590000000000003410605131648480892181396484375,
50.4200000000000017053025658242404460906982421875,
49.49000000000000198951966012828052043914794921875,
49.52000000000000312638803734444081783294677734375,
51.9200000000000017053025658242404460906982421875,
54.61999999999999744204615126363933086395263671875,
51.36999999999999744204615126363933086395263671875,
51.13000000000000255795384873636066913604736328125
]
},
"b": {
"value": 23.239999999999998436805981327779591083526611328125,
"raw_values": [
23.23893169212799847400674480013549327850341796875
],
"min_result": [
"13.48"
],
"max_result": [
"24.22"
],
"test_run_times": [
51.00999999999999801048033987171947956085205078125
]
}
}
},
"2bc391ee0b594811f657300072fb2a46f2a71e6e": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 1 resnet152",
"description": "Device: CPU - Batch Size: 1 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 9.9700000000000006394884621840901672840118408203125,
"raw_values": [
9.96586025483220083742708084173500537872314453125
],
"min_result": [
"4.85"
],
"max_result": [
"10.69"
],
"test_run_times": [
115.18000000000000682121026329696178436279296875
]
},
"a": {
"value": 10.5800000000000000710542735760100185871124267578125,
"raw_values": [
10.5467705533050004618189632310532033443450927734375,
10.6849503548129991514770154026336967945098876953125,
11.105298998845999136619866476394236087799072265625,
9.985966879336299228953066631220281124114990234375,
10.9449969350380005295164664858020842075347900390625,
11.1043122241839995467671542428433895111083984375,
10.5625689833200002709645559662021696567535400390625,
10.7039675552169999406260103569366037845611572265625,
10.17704190556599996853037737309932708740234375,
9.7716874937444995197211028425954282283782958984375,
10.830720992267000468700643978081643581390380859375,
10.43519230972299993709384580142796039581298828125,
10.495673607821000672402078635059297084808349609375,
10.6044230225099997966253795311786234378814697265625,
10.6953008801090003743183842743746936321258544921875
],
"min_result": [
"4.55"
],
"max_result": [
"11.67"
],
"test_run_times": [
109.06999999999999317878973670303821563720703125,
107.8599999999999994315658113919198513031005859375,
104.099999999999994315658113919198513031005859375,
114.93000000000000682121026329696178436279296875,
105.06999999999999317878973670303821563720703125,
104.43000000000000682121026329696178436279296875,
108.650000000000005684341886080801486968994140625,
107.659999999999996589394868351519107818603515625,
112.900000000000005684341886080801486968994140625,
117.2699999999999960209606797434389591217041015625,
106.659999999999996589394868351519107818603515625,
110.3799999999999954525264911353588104248046875,
109.7900000000000062527760746888816356658935546875,
108.4500000000000028421709430404007434844970703125,
108
]
},
"b": {
"value": 10.5999999999999996447286321199499070644378662109375,
"raw_values": [
10.5986381889390006705298219458200037479400634765625
],
"min_result": [
"4.86"
],
"max_result": [
"11.57"
],
"test_run_times": [
108.5
]
}
}
},
"1817b719ec4714ac77d1b79b309bdc2361beb3cf": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 16 resnet50",
"description": "Device: CPU - Batch Size: 16 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 20.92999999999999971578290569595992565155029296875,
"raw_values": [
20.927246190908999068369666929356753826141357421875
],
"min_result": [
"12.91"
],
"max_result": [
"21.51"
],
"test_run_times": [
106.8799999999999954525264911353588104248046875
]
},
"a": {
"value": 21.530000000000001136868377216160297393798828125,
"raw_values": [
21.667819766291000149749379488639533519744873046875,
21.708026180560000995001246337778866291046142578125,
21.220377003088998435487155802547931671142578125
],
"min_result": [
"12.64"
],
"max_result": [
"22.28"
],
"test_run_times": [
101.9800000000000039790393202565610408782958984375,
100.8799999999999954525264911353588104248046875,
102.650000000000005684341886080801486968994140625
]
},
"b": {
"value": 20.3599999999999994315658113919198513031005859375,
"raw_values": [
20.361681147094000010611125617288053035736083984375
],
"min_result": [
"11.37"
],
"max_result": [
"21.4"
],
"test_run_times": [
108.469999999999998863131622783839702606201171875
]
}
}
},
"5bb5428bac71de14e9e94ef4b2c074689a36c369": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 32 resnet50",
"description": "Device: CPU - Batch Size: 32 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 20.190000000000001278976924368180334568023681640625,
"raw_values": [
20.191276470064000392312664189375936985015869140625
],
"min_result": [
"11.95"
],
"max_result": [
"21.04"
],
"test_run_times": [
106.2900000000000062527760746888816356658935546875
]
},
"a": {
"value": 20.839999999999999857891452847979962825775146484375,
"raw_values": [
20.392266512431998393140020198188722133636474609375,
20.58150581633800157987934653647243976593017578125,
19.160659132961999517874573939479887485504150390625,
20.839363178641999496676362468861043453216552734375,
20.827096426823999308908241800963878631591796875,
21.519201451680000758415189920924603939056396484375,
20.323975220183999823575504706241190433502197265625,
21.11513709971099927997784106992185115814208984375,
20.440739647811000168076134286820888519287109375,
20.912222479991999790627232869155704975128173828125,
21.5564458031630010736989788711071014404296875,
20.933280872291998520040579023770987987518310546875,
21.549491191775000942243423196487128734588623046875,
21.43444876574000090840854682028293609619140625,
21.015563614036000927853820030577480792999267578125
],
"min_result": [
"11.24"
],
"max_result": [
"22.33"
],
"test_run_times": [
105.159999999999996589394868351519107818603515625,
104.4899999999999948840923025272786617279052734375,
107.43999999999999772626324556767940521240234375,
103.0400000000000062527760746888816356658935546875,
102.81999999999999317878973670303821563720703125,
102.0499999999999971578290569595992565155029296875,
105.3799999999999954525264911353588104248046875,
103.8799999999999954525264911353588104248046875,
105.25,
103.6400000000000005684341886080801486968994140625,
102.2300000000000039790393202565610408782958984375,
105.6700000000000017053025658242404460906982421875,
103.4800000000000039790393202565610408782958984375,
103.6700000000000017053025658242404460906982421875,
102.219999999999998863131622783839702606201171875
]
