Tests for a future article. AMD Ryzen 9 5900HX testing with a ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS) and ASUS AMD Cezanne 512MB on Ubuntu 22.10 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 2403290-PTS-5900HXEO83
{
"title": "5900hx eo q1",
"last_modified": "2024-03-29 16:28:58",
"description": "Tests for a future article. AMD Ryzen 9 5900HX testing with a ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS) and ASUS AMD Cezanne 512MB on Ubuntu 22.10 via the Phoronix Test Suite.",
"systems": {
"a": {
"identifier": "a",
"hardware": {
"Processor": "AMD Ryzen 9 5900HX @ 3.30GHz (8 Cores \/ 16 Threads)",
"Motherboard": "ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS)",
"Chipset": "AMD Renoir\/Cezanne",
"Memory": "2 x 8GB DDR4-3200MT\/s Micron 4ATF1G64HZ-3G2E2",
"Disk": "512GB SAMSUNG MZVLQ512HBLU-00B00",
"Graphics": "ASUS AMD Cezanne 512MB (2500\/1000MHz)",
"Audio": "AMD Navi 21\/23",
"Monitor": "LQ156M1JW25",
"Network": "Realtek RTL8111\/8168\/8411 + MEDIATEK MT7921 802.11ax PCI"
},
"software": {
"OS": "Ubuntu 22.10",
"Kernel": "5.19.0-46-generic (x86_64)",
"Desktop": "GNOME Shell 43.0",
"Display Server": "X Server 1.21.1.4 + Wayland",
"OpenGL": "4.6 Mesa 22.2.5 (LLVM 15.0.2 DRM 3.47)",
"Vulkan": "1.3.224",
"Compiler": "GCC 12.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1080"
},
"user": "pts",
"timestamp": "2024-03-29 11:26:19",
"client_version": "10.8.4",
"data": {
"compiler-configuration": "--build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-12-U8K4Qv\/gcc-12-12.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-12-U8K4Qv\/gcc-12-12.2.0\/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-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",
"cpu-pm": "ACPI Profile: balanced",
"platform-profile": "balanced",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.10.7",
"security": "itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"b": {
"identifier": "b",
"hardware": {
"Processor": "AMD Ryzen 9 5900HX @ 3.30GHz (8 Cores \/ 16 Threads)",
"Motherboard": "ASUS ROG Strix G513QY_G513QY G513QY v1.0 (G513QY.318 BIOS)",
"Chipset": "AMD Renoir\/Cezanne",
"Memory": "2 x 8GB DDR4-3200MT\/s Micron 4ATF1G64HZ-3G2E2",
"Disk": "512GB SAMSUNG MZVLQ512HBLU-00B00",
"Graphics": "ASUS AMD Cezanne 512MB (2500\/1000MHz)",
"Audio": "AMD Navi 21\/23",
"Monitor": "LQ156M1JW25",
"Network": "Realtek RTL8111\/8168\/8411 + MEDIATEK MT7921 802.11ax PCI"
},
"software": {
"OS": "Ubuntu 22.10",
"Kernel": "5.19.0-46-generic (x86_64)",
"Desktop": "GNOME Shell 43.0",
"Display Server": "X Server 1.21.1.4 + Wayland",
"OpenGL": "4.6 Mesa 22.2.5 (LLVM 15.0.2 DRM 3.47)",
"Vulkan": "1.3.224",
"Compiler": "GCC 12.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1080"
},
"user": "pts",
"timestamp": "2024-03-29 13:54:13",
"client_version": "10.8.4",
"data": {
"compiler-configuration": "--build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-12-U8K4Qv\/gcc-12-12.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-12-U8K4Qv\/gcc-12-12.2.0\/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-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",
"cpu-pm": "ACPI Profile: balanced",
"platform-profile": "balanced",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.10.7",
"security": "itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
}
},
"results": {
"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": {
"a": {
"value": 155860,
"test_run_times": [
467.1100000000000136424205265939235687255859375
],
"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": 155503,
"test_run_times": [
478.6000000000000227373675443232059478759765625
],
"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"
}
}
}
}
},
"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": {
"a": {
"value": 4.61000000000000031974423109204508364200592041015625,
"test_run_times": [
26.620000000000000994759830064140260219573974609375
]
},
"b": {
"value": 4.71999999999999975131004248396493494510650634765625,
"test_run_times": [
25.8900000000000005684341886080801486968994140625
]
}
}
},
"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": {
"a": {
"value": 41.53999999999999914734871708787977695465087890625,
"test_run_times": [
44.159999999999996589394868351519107818603515625
]
},
"b": {
"value": 42.63000000000000255795384873636066913604736328125,
"test_run_times": [
43.00999999999999801048033987171947956085205078125
]
}
}
},
"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": {
"a": {
"value": 57.090000000000003410605131648480892181396484375,
"test_run_times": [
63.4200000000000017053025658242404460906982421875
]
},
"b": {
"value": 58.03999999999999914734871708787977695465087890625,
"test_run_times": [
