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 2401107-PTS-FGHJ244998
{
"title": "fghj",
"last_modified": "2024-01-10 10:10:41",
"description": "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 8 GB 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": "2024-01-09 20:49:25",
"client_version": "10.8.5",
"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 8 GB DDR4-3200MT\/s Micron 4ATF1G64HZ-3G2E2",
"Disk": "512GB SAMSUNG MZVLQ512HBLU-00B00",
"Graphics": "ASUS AMD Cezanne 512MB",
"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": "2024-01-09 21:50:24",
"client_version": "10.8.5",
"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"
}
},
"c": {
"identifier": "c",
"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 8 GB 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": "2024-01-10 04:57:33",
"client_version": "10.8.5",
"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": {
"4c7bf00e1ffdac6120c4e7e06f896a2dcf99c6a6": {
"identifier": "pts\/pytorch-1.0.1",
"title": "PyTorch",
"app_version": "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": 34.03999999999999914734871708787977695465087890625,
"raw_values": [
34.038904189134001398997497744858264923095703125
],
"min_result": [
"28.91"
],
"max_result": [
"36.18"
],
"test_run_times": [
35.340000000000003410605131648480892181396484375
]
},
"b": {
"value": 34.43999999999999772626324556767940521240234375,
"raw_values": [
31.41179710701300109576550312340259552001953125,
32.4235127447170015102528850547969341278076171875,
33.32756433062500178721165866591036319732666015625,
34.557278778658002238444169051945209503173828125,
35.53470587111799972035441896878182888031005859375,
34.145531955774998777997097931802272796630859375,
34.31938505788900073412150959484279155731201171875,
33.91428422655400254370761103928089141845703125,
34.328772573625002451080945320427417755126953125,
35.01279013043200194488235865719616413116455078125,
37.10556537386099762443336658179759979248046875,
37.16263682784499877698181080631911754608154296875
],
"min_result": [
"26.93"
],
"max_result": [
"39.45"
],
"test_run_times": [
37.5799999999999982946974341757595539093017578125,
36.6099999999999994315658113919198513031005859375,
35.72999999999999687361196265555918216705322265625,
34.61999999999999744204615126363933086395263671875,
33.7000000000000028421709430404007434844970703125,
35.03999999999999914734871708787977695465087890625,
34.8599999999999994315658113919198513031005859375,
35.13000000000000255795384873636066913604736328125,
34.8299999999999982946974341757595539093017578125,
34.2000000000000028421709430404007434844970703125,
32.52000000000000312638803734444081783294677734375,
32.3900000000000005684341886080801486968994140625
]
},
"c": {
"value": 34.13000000000000255795384873636066913604736328125,
"raw_values": [
35.45846843269900006134776049293577671051025390625,
36.18516589048000042794228647835552692413330078125,
34.07171041674499889495564275421202182769775390625,
32.50677324354700203912216238677501678466796875,
32.24618977116499962676243740133941173553466796875,
34.96883870941299932155743590556085109710693359375,
33.369296875071000840762280859053134918212890625,
33.431754979613998557397280819714069366455078125,
32.57657222099400229353705071844160556793212890625,
33.62081264528099922017645440064370632171630859375,
35.42041871855399648438833537511527538299560546875,
34.9432617574669990290203713811933994293212890625,
35.1834263305560028811669326387345790863037109375,
35.41490638318099826165052945725619792938232421875,
32.47908325073100144209092832170426845550537109375
],
"min_result": [
"26.23"
],
"max_result": [
"39.87"
],
"test_run_times": [
33.780000000000001136868377216160297393798828125,
33.13000000000000255795384873636066913604736328125,
35.0499999999999971578290569595992565155029296875,
36.60000000000000142108547152020037174224853515625,
36.82000000000000028421709430404007434844970703125,
34.47999999999999687361196265555918216705322265625,
35.75,
35.67999999999999971578290569595992565155029296875,
36.49000000000000198951966012828052043914794921875,
35.42999999999999971578290569595992565155029296875,
33.78999999999999914734871708787977695465087890625,
34.17999999999999971578290569595992565155029296875,
33.97999999999999687361196265555918216705322265625,
33.86999999999999744204615126363933086395263671875,
36.6400000000000005684341886080801486968994140625
]
}
}
},
"0f8d8cb3b9eaa2299a391dfeb4ecf8e83c675ab3": {
"identifier": "pts\/pytorch-1.0.1",
"title": "PyTorch",
"app_version": "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": 15.1500000000000003552713678800500929355621337890625,
"raw_values": [
15.1539787785879997983329303679056465625762939453125
],
"min_result": [
"13.55"
],
"max_result": [
"16.17"
],
"test_run_times": [
75.8599999999999994315658113919198513031005859375
]
},
"b": {