},
"b": {
"value": 21.030000000000001136868377216160297393798828125,
"raw_values": [
21.03018178097099877277287305332720279693603515625
],
"min_result": [
"15.23"
],
"max_result": [
"21.8"
],
"test_run_times": [
102.340000000000003410605131648480892181396484375
]
}
}
},
"e53ed50df6ab47811484cbc3c159c79dc2966b78": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 64 resnet50",
"description": "Device: CPU - Batch Size: 64 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 21.589999999999999857891452847979962825775146484375,
"raw_values": [
21.5948884857699994199720094911754131317138671875
],
"min_result": [
"14.02"
],
"max_result": [
"22.21"
],
"test_run_times": [
101.8900000000000005684341886080801486968994140625
]
},
"a": {
"value": 21.0799999999999982946974341757595539093017578125,
"raw_values": [
21.515379582657001122925066738389432430267333984375,
20.955585213180000891952659003436565399169921875,
20.754626919237001203555337269790470600128173828125
],
"min_result": [
"13.2"
],
"max_result": [
"22.07"
],
"test_run_times": [
101.3599999999999994315658113919198513031005859375,
101.780000000000001136868377216160297393798828125,
103.150000000000005684341886080801486968994140625
]
},
"b": {
"value": 20.89999999999999857891452847979962825775146484375,
"raw_values": [
20.895529516376999623616939061321318149566650390625
],
"min_result": [
"13.13"
],
"max_result": [
"21.57"
],
"test_run_times": [
102.7699999999999960209606797434389591217041015625
]
}
}
},
"75c834417bf0059ea75b1d19b03766a190e2dc13": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 16 resnet152",
"description": "Device: CPU - Batch Size: 16 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 8.92999999999999971578290569595992565155029296875,
"raw_values": [
8.9336238000036995998698330367915332317352294921875
],
"min_result": [
"8.8"
],
"max_result": [
"9.04"
],
"test_run_times": [
235.509999999999990905052982270717620849609375
]
},
"a": {
"value": 9.0099999999999997868371792719699442386627197265625,
"raw_values": [
9.084186920374900608976531657390296459197998046875,
8.8242664155581991280996589921414852142333984375,
9.116947862909700717182204243727028369903564453125
],
"min_result": [
"4.81"
],
"max_result": [
"9.31"
],
"test_run_times": [
229.3899999999999863575794734060764312744140625,
233.1100000000000136424205265939235687255859375,
228.93000000000000682121026329696178436279296875
]
},
"b": {
"value": 9.1199999999999992184029906638897955417633056640625,
"raw_values": [
9.1156011246623993571347455144859850406646728515625
],
"min_result": [
"8.99"
],
"max_result": [
"9.29"
],
"test_run_times": [
229.729999999999989768184605054557323455810546875
]
}
}
},
"c0ebee3de3af3f6bb30ca7bfd912294570db05fa": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 256 resnet50",
"description": "Device: CPU - Batch Size: 256 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 21.199999999999999289457264239899814128875732421875,
"raw_values": [
21.20420927439300129435650887899100780487060546875
],
"min_result": [
"12.68"
],
"max_result": [
"21.88"
],
"test_run_times": [
102.349999999999994315658113919198513031005859375
]
},
"a": {
"value": 20.769999999999999573674358543939888477325439453125,
"raw_values": [
20.688097501323998272937387810088694095611572265625,
20.6384956900050013928193948231637477874755859375,
20.972423122902998926520012901164591312408447265625
],
"min_result": [
"12.97"
],
"max_result": [
"21.67"
],
"test_run_times": [
104.2099999999999937472239253111183643341064453125,
107.1400000000000005684341886080801486968994140625,
102.81999999999999317878973670303821563720703125
]
},
"b": {
"value": 20.85000000000000142108547152020037174224853515625,
"raw_values": [
20.851915897426000157111047883518040180206298828125
],
"min_result": [
"12.74"
],
"max_result": [
"21.39"
],
"test_run_times": [
103.7300000000000039790393202565610408782958984375
]
}
}
},
"56fa1ea70f6128a460fab8eadbc9d03e19a68f1f": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 32 resnet152",
"description": "Device: CPU - Batch Size: 32 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 8.7200000000000006394884621840901672840118408203125,
"raw_values": [
8.7152500190029993376583661301992833614349365234375
],
"min_result": [
"5.23"
],
"max_result": [
"9.06"
],
"test_run_times": [
240.68000000000000682121026329696178436279296875
]
},
"a": {
"value": 9.339999999999999857891452847979962825775146484375,
"raw_values": [
9.4869859545816996870826187659986317157745361328125,
9.1984085482283006740544806234538555145263671875,
9.32417611414459912566599086858332157135009765625
],
"min_result": [
"4.74"
],
"max_result": [
"9.74"
],
"test_run_times": [
225.1200000000000045474735088646411895751953125,
227.490000000000009094947017729282379150390625,
224.6299999999999954525264911353588104248046875
]
},
"b": {
"value": 9.2799999999999993605115378159098327159881591796875,
"raw_values": [
9.279335549872399724335991777479648590087890625
],
"min_result": [
"5.31"
],
"max_result": [
"9.48"
],
"test_run_times": [
227.900000000000005684341886080801486968994140625
]
}
}
},
"0d499a4b318c513750ceefe20d7b87453d9d336f": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 512 resnet50",
"description": "Device: CPU - Batch Size: 512 - Model: ResNet-50",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 20.42999999999999971578290569595992565155029296875,
"raw_values": [
20.42960690880600083119134069420397281646728515625
],
"min_result": [
"13.46"
],
"max_result": [
"21.1"
],
"test_run_times": [
105.75
]
},
"a": {
"value": 21.010000000000001563194018672220408916473388671875,
"raw_values": [
21.123891140209000383265447453595697879791259765625,
20.391155342065001576656868564896285533905029296875,
21.96985136597700005722799687646329402923583984375,
20.75327137539699862145425868220627307891845703125,
20.77591713861900046822484000585973262786865234375,
19.867405052597998604824169888161122798919677734375,
21.18365127559000171686420799233019351959228515625,
20.70056736755800130822535720653831958770751953125,
21.106392186714998615570948459208011627197265625,
21.109527299324998494967076112516224384307861328125,
21.518009971028998705833146232180297374725341796875,
21.673105642612998877893915050663053989410400390625,
21.22601434054499947023941786028444766998291015625,
21.31161365502899940338465967215597629547119140625,
20.408827949026001391530371620319783687591552734375