62.35000000000000142108547152020037174224853515625
]
}
}
},
"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": {
"a": {
"value": 69.68000000000000682121026329696178436279296875,
"test_run_times": [
102.75
]
},
"b": {
"value": 70.840000000000003410605131648480892181396484375,
"test_run_times": [
101.030000000000001136868377216160297393798828125
]
}
}
},
"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": {
"a": {
"value": 13.03999999999999914734871708787977695465087890625,
"test_run_times": [
10.82000000000000028421709430404007434844970703125
]
},
"b": {
"value": 13.199999999999999289457264239899814128875732421875,
"test_run_times": [
10.730000000000000426325641456060111522674560546875
]
}
}
},
"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": {
"a": {
"value": 5.3300000000000000710542735760100185871124267578125,
"test_run_times": [
23.769999999999999573674358543939888477325439453125
]
},
"b": {
"value": 5.480000000000000426325641456060111522674560546875,
"test_run_times": [
23.190000000000001278976924368180334568023681640625
]
}
}
},
"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": {
"a": {
"value": 21.870000000000000994759830064140260219573974609375,
"test_run_times": [
82.9800000000000039790393202565610408782958984375
]
},
"b": {
"value": 22.10000000000000142108547152020037174224853515625,
"test_run_times": [
82.0799999999999982946974341757595539093017578125
]
}
}
},
"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": {
"a": {
"value": 7.8499999999999996447286321199499070644378662109375,
"test_run_times": [
227.229999999999989768184605054557323455810546875
]
},
"b": {
"value": 7.87000000000000010658141036401502788066864013671875,
"test_run_times": [
226.719999999999998863131622783839702606201171875
]
}
}
},
"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": {
"a": {
"value": 21.780000000000001136868377216160297393798828125,
"test_run_times": [
164.090000000000003410605131648480892181396484375
]
},
"b": {
"value": 21.89999999999999857891452847979962825775146484375,
"test_run_times": [
163.270000000000010231815394945442676544189453125
]
}
}
},
"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": {
"a": {
"value": 7.71999999999999975131004248396493494510650634765625,
"test_run_times": [
458.98000000000001818989403545856475830078125
]
},
"b": {
"value": 7.79999999999999982236431605997495353221893310546875,
"test_run_times": [
454.279999999999972715158946812152862548828125
]
}
}
},
"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": {
"a": {
"value": 21.67999999999999971578290569595992565155029296875,
"test_run_times": [
327.3700000000000045474735088646411895751953125
]
},
"b": {
"value": 21.8299999999999982946974341757595539093017578125,
"test_run_times": [
324.98000000000001818989403545856475830078125
]
}
}
},
"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": {
"a": {
"value": 7.69000000000000039079850466805510222911834716796875,
"test_run_times": [
918.6299999999999954525264911353588104248046875
]
},
"b": {
"value": 7.839999999999999857891452847979962825775146484375,
"test_run_times": [
902.0800000000000409272615797817707061767578125
]
}
}
},
"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": {
"a": {
"value": 33.77000000000000312638803734444081783294677734375,
"raw_values": [
33.76619203287899750876022153533995151519775390625
],
"min_result": [
"28.4"
],
"max_result": [
"36.15"
],
"test_run_times": [
36.27000000000000312638803734444081783294677734375
]
},
"b": {
"value": 33.06000000000000227373675443232059478759765625,
"raw_values": [
33.06068164398499931166952592320740222930908203125
],
"min_result": [
"24.65"
],
"max_result": [
"35.35"
],
"test_run_times": [
36.85000000000000142108547152020037174224853515625
]
}
}
},
"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": {
"a": {
"value": 15.4900000000000002131628207280300557613372802734375,
"raw_values": [
15.4937807318629996444769858499057590961456298828125
],
"min_result": [
"13.24"
],
"max_result": [
"15.91"
],
"test_run_times": [
74.340000000000003410605131648480892181396484375
]
},
"b": {
"value": 15.17999999999999971578290569595992565155029296875,
"raw_values": [
15.1813004417179993055242448463104665279388427734375
],
"min_result": [
"12.92"
],
"max_result": [
"16.18"
],
"test_run_times": [
75.7300000000000039790393202565610408782958984375
]
}
}
},
"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": {
"a": {
"value": 19.760000000000001563194018672220408916473388671875,
"raw_values": [
19.76474938959700011764653027057647705078125
],
"min_result": [
"18.28"
],
"max_result": [
"20.45"
],
"test_run_times": [
91.2999999999999971578290569595992565155029296875
]
},
"b": {
"value": 19.219999999999998863131622783839702606201171875,