],
"min_result": [
"11.92"
],
"max_result": [
"22.65"
],
"test_run_times": [
102.2900000000000062527760746888816356658935546875,
105.8299999999999982946974341757595539093017578125,
99.659999999999996589394868351519107818603515625,
103.68000000000000682121026329696178436279296875,
103.3799999999999954525264911353588104248046875,
109.5799999999999982946974341757595539093017578125,
102.530000000000001136868377216160297393798828125,
104.159999999999996589394868351519107818603515625,
101.81000000000000227373675443232059478759765625,
102.849999999999994315658113919198513031005859375,
102,
100.340000000000003410605131648480892181396484375,
102.159999999999996589394868351519107818603515625,
103.099999999999994315658113919198513031005859375,
105.6400000000000005684341886080801486968994140625
]
},
"b": {
"value": 21.010000000000001563194018672220408916473388671875,
"raw_values": [
21.0125790999179997697865474037826061248779296875
],
"min_result": [
"14.13"
],
"max_result": [
"21.43"
],
"test_run_times": [
104.1400000000000005684341886080801486968994140625
]
}
}
},
"16296c993bdfa97a6848d705ddcb761a04402680": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 64 resnet152",
"description": "Device: CPU - Batch Size: 64 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 9.21000000000000085265128291212022304534912109375,
"raw_values": [
9.205423636420700717053478001616895198822021484375
],
"min_result": [
"4.8"
],
"max_result": [
"9.43"
],
"test_run_times": [
227.759999999999990905052982270717620849609375
]
},
"a": {
"value": 8.910000000000000142108547152020037174224853515625,
"raw_values": [
8.8158007348403994996033361530862748622894287109375,
9.122936103276099828462974983267486095428466796875,
9.38485019793269970023175119422376155853271484375,
8.596137299316300328655415796674787998199462890625,
8.62740281868079961213879869319498538970947265625,
9.5029001173169991290023972396738827228546142578125,
8.54877727447099999835700145922601222991943359375,
9.083516130316699133118163445033133029937744140625,
8.615061961050599848022102378308773040771484375,
9.052277495767800274961700779385864734649658203125,
8.7745805522166993029031800688244402408599853515625,
8.7409772446490006103658743086270987987518310546875
],
"min_result": [
"4.5"
],
"max_result": [
"9.7"
],
"test_run_times": [
239.740000000000009094947017729282379150390625,
230.460000000000007958078640513122081756591796875,
225.5,
246.349999999999994315658113919198513031005859375,
243.020000000000010231815394945442676544189453125,
228.3799999999999954525264911353588104248046875,
241.6100000000000136424205265939235687255859375,
227.990000000000009094947017729282379150390625,
243.759999999999990905052982270717620849609375,
230.229999999999989768184605054557323455810546875,
237.18000000000000682121026329696178436279296875,
239.789999999999992041921359486877918243408203125
]
},
"b": {
"value": 8.78999999999999914734871708787977695465087890625,
"raw_values": [
8.794520276849400630680975154973566532135009765625
],
"min_result": [
"4.6"
],
"max_result": [
"8.97"
],
"test_run_times": [
237.6299999999999954525264911353588104248046875
]
}
}
},
"e3737a48218cdf9ba397f2538c1ec5ba8ba6bf81": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 256 resnet152",
"description": "Device: CPU - Batch Size: 256 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 8.9199999999999999289457264239899814128875732421875,
"raw_values": [
8.9173247997935991548956735641695559024810791015625
],
"min_result": [
"5.04"
],
"max_result": [
"9.16"
],
"test_run_times": [
233.289999999999992041921359486877918243408203125
]
},
"a": {
"value": 9.089999999999999857891452847979962825775146484375,
"raw_values": [
8.5810206912180007066126563586294651031494140625,
9.2792485351829991913064077380113303661346435546875,
8.6564652394964003434552068938501179218292236328125,
8.8566080789117993532499895081855356693267822265625,
9.64874340720979972729764995165169239044189453125,
9.096724292717400572882979759015142917633056640625,
9.480007971201199978850127081386744976043701171875,
9.0767686746749998150107785477302968502044677734375,
9.5665820710665006032513701939024031162261962890625,
8.7336428375786994138252339325845241546630859375,
9.0102379005197992256626093876548111438751220703125,
9.0540224020670994065085324109531939029693603515625
],
"min_result": [
"4.84"
],
"max_result": [
"10.03"
],
"test_run_times": [
241.6100000000000136424205265939235687255859375,
224.30000000000001136868377216160297393798828125,
242.270000000000010231815394945442676544189453125,
232.909999999999996589394868351519107818603515625,
216.530000000000001136868377216160297393798828125,
228.219999999999998863131622783839702606201171875,
221.56000000000000227373675443232059478759765625,
232.909999999999996589394868351519107818603515625,
220.020000000000010231815394945442676544189453125,
237.8600000000000136424205265939235687255859375,
235.1200000000000045474735088646411895751953125,
229.669999999999987494447850622236728668212890625
]
},
"b": {
"value": 8.8499999999999996447286321199499070644378662109375,
"raw_values": [
8.8538824033850005434942431747913360595703125
],
"min_result": [
"5.25"
],
"max_result": [
"9.05"
],
"test_run_times": [
238.8899999999999863575794734060764312744140625
]
}
}
},
"1e1b7ee4b6d0a9be046b48132617a756ba63cb19": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 512 resnet152",
"description": "Device: CPU - Batch Size: 512 - Model: ResNet-152",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 9.4700000000000006394884621840901672840118408203125,
"raw_values": [
9.474132699527100243130917078815400600433349609375
],
"min_result": [
"5.17"
],
"max_result": [
"9.87"
],
"test_run_times": [
223.06000000000000227373675443232059478759765625
]
},
"a": {
"value": 9.3300000000000000710542735760100185871124267578125,
"raw_values": [
9.51541919676260050664495793171226978302001953125,
9.1856535212848005045316313044168055057525634765625,
9.2805177426980005606083068414591252803802490234375
],
"min_result": [
"4.69"
],
"max_result": [
"9.66"
],
"test_run_times": [
221.68999999999999772626324556767940521240234375,
230.080000000000012505552149377763271331787109375,
223.18000000000000682121026329696178436279296875
]
},
"b": {
"value": 8.8100000000000004973799150320701301097869873046875,
"raw_values": [
8.8065388989351003345973367686383426189422607421875
],
"min_result": [
"4.87"
],
"max_result": [
"8.97"
],
"test_run_times": [
238.780000000000001136868377216160297393798828125
]
}
}
},
"91f57edf4d0566d1c42799517ef9c6f11b556d59": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 1 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 6.29000000000000003552713678800500929355621337890625,
"raw_values": [
6.288960738030500152717650053091347217559814453125
],
"min_result": [
"3.09"
],
"max_result": [
"6.44"
],
"test_run_times": [
180.900000000000005684341886080801486968994140625
]
},
"a": {
"value": 6.45000000000000017763568394002504646778106689453125,
"raw_values": [
6.2833664845030998691299828351475298404693603515625,
6.51553048048099991973458600114099681377410888671875,
6.5644180000247001061097762431018054485321044921875
],
"min_result": [
"3.05"
],
"max_result": [
"6.85"
],
"test_run_times": [
181.56999999999999317878973670303821563720703125,
175.099999999999994315658113919198513031005859375,
174.6299999999999954525264911353588104248046875
]
},
"b": {
"value": 6.5,
"raw_values": [
6.50419645107589960986160804168321192264556884765625
],
"min_result": [
"3.35"
],
"max_result": [
"6.62"
],
"test_run_times": [
175.340000000000003410605131648480892181396484375
]
}
}
},
"11aa33c4a0cf33904eaf5622d1a19d243b999579": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 16 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 2.3300000000000000710542735760100185871124267578125,
"raw_values": [
2.328163331307199879205427350825630128383636474609375
],
"min_result": [
"1.76"
],
"max_result": [
"2.72"
],
"test_run_times": [
655.0900000000000318323145620524883270263671875
]
},
"a": {
"value": 2.3300000000000000710542735760100185871124267578125,
"raw_values": [
2.34370940420769979795068138628266751766204833984375,
2.3503592655721998738727052113972604274749755859375,
2.310222220681399818431600579060614109039306640625
],
"min_result": [
"1.77"
],
"max_result": [
"2.9"
],
"test_run_times": [
651.6200000000000045474735088646411895751953125,
650.6200000000000045474735088646411895751953125,
658.779999999999972715158946812152862548828125
]
},
"b": {
"value": 2.350000000000000088817841970012523233890533447265625,
"raw_values": [
2.349166152438999954910059386747889220714569091796875
],
"min_result": [
"1.82"
],
"max_result": [
"2.76"
],
"test_run_times": [
645.5900000000000318323145620524883270263671875
]
}
}
},
"06c69cec0fca59101a0c4df029f8fd067643dd03": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 32 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 2.3300000000000000710542735760100185871124267578125,
"raw_values": [
2.32964945169269999070138510433025658130645751953125
],
"min_result": [
"1.78"
],
"max_result": [
"2.8"
],
"test_run_times": [
645.4099999999999681676854379475116729736328125
]
},
"a": {
"value": 2.310000000000000053290705182007513940334320068359375,
"raw_values": [
2.29853201184879996077370378770865499973297119140625,
2.31885343255089981795435960520990192890167236328125,
2.323894807046400057259916138718836009502410888671875
],
"min_result": [
"1.88"
],
"max_result": [
"2.74"
],
"test_run_times": [
659.23000000000001818989403545856475830078125,
657,
655.759999999999990905052982270717620849609375
]
},
"b": {
"value": 2.319999999999999840127884453977458178997039794921875,
"raw_values": [
2.317597769168500132508370370487682521343231201171875
],
"min_result": [
"1.94"
],
"max_result": [
"2.8"
],
"test_run_times": [
660.76999999999998181010596454143524169921875
]
}
}
},
"e471e6d59124e53e1c89d2df76ee3bd8192bf205": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 64 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 2.319999999999999840127884453977458178997039794921875,
"raw_values": [
2.3237855498783002161644617444835603237152099609375
],
"min_result": [
"1.9"
],
"max_result": [
"2.75"
],
"test_run_times": [
651.8799999999999954525264911353588104248046875
]
},
"a": {
"value": 2.310000000000000053290705182007513940334320068359375,
"raw_values": [
2.321464440572800214113158290274441242218017578125,
2.29761592284040006006762268953025341033935546875,
2.32231474914020008526449601049534976482391357421875
],
"min_result": [
"1.53"
],
"max_result": [
"2.83"
],
"test_run_times": [
652.779999999999972715158946812152862548828125,
657,
656
]
},
"b": {
"value": 2.3300000000000000710542735760100185871124267578125,
"raw_values": [
2.33152809955609985337332545896060764789581298828125
],
"min_result": [
"1.78"
],
"max_result": [
"2.77"
],
"test_run_times": [
659.6000000000000227373675443232059478759765625
]
}
}
},
"4cac0e56d23e0dfbd71412a15e30666ef513d10f": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 256 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 2.29000000000000003552713678800500929355621337890625,
"raw_values": [
2.287136724613299865183080328279174864292144775390625
],
"min_result": [
"1.79"
],
"max_result": [
"2.72"
],
"test_run_times": [
661.9299999999999499777914024889469146728515625
]
},
"a": {
"value": 2.3300000000000000710542735760100185871124267578125,
"raw_values": [
2.311358325174400096813087657210417091846466064453125,
2.340489849675300160214419520343653857707977294921875,
2.332287579603899985158932395279407501220703125
],
"min_result": [
"1.59"
],
"max_result": [
"2.78"
],
"test_run_times": [
655.6499999999999772626324556767940521240234375,
655.26999999999998181010596454143524169921875,
651.1799999999999499777914024889469146728515625
]
},
"b": {
"value": 2.310000000000000053290705182007513940334320068359375,
"raw_values": [
2.308380447636400045752225196338258683681488037109375
],
"min_result": [
"1.92"
],
"max_result": [
"2.67"
],
"test_run_times": [
657.509999999999990905052982270717620849609375
]
}
}
},
"6a4e9ff171c98091c4eac6a3be870c63a4c07d1b": {
"identifier": "pts\/pytorch-1.1.0",
"title": "PyTorch",
"app_version": "2.2.1",
"arguments": "cpu 512 efficientnet_v2_l",
"description": "Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l",
"scale": "batches\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 2.310000000000000053290705182007513940334320068359375,
"raw_values": [
2.3108555774630001877767426776699721813201904296875
],
"min_result": [
"1.7"
],
"max_result": [
"2.84"
],
"test_run_times": [
654.2899999999999636202119290828704833984375
]
},
"a": {
"value": 2.3300000000000000710542735760100185871124267578125,
"raw_values": [
2.345086109491699932760866431635804474353790283203125,
2.300391387487299876823954036808572709560394287109375,