"raw_values": [
19.22110231915900158128351904451847076416015625
],
"min_result": [
"17.83"
],
"max_result": [
"19.83"
],
"test_run_times": [
93.7399999999999948840923025272786617279052734375
]
}
}
},
"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": {
"a": {
"value": 19.660000000000000142108547152020037174224853515625,
"raw_values": [
19.65659055974600022409504163078963756561279296875
],
"min_result": [
"18.64"
],
"max_result": [
"20.3"
],
"test_run_times": [
93.2699999999999960209606797434389591217041015625
]
},
"b": {
"value": 20.769999999999999573674358543939888477325439453125,
"raw_values": [
20.766831678452998488637604168616235256195068359375
],
"min_result": [
"17.08"
],
"max_result": [
"21.79"
],
"test_run_times": [
85.1099999999999994315658113919198513031005859375
]
}
}
},
"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": {
"a": {
"value": 20.1099999999999994315658113919198513031005859375,
"raw_values": [
20.11403135396700037063055788166821002960205078125
],
"min_result": [
"18.97"
],
"max_result": [
"21.46"
],
"test_run_times": [
89.81000000000000227373675443232059478759765625
]
},
"b": {
"value": 18.589999999999999857891452847979962825775146484375,
"raw_values": [
18.587567920590998937768745236098766326904296875
],
"min_result": [
"17.92"
],
"max_result": [
"18.9"
],
"test_run_times": [
93.7399999999999948840923025272786617279052734375
]
}
}
},
"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": {
"a": {
"value": 9.21000000000000085265128291212022304534912109375,
"raw_values": [
9.2126452713237991787309510982595384120941162109375
],
"min_result": [
"8.4"
],
"max_result": [
"9.79"
],
"test_run_times": [
198.099999999999994315658113919198513031005859375
]
},
"b": {
"value": 9.1699999999999999289457264239899814128875732421875,
"raw_values": [
9.1664289502538007781140549923293292522430419921875
],
"min_result": [
"7.84"
],
"max_result": [
"9.75"
],
"test_run_times": [
196.68000000000000682121026329696178436279296875
]
}
}
},
"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": {
"a": {
"value": 9.1500000000000003552713678800500929355621337890625,
"raw_values": [
9.1466894645297003307859995402395725250244140625
],
"min_result": [
"8.27"
],
"max_result": [
"9.72"
],
"test_run_times": [
197.659999999999996589394868351519107818603515625
]
},
"b": {
"value": 8.6899999999999995026200849679298698902130126953125,
"raw_values": [
8.6915009488927008618475156254135072231292724609375
],
"min_result": [
"8.29"
],
"max_result": [
"9.38"
],
"test_run_times": [
201.75
]
}
}
},
"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": {
"a": {
"value": 8.6699999999999999289457264239899814128875732421875,
"raw_values": [
8.674097957345100695647488464601337909698486328125
],
"min_result": [
"7.68"
],
"max_result": [
"9.4"
],
"test_run_times": [
203.210000000000007958078640513122081756591796875
]
},
"b": {
"value": 9.339999999999999857891452847979962825775146484375,
"raw_values": [
9.3354580505813000712578286766074597835540771484375
],
"min_result": [
"8.61"
],
"max_result": [
"9.98"
],
"test_run_times": [
192.44999999999998863131622783839702606201171875
]
}
}
},
"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": {
"a": {
"value": 9.3300000000000000710542735760100185871124267578125,
"raw_values": [
9.3308702512336996193198501714505255222320556640625
],
"min_result": [
"8.18"
],
"max_result": [
"9.65"
],
"test_run_times": [
122.3599999999999994315658113919198513031005859375
]
},
"b": {
"value": 9.550000000000000710542735760100185871124267578125,
"raw_values": [
9.5527072187722996687853083130903542041778564453125
],
"min_result": [
"8.99"
],
"max_result": [
"9.9"
],
"test_run_times": [
119.6700000000000017053025658242404460906982421875
]
}
}
},
"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": {
"a": {
"value": 6.21999999999999975131004248396493494510650634765625,
"raw_values": [
6.21767496229370042470918633625842630863189697265625
],
"min_result": [
"5.81"
],
"max_result": [
"6.46"
],
"test_run_times": [
298.68000000000000682121026329696178436279296875
]
},
"b": {
"value": 6.339999999999999857891452847979962825775146484375,
"raw_values": [
6.34230373154319959638769432785920798778533935546875
],
"min_result": [
"6.05"
],
"max_result": [
"6.53"
],
"test_run_times": [
294.1499999999999772626324556767940521240234375
]
}
}
},
"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": {
"a": {
"value": 6.21999999999999975131004248396493494510650634765625,
"raw_values": [
6.224648319718600220085136243142187595367431640625
],
"min_result": [
"5.89"
],
"max_result": [
"6.48"
],
"test_run_times": [
299.91000000000002501110429875552654266357421875
]
},
"b": {
"value": 6.17999999999999971578290569595992565155029296875,
"raw_values": [