2.33767639091310019949787601944990456104278564453125
],
"min_result": [
"1.58"
],
"max_result": [
"2.83"
],
"test_run_times": [
653.779999999999972715158946812152862548828125,
651.69000000000005456968210637569427490234375,
655.1000000000000227373675443232059478759765625
]
},
"b": {
"value": 2.319999999999999840127884453977458178997039794921875,
"raw_values": [
2.32359701943070007246205932460725307464599609375
],
"min_result": [
"1.79"
],
"max_result": [
"2.71"
],
"test_run_times": [
651.0399999999999636202119290828704833984375
]
}
}
},
"402d48a955b9ec8faf2263d0617ed5f693c5868f": {
"identifier": "pts\/rocksdb-1.6.0",
"title": "RocksDB",
"app_version": "9.0",
"arguments": "--benchmarks=\"overwrite\"",
"description": "Test: Overwrite",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 421049,
"test_run_times": [
60.35000000000000142108547152020037174224853515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"a": {
"value": 421616,
"test_run_times": [
60.28999999999999914734871708787977695465087890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 439602,
"test_run_times": [
60.46000000000000085265128291212022304534912109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"5574a9adcdcc43772f1310c523e9d41f60bd81bb": {
"identifier": "pts\/rocksdb-1.6.0",
"title": "RocksDB",
"app_version": "9.0",
"arguments": "--benchmarks=\"readrandom\"",
"description": "Test: Random Read",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 1105306233,
"test_run_times": [
60.07000000000000028421709430404007434844970703125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"a": {
"value": 1108892776,
"test_run_times": [
60.07000000000000028421709430404007434844970703125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 1108469308,
"test_run_times": [
60.07000000000000028421709430404007434844970703125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"a5a9147abb170b17ed93e595ff3e61bcb669d5e7": {
"identifier": "pts\/rocksdb-1.6.0",
"title": "RocksDB",
"app_version": "9.0",
"arguments": "--benchmarks=\"updaterandom\"",
"description": "Test: Update Random",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 421266,
"test_run_times": [
60.2999999999999971578290569595992565155029296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"a": {
"value": 425687,
"test_run_times": [
60.590000000000003410605131648480892181396484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 427391,
"test_run_times": [
60.340000000000003410605131648480892181396484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"375d56ea79544634b2c79f2912a7d11db375dc2a": {
"identifier": "pts\/rocksdb-1.6.0",
"title": "RocksDB",
"app_version": "9.0",
"arguments": "--benchmarks=\"readwhilewriting\"",
"description": "Test: Read While Writing",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 27130363,
"test_run_times": [
60.17999999999999971578290569595992565155029296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"a": {
"value": 26406662,
"test_run_times": [
60.18999999999999772626324556767940521240234375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 26135567,
"test_run_times": [
60.17999999999999971578290569595992565155029296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"661a5b046c1aea421c67c3eea81e7b7418e850d7": {
"identifier": "pts\/rocksdb-1.6.0",
"title": "RocksDB",
"app_version": "9.0",
"arguments": "--benchmarks=\"readrandomwriterandom\"",
"description": "Test: Read Random Write Random",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 3619142,
"test_run_times": [
60.2999999999999971578290569595992565155029296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"a": {
"value": 3643263,
"test_run_times": [
60.2999999999999971578290569595992565155029296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 3638929,
"test_run_times": [
60.2999999999999971578290569595992565155029296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"4aa2a8dc9d9beef6165ea03da7a36fbc2fc7b3af": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=1 --model=alexnet",
"description": "Device: CPU - Batch Size: 1 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 21.160000000000000142108547152020037174224853515625,
"test_run_times": [
7.160000000000000142108547152020037174224853515625
]
},
"a": {
"value": 20.780000000000001136868377216160297393798828125,
"raw_values": [
21.60000000000000142108547152020037174224853515625,
20.440000000000001278976924368180334568023681640625,
19.530000000000001136868377216160297393798828125,
20.8299999999999982946974341757595539093017578125,
21.120000000000000994759830064140260219573974609375,
21.559999999999998721023075631819665431976318359375,
20.78999999999999914734871708787977695465087890625,
19.949999999999999289457264239899814128875732421875,
20.25,
21.449999999999999289457264239899814128875732421875,
21.17999999999999971578290569595992565155029296875,
20.46000000000000085265128291212022304534912109375,
21.339999999999999857891452847979962825775146484375,
20.28999999999999914734871708787977695465087890625,
20.89999999999999857891452847979962825775146484375
],
"test_run_times": [
7.0099999999999997868371792719699442386627197265625,
7.28000000000000024868995751603506505489349365234375,
7.45999999999999996447286321199499070644378662109375,
7.1699999999999999289457264239899814128875732421875,
7.12999999999999989341858963598497211933135986328125,
7.0099999999999997868371792719699442386627197265625,
7.17999999999999971578290569595992565155029296875,
7.4000000000000003552713678800500929355621337890625,
7.30999999999999960920149533194489777088165283203125,
7.03000000000000024868995751603506505489349365234375,
7.12999999999999989341858963598497211933135986328125,
7.29999999999999982236431605997495353221893310546875,
7.0800000000000000710542735760100185871124267578125,
7.29000000000000003552713678800500929355621337890625,
7.19000000000000039079850466805510222911834716796875
]
},
"b": {
"value": 21.010000000000001563194018672220408916473388671875,
"test_run_times": [
7.0999999999999996447286321199499070644378662109375
]
}
}
},
"08449982a4f5f924d45208f47b9d8c62067b2e23": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=16 --model=alexnet",
"description": "Device: CPU - Batch Size: 16 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 242.289999999999992041921359486877918243408203125,
"test_run_times": [
9.17999999999999971578290569595992565155029296875
]
},
"a": {
"value": 247.55000000000001136868377216160297393798828125,
"raw_values": [
238.659999999999996589394868351519107818603515625,
254.979999999999989768184605054557323455810546875,
256.3799999999999954525264911353588104248046875,
229.93000000000000682121026329696178436279296875,
240.969999999999998863131622783839702606201171875,
249.289999999999992041921359486877918243408203125,
251,
245.1100000000000136424205265939235687255859375,
258.220000000000027284841053187847137451171875,
238.8799999999999954525264911353588104248046875,
249.330000000000012505552149377763271331787109375,
254.68000000000000682121026329696178436279296875,
256.18999999999999772626324556767940521240234375,
235.18000000000000682121026329696178436279296875,
254.520000000000010231815394945442676544189453125
],
"test_run_times": [
9.3699999999999992184029906638897955417633056640625,
8.910000000000000142108547152020037174224853515625,
8.839999999999999857891452847979962825775146484375,
9.6199999999999992184029906638897955417633056640625,
9.28999999999999914734871708787977695465087890625,
9.019999999999999573674358543939888477325439453125,
9.019999999999999573674358543939888477325439453125,
9.1400000000000005684341886080801486968994140625,
8.839999999999999857891452847979962825775146484375,
9.32000000000000028421709430404007434844970703125,
9.050000000000000710542735760100185871124267578125,
8.9000000000000003552713678800500929355621337890625,
8.8800000000000007815970093361102044582366943359375,
9.3900000000000005684341886080801486968994140625,
8.8900000000000005684341886080801486968994140625
]
},
"b": {
"value": 236.56000000000000227373675443232059478759765625,
"test_run_times": [
9.42999999999999971578290569595992565155029296875
]
}
}
},
"4042d31bc5aa3c11c217e669c15bfcdfecd2af39": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=32 --model=alexnet",
"description": "Device: CPU - Batch Size: 32 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 424.06000000000000227373675443232059478759765625,
"test_run_times": [
10.3300000000000000710542735760100185871124267578125
]
},
"a": {
"value": 436.25,
"raw_values": [
404.490000000000009094947017729282379150390625,
451.76999999999998181010596454143524169921875,
463,
455.41000000000002501110429875552654266357421875,
462.43999999999999772626324556767940521240234375,
402.31000000000000227373675443232059478759765625,
447.76999999999998181010596454143524169921875,
465.3700000000000045474735088646411895751953125,
415.279999999999972715158946812152862548828125,
425.970000000000027284841053187847137451171875,
460.970000000000027284841053187847137451171875,
460.42000000000001591615728102624416351318359375,
420.56999999999999317878973670303821563720703125,
403.3600000000000136424205265939235687255859375,
404.66000000000002501110429875552654266357421875
],
"test_run_times": [
10.7799999999999993605115378159098327159881591796875,
9.9900000000000002131628207280300557613372802734375,
9.699999999999999289457264239899814128875732421875,
9.8499999999999996447286321199499070644378662109375,
9.8699999999999992184029906638897955417633056640625,
10.8100000000000004973799150320701301097869873046875,
10.1099999999999994315658113919198513031005859375,
9.6699999999999999289457264239899814128875732421875,
10.4900000000000002131628207280300557613372802734375,
10.28999999999999914734871708787977695465087890625,
9.769999999999999573674358543939888477325439453125,
9.8900000000000005684341886080801486968994140625,
10.4000000000000003552713678800500929355621337890625,
10.7599999999999997868371792719699442386627197265625,
10.7599999999999997868371792719699442386627197265625
]
},
"b": {
"value": 461.6000000000000227373675443232059478759765625,
"test_run_times": [
9.75
]
}
}
},
"cc9e31e984b8806636e79ff6e5e21c1a6f766e29": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=64 --model=alexnet",
"description": "Device: CPU - Batch Size: 64 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 765.549999999999954525264911353588104248046875,
"test_run_times": [
11.3900000000000005684341886080801486968994140625
]
},
"a": {
"value": 749.4600000000000363797880709171295166015625,
"raw_values": [
780.6000000000000227373675443232059478759765625,
721.6799999999999499777914024889469146728515625,
756.0900000000000318323145620524883270263671875,
765.1699999999999590727384202182292938232421875,
726.98000000000001818989403545856475830078125,
723.6299999999999954525264911353588104248046875,
740.4600000000000363797880709171295166015625,
736.8400000000000318323145620524883270263671875,
760.1100000000000136424205265939235687255859375,
766.450000000000045474735088646411895751953125,
758.3500000000000227373675443232059478759765625,
755.1499999999999772626324556767940521240234375,
775.990000000000009094947017729282379150390625,
713.4199999999999590727384202182292938232421875,
760.94000000000005456968210637569427490234375
],
"test_run_times": [
11.199999999999999289457264239899814128875732421875,
11.8900000000000005684341886080801486968994140625,
11.5,
11.3800000000000007815970093361102044582366943359375,
11.8800000000000007815970093361102044582366943359375,
11.8900000000000005684341886080801486968994140625,
11.7200000000000006394884621840901672840118408203125,
11.6899999999999995026200849679298698902130126953125,
11.449999999999999289457264239899814128875732421875,
11.3900000000000005684341886080801486968994140625,
11.4700000000000006394884621840901672840118408203125,
11.519999999999999573674358543939888477325439453125,
11.25,
11.980000000000000426325641456060111522674560546875,
11.449999999999999289457264239899814128875732421875
]
},
"b": {
"value": 743.5,
"test_run_times": [
11.6199999999999992184029906638897955417633056640625
]
}
}
},
"efd4132b4ca34777b8be0494c36cc1edae74ee0d": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=1 --model=googlenet",
"description": "Device: CPU - Batch Size: 1 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 12.5800000000000000710542735760100185871124267578125,
"test_run_times": [
11.96000000000000085265128291212022304534912109375
]
},
"a": {
"value": 13.199999999999999289457264239899814128875732421875,
"raw_values": [
13.6099999999999994315658113919198513031005859375,
12.769999999999999573674358543939888477325439453125,
13.8300000000000000710542735760100185871124267578125,
12.8300000000000000710542735760100185871124267578125,