6.18123217694159965418521096580661833286285400390625
],
"min_result": [
"5.92"
],
"max_result": [
"6.42"
],
"test_run_times": [
298.8899999999999863575794734060764312744140625
]
}
}
},
"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": {
"a": {
"value": 6.21999999999999975131004248396493494510650634765625,
"raw_values": [
6.22014391899570018296117268619127571582794189453125
],
"min_result": [
"5.84"
],
"max_result": [
"6.49"
],
"test_run_times": [
298.06999999999999317878973670303821563720703125
]
},
"b": {
"value": 5.9000000000000003552713678800500929355621337890625,
"raw_values": [
5.89866643243239963112500845454633235931396484375
],
"min_result": [
"5.51"
],
"max_result": [
"6.32"
],
"test_run_times": [
307.48000000000001818989403545856475830078125
]
}
}
},
"7e0a0b59e46d596b26cb4b6781f8ea1acfb478d3": {
"identifier": "pts\/primesieve-1.10.0",
"title": "Primesieve",
"app_version": "12.1",
"arguments": "1e12",
"description": "Length: 1e12",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 19.2710000000000007958078640513122081756591796875,
"test_run_times": [
19.28999999999999914734871708787977695465087890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 19.251999999999998891553332214243710041046142578125,
"test_run_times": [
19.260000000000001563194018672220408916473388671875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"f7bde6e6bd4dbb60d5b8b62e4dcb0d37bdd03163": {
"identifier": "pts\/stockfish-1.5.0",
"title": "Stockfish",
"app_version": "16.1",
"description": "Chess Benchmark",
"scale": "Nodes Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 11509974,
"test_run_times": [
162.56999999999999317878973670303821563720703125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-lgcov -m64 -lpthread -fno-exceptions -std=c++17 -fno-peel-loops -fno-tracer -pedantic -O3 -funroll-loops -msse -msse3 -mpopcnt -mavx2 -mbmi -msse4.1 -mssse3 -msse2 -mbmi2 -flto -flto-partition=one -flto=jobserver"
}
}
},
"b": {
"value": 12942804,
"test_run_times": [
155.81000000000000227373675443232059478759765625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-lgcov -m64 -lpthread -fno-exceptions -std=c++17 -fno-peel-loops -fno-tracer -pedantic -O3 -funroll-loops -msse -msse3 -mpopcnt -mavx2 -mbmi -msse4.1 -mssse3 -msse2 -mbmi2 -flto -flto-partition=one -flto=jobserver"
}
}
}
}
},
"07874bd30a80753be1d28881eddc0428fcb350ae": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160",
"description": "Encoder Mode: Preset 4 - Input: Bosphorus 4K",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 3.6349999999999997868371792719699442386627197265625,
"test_run_times": [
44.93999999999999772626324556767940521240234375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 3.653999999999999914734871708787977695465087890625,
"test_run_times": [
44.6700000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"2d6461041456af39b5df4efcec7f39f3157f549d": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160",
"description": "Encoder Mode: Preset 8 - Input: Bosphorus 4K",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 26.05499999999999971578290569595992565155029296875,
"test_run_times": [
23.780000000000001136868377216160297393798828125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 25.998999999999998777866494492627680301666259765625,
"test_run_times": [
23.809999999999998721023075631819665431976318359375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"b7dbdc4a31deb7c3fd3898dbe6df6073d5bae0ee": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160",
"description": "Encoder Mode: Preset 12 - Input: Bosphorus 4K",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 64.01200000000000045474735088646411895751953125,
"test_run_times": [
9.9399999999999995026200849679298698902130126953125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 62.73899999999999721467247582040727138519287109375,
"test_run_times": [
10.1300000000000007815970093361102044582366943359375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"685f4e221e2e654e3714ee352fed82e506e17245": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 13 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160",
"description": "Encoder Mode: Preset 13 - Input: Bosphorus 4K",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 65.4980000000000046611603465862572193145751953125,
"test_run_times": [
9.7200000000000006394884621840901672840118408203125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 64.3829999999999955662133288569748401641845703125,
"test_run_times": [
9.8699999999999992184029906638897955417633056640625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"dc904a5f05b6af7d9d2f0cb350633ab3906286e0": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 4 -n 160 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080",