13.46000000000000085265128291212022304534912109375,
12.6099999999999994315658113919198513031005859375,
13.199999999999999289457264239899814128875732421875,
13.9900000000000002131628207280300557613372802734375,
12.6199999999999992184029906638897955417633056640625,
13.3599999999999994315658113919198513031005859375,
12.449999999999999289457264239899814128875732421875,
13.32000000000000028421709430404007434844970703125,
12.519999999999999573674358543939888477325439453125,
13.839999999999999857891452847979962825775146484375,
13.5600000000000004973799150320701301097869873046875
],
"test_run_times": [
11.25,
11.9399999999999995026200849679298698902130126953125,
11.0800000000000000710542735760100185871124267578125,
11.769999999999999573674358543939888477325439453125,
11.3699999999999992184029906638897955417633056640625,
12.0999999999999996447286321199499070644378662109375,
11.4700000000000006394884621840901672840118408203125,
10.9900000000000002131628207280300557613372802734375,
11.9000000000000003552713678800500929355621337890625,
11.4399999999999995026200849679298698902130126953125,
12.050000000000000710542735760100185871124267578125,
11.449999999999999289457264239899814128875732421875,
11.980000000000000426325641456060111522674560546875,
11.1199999999999992184029906638897955417633056640625,
11.3499999999999996447286321199499070644378662109375
]
},
"b": {
"value": 13.519999999999999573674358543939888477325439453125,
"test_run_times": [
11.3699999999999992184029906638897955417633056640625
]
}
}
},
"1eff874d2ed99fbec15252604d5788236f12724f": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=1 --model=resnet50",
"description": "Device: CPU - Batch Size: 1 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 4.04999999999999982236431605997495353221893310546875,
"test_run_times": [
31
]
},
"a": {
"value": 3.899999999999999911182158029987476766109466552734375,
"test_run_times": [
38.13000000000000255795384873636066913604736328125
]
},
"b": {
"value": 4.0099999999999997868371792719699442386627197265625,
"test_run_times": [
31.280000000000001136868377216160297393798828125
]
}
}
},
"3fc0ca1d5a0746bef2ec915696cd1e7e450f0486": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=256 --model=alexnet",
"description": "Device: CPU - Batch Size: 256 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 1652.23000000000001818989403545856475830078125,
"test_run_times": [
19.300000000000000710542735760100185871124267578125
]
},
"a": {
"value": 1604.51999999999998181010596454143524169921875,
"test_run_times": [
19.82000000000000028421709430404007434844970703125
]
},
"b": {
"value": 1656.7899999999999636202119290828704833984375,
"test_run_times": [
19.3599999999999994315658113919198513031005859375
]
}
}
},
"5c98d60e307e91e3fa4a166cb951aedf30820571": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=512 --model=alexnet",
"description": "Device: CPU - Batch Size: 512 - Model: AlexNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 1980.509999999999990905052982270717620849609375,
"test_run_times": [
30.879999999999999005240169935859739780426025390625
]
},
"a": {
"value": 2010.55999999999994543031789362430572509765625,
"test_run_times": [
30.53999999999999914734871708787977695465087890625
]
},
"b": {
"value": 2010.59999999999990905052982270717620849609375,
"test_run_times": [
30.519999999999999573674358543939888477325439453125
]
}
}
},
"0c7ca7413dad7058da6c1b7ecf451e37c79a852f": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=16 --model=googlenet",
"description": "Device: CPU - Batch Size: 16 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 112.6400000000000005684341886080801486968994140625,
"test_run_times": [
19.219999999999998863131622783839702606201171875
]
},
"a": {
"value": 114.2600000000000051159076974727213382720947265625,
"test_run_times": [
18.92999999999999971578290569595992565155029296875
]
},
"b": {
"value": 119.219999999999998863131622783839702606201171875,
"test_run_times": [
18.28999999999999914734871708787977695465087890625
]
}
}
},
"113aa8ffcc7b9a5e5921242a3c219cbcf10a56c1": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=16 --model=resnet50",
"description": "Device: CPU - Batch Size: 16 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 39.67999999999999971578290569595992565155029296875,
"test_run_times": [
48.78999999999999914734871708787977695465087890625
]
},
"a": {
"value": 41.25999999999999801048033987171947956085205078125,
"test_run_times": [
47.25
]
},
"b": {
"value": 35.9200000000000017053025658242404460906982421875,
"test_run_times": [
53.39999999999999857891452847979962825775146484375
]
}
}
},
"fbe5c59152314e76bd9f9138ab14c06003fca508": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=32 --model=googlenet",
"description": "Device: CPU - Batch Size: 32 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 185.159999999999996589394868351519107818603515625,
"test_run_times": [
22.67999999999999971578290569595992565155029296875
]
},
"a": {
"value": 176.3600000000000136424205265939235687255859375,
"test_run_times": [
23.719999999999998863131622783839702606201171875
]
},
"b": {
"value": 190.740000000000009094947017729282379150390625,
"test_run_times": [
22.17999999999999971578290569595992565155029296875
]
}
}
},
"553578ea95c8cd321f02803aae717264cb615497": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=32 --model=resnet50",
"description": "Device: CPU - Batch Size: 32 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 65.8799999999999954525264911353588104248046875,
"test_run_times": [
64.219999999999998863131622783839702606201171875
]
},
"a": {
"value": 60.25,
"test_run_times": [
63.14999999999999857891452847979962825775146484375
]
},
"b": {
"value": 66.68000000000000682121026329696178436279296875,
"test_run_times": [
57.50999999999999801048033987171947956085205078125
]
}
}
},
"756b849822aa6cfd1f7ea7544eee95ad83059012": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=64 --model=googlenet",
"description": "Device: CPU - Batch Size: 64 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 275.33999999999997498889570124447345733642578125,
"test_run_times": [
29.57000000000000028421709430404007434844970703125
]
},
"a": {
"value": 273.68000000000000682121026329696178436279296875,
"test_run_times": [
29.71000000000000085265128291212022304534912109375
]
},
"b": {
"value": 256.8700000000000045474735088646411895751953125,
"test_run_times": [