"description": "Encoder Mode: Preset 4 - Input: Bosphorus 1080p",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 12.928000000000000824229573481716215610504150390625,
"test_run_times": [
12.7599999999999997868371792719699442386627197265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 13.025999999999999801048033987171947956085205078125,
"test_run_times": [
12.660000000000000142108547152020037174224853515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"e25f1395e53b97de67de5cb714bfadc6f1a32e2b": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 8 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080",
"description": "Encoder Mode: Preset 8 - Input: Bosphorus 1080p",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 86.626000000000004774847184307873249053955078125,
"test_run_times": [
7.28000000000000024868995751603506505489349365234375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 83.8709999999999951114659779705107212066650390625,
"test_run_times": [
7.5
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"cf74c258930ce6572b669052b6a298b7e2c32c02": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 12 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080",
"description": "Encoder Mode: Preset 12 - Input: Bosphorus 1080p",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 285.0149999999999863575794734060764312744140625,
"test_run_times": [
2.29999999999999982236431605997495353221893310546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 266.97300000000001318767317570745944976806640625,
"test_run_times": [
2.439999999999999946709294817992486059665679931640625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"fa830dfe04cd3079e6f88420aec30f0bb9868cfb": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 13 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080",
"description": "Encoder Mode: Preset 13 - Input: Bosphorus 1080p",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 329.49700000000001409716787748038768768310546875,
"test_run_times": [
2.0099999999999997868371792719699442386627197265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 332.8980000000000245563569478690624237060546875,
"test_run_times": [
1.9899999999999999911182158029987476766109466552734375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"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": {
"a": {
"value": 152.81000000000000227373675443232059478759765625,
"test_run_times": [
154
]
},
"b": {
"value": 154.219999999999998863131622783839702606201171875,
"test_run_times": [
154.919999999999987494447850622236728668212890625
]
}
}
},
"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": {
"a": {
"value": 208.770000000000010231815394945442676544189453125,
"test_run_times": [
209.849999999999994315658113919198513031005859375
]
},
"b": {
"value": 208.68999999999999772626324556767940521240234375,
"test_run_times": [
209.740000000000009094947017729282379150390625
]
}
}
},
"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": {
"a": {
"value": 395.990000000000009094947017729282379150390625,
"test_run_times": [
396.42000000000001591615728102624416351318359375
]
},
"b": {
"value": 397.58999999999997498889570124447345733642578125,
"test_run_times": [
397.95999999999997953636921010911464691162109375
]
}
}
},
"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": {
"a": {
"value": 186.330000000000012505552149377763271331787109375,
"test_run_times": [
186.960000000000007958078640513122081756591796875
]
},
"b": {
"value": 185.759999999999990905052982270717620849609375,
"test_run_times": [
186.400000000000005684341886080801486968994140625
]
}
}
},
"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": {
"a": {
"value": 1474.589999999999918145476840436458587646484375,
"test_run_times": [
1478.59999999999990905052982270717620849609375
]
},
"b": {
"value": 1490.950000000000045474735088646411895751953125,
"test_run_times": [
1494.920000000000072759576141834259033203125
]
}
}
},
"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": {
"a": {
"value": 481.6200000000000045474735088646411895751953125,
"test_run_times": [
482.20999999999997953636921010911464691162109375
]
},
"b": {
"value": 482.1299999999999954525264911353588104248046875,
"test_run_times": [
482.759999999999990905052982270717620849609375
]
}
}
},
"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": {
"a": {
"value": 44.55499999999999971578290569595992565155029296875,
"test_run_times": [
44.56000000000000227373675443232059478759765625
]
},
"b": {
"value": 43.98599999999999710098563809879124164581298828125,
"test_run_times": [
43.99000000000000198951966012828052043914794921875
]
}
}
}
}
}