31.339999999999999857891452847979962825775146484375
]
}
}
},
"c2b4c32d69dc5fddfa4829c640df8922cbe2fa37": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=64 --model=resnet50",
"description": "Device: CPU - Batch Size: 64 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 87.719999999999998863131622783839702606201171875,
"test_run_times": [
85.469999999999998863131622783839702606201171875
]
},
"a": {
"value": 88.93000000000000682121026329696178436279296875,
"test_run_times": [
84.5100000000000051159076974727213382720947265625
]
},
"b": {
"value": 88.9500000000000028421709430404007434844970703125,
"test_run_times": [
84.43000000000000682121026329696178436279296875
]
}
}
},
"f45c09499237f1715f224cec3778b8e2b561e26b": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=256 --model=googlenet",
"description": "Device: CPU - Batch Size: 256 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 400.029999999999972715158946812152862548828125,
"test_run_times": [
75.1700000000000017053025658242404460906982421875
]
},
"a": {
"value": 399.45999999999997953636921010911464691162109375,
"test_run_times": [
75.280000000000001136868377216160297393798828125
]
},
"b": {
"value": 400.6100000000000136424205265939235687255859375,
"test_run_times": [
74.969999999999998863131622783839702606201171875
]
}
}
},
"c79954d082be150cefddf4af1ec61f414286b450": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=256 --model=resnet50",
"description": "Device: CPU - Batch Size: 256 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 119.8299999999999982946974341757595539093017578125,
"test_run_times": [
242.090000000000003410605131648480892181396484375
]
},
"a": {
"value": 118.8799999999999954525264911353588104248046875,
"test_run_times": [
243.93000000000000682121026329696178436279296875
]
},
"b": {
"value": 118.7699999999999960209606797434389591217041015625,
"test_run_times": [
244.280000000000001136868377216160297393798828125
]
}
}
},
"5271aa1559827b988959a00c9654f9dec12c83dd": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=512 --model=googlenet",
"description": "Device: CPU - Batch Size: 512 - Model: GoogLeNet",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 493.31000000000000227373675443232059478759765625,
"test_run_times": [
119.5499999999999971578290569595992565155029296875
]
},
"a": {
"value": 484.01999999999998181010596454143524169921875,
"test_run_times": [
121.659999999999996589394868351519107818603515625
]
},
"b": {
"value": 494.45999999999997953636921010911464691162109375,
"test_run_times": [
119.31999999999999317878973670303821563720703125
]
}
}
},
"b24071a13173fed1d53bd54c5c89d56a1073ff7d": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=512 --model=resnet50",
"description": "Device: CPU - Batch Size: 512 - Model: ResNet-50",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 140.590000000000003410605131648480892181396484375,
"test_run_times": [
409.75
]
},
"a": {
"value": 140.490000000000009094947017729282379150390625,
"test_run_times": [
410.01999999999998181010596454143524169921875
]
},
"b": {
"value": 141.159999999999996589394868351519107818603515625,
"test_run_times": [
408.43000000000000682121026329696178436279296875
]
}
}
},
"c3b5387998e4006084a331673013309ebc420552": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=1 --model=vgg16",
"description": "Device: CPU - Batch Size: 1 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"b": {
"value": 9.3900000000000005684341886080801486968994140625,
"test_run_times": [
13.9900000000000002131628207280300557613372802734375
]
}
}
},
"29ad2dd362dad2842eaa589bcb10d92457d4742b": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=16 --model=vgg16",
"description": "Device: CPU - Batch Size: 16 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"b": {
"value": 60.68999999999999772626324556767940521240234375,
"test_run_times": [
32.159999999999996589394868351519107818603515625
]
}
}
},
"d8cbe80fca45933149672c23d1c95cbdab4d8ca5": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=32 --model=vgg16",
"description": "Device: CPU - Batch Size: 32 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"b": {
"value": 76.0400000000000062527760746888816356658935546875,
"test_run_times": [
49.71000000000000085265128291212022304534912109375
]
}
}
},
"27728d5ccf6d68a6274e3d800a76cbeee3a59a98": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=64 --model=vgg16",
"description": "Device: CPU - Batch Size: 64 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"b": {
"value": 95.909999999999996589394868351519107818603515625,
"test_run_times": [
77.2399999999999948840923025272786617279052734375
]
}
}
},
"801cae2e8025c5598601ed7196f53697d6cdd87e": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=256 --model=vgg16",
"description": "Device: CPU - Batch Size: 256 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"b": {
"value": 127.18000000000000682121026329696178436279296875,
"test_run_times": [
227.75
]
}
}
},
"b5b40ba89ab3ef335b7f99f8d43cca4cd14caccb": {
"identifier": "pts\/tensorflow-2.2.0",
"title": "TensorFlow",
"app_version": "2.16.1",
"arguments": "--device cpu --batch_size=512 --model=vgg16",
"description": "Device: CPU - Batch Size: 512 - Model: VGG-16",
"scale": "images\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"b": {
"value": 135.780000000000001136868377216160297393798828125,
"test_run_times": [
422.92000000000001591615728102624416351318359375
]
}
}
},
"e40d6565e0c575145dc453b94f3ca3ca2807fdeb": {
"identifier": "pts\/build-mesa-1.1.0",
"title": "Timed Mesa Compilation",
"app_version": "24.0",
"description": "Time To Compile",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"PRE": {
"value": 14.660000000000000142108547152020037174224853515625,
"test_run_times": [
14.660000000000000142108547152020037174224853515625
]
},
"a": {
"value": 14.756000000000000227373675443232059478759765625,
"raw_values": [
14.757999999999999118927007657475769519805908203125,
14.827999999999999403144101961515843868255615234375,
14.6809999999999991615595718030817806720733642578125
],
"test_run_times": [
14.7599999999999997868371792719699442386627197265625,
14.8300000000000000710542735760100185871124267578125,
14.67999999999999971578290569595992565155029296875
]
},
"b": {
"value": 14.7110000000000002984279490192420780658721923828125,
"test_run_times": [
14.71000000000000085265128291212022304534912109375
]
}
}
}
}
}