"value": 15.269999999999999573674358543939888477325439453125,
"raw_values": [
15.307634723317999458913618582300841808319091796875,
15.047894456984000299826220725663006305694580078125,
15.46067976003899957504472695291042327880859375
],
"min_result": [
"12.92"
],
"max_result": [
"16.47"
],
"test_run_times": [
74.9200000000000017053025658242404460906982421875,
76.4500000000000028421709430404007434844970703125,
74.5100000000000051159076974727213382720947265625
]
},
"c": {
"value": 15.21000000000000085265128291212022304534912109375,
"raw_values": [
15.120672666865999644869589246809482574462890625,
15.143607087323999849104438908398151397705078125,
15.367364168350999165113535127602517604827880859375
],
"min_result": [
"13.44"
],
"max_result": [
"16.4"
],
"test_run_times": [
76.0100000000000051159076974727213382720947265625,
75.8599999999999994315658113919198513031005859375,
75.0799999999999982946974341757595539093017578125
]
}
}
},
"594d16c50ef13421d29a77ac009ce481ebc2a82c": {
"identifier": "pts\/pytorch-1.0.1",
"title": "PyTorch",
"app_version": "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": 20.219999999999998863131622783839702606201171875,
"raw_values": [
20.22027348229600107742953696288168430328369140625
],
"min_result": [
"18.6"
],
"max_result": [
"20.71"
],
"test_run_times": [
90.1700000000000017053025658242404460906982421875
]
},
"b": {
"value": 18.949999999999999289457264239899814128875732421875,
"raw_values": [
18.949872077287000848855313961394131183624267578125,
19.786839843149000017774596926756203174591064453125,
20.536952002814000906028013559989631175994873046875,
19.520178143039000673297778121195733547210693359375,
19.462228654644999181755338213406503200531005859375,
17.250528755834000804725292255170643329620361328125,
19.9421389519419989255766267888247966766357421875,
19.05123688356000144494828418828547000885009765625,
17.3282418573379999315875465981662273406982421875,
19.35845123491800023884934489615261554718017578125,
18.829148806028999985073824063874781131744384765625,
19.545769445579001200030688778497278690338134765625,
18.59431497539100064386730082333087921142578125,
18.745193973136000664680977934040129184722900390625,
17.41388778090900046890965313650667667388916015625
],
"min_result": [
"14.69"
],
"max_result": [
"21.46"
],
"test_run_times": [
94.68999999999999772626324556767940521240234375,
92.2300000000000039790393202565610408782958984375,
88.1400000000000005684341886080801486968994140625,
91.349999999999994315658113919198513031005859375,
90.9500000000000028421709430404007434844970703125,
99.3700000000000045474735088646411895751953125,
90.0400000000000062527760746888816356658935546875,
91.9599999999999937472239253111183643341064453125,
96.900000000000005684341886080801486968994140625,
91.3299999999999982946974341757595539093017578125,
92.1400000000000005684341886080801486968994140625,
92.530000000000001136868377216160297393798828125,
94.93000000000000682121026329696178436279296875,
95.0199999999999960209606797434389591217041015625,
98.3700000000000045474735088646411895751953125
]
},
"c": {
"value": 19.760000000000001563194018672220408916473388671875,
"raw_values": [
19.722617295683999572020184132270514965057373046875,
20.150905789961001346455304883420467376708984375,
19.4135538118219983516610227525234222412109375
],
"min_result": [
"16.58"
],
"max_result": [
"21.09"
],
"test_run_times": [
92.2699999999999960209606797434389591217041015625,
87.7999999999999971578290569595992565155029296875,
91.969999999999998863131622783839702606201171875
]
}
}
},
"4f2db05f6bebd9b371472ed1afa49f37fc27fa2a": {
"identifier": "pts\/pytorch-1.0.1",
"title": "PyTorch",
"app_version": "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": 9.089999999999999857891452847979962825775146484375,
"raw_values": [
9.0906025697537007346227255766279995441436767578125
],
"min_result": [
"8.47"
],
"max_result": [
"9.73"
],
"test_run_times": [
196.409999999999996589394868351519107818603515625
]
},
"b": {
"value": 9.07000000000000028421709430404007434844970703125,
"raw_values": [
9.3013759770743007493365439586341381072998046875,
9.47056289629909997529466636478900909423828125,
8.54944364619110075409480486996471881866455078125,
8.922380353636700789365931996144354343414306640625,
9.1733347513166005882112585823051631450653076171875,
9.1921923145959993917131214402616024017333984375,
8.938977817981200502117644646205008029937744140625,
9.214398068868600688574588275514543056488037109375,
9.1904102073154003704757997184060513973236083984375,
9.0788411646003002175575602450408041477203369140625,
8.7184899689196999617024630424566566944122314453125,
9.0820361018390993734783478430472314357757568359375
],
"min_result": [
"7.85"
],
"max_result": [
"10"
],
"test_run_times": [
193.31999999999999317878973670303821563720703125,
192.150000000000005684341886080801486968994140625,
204.229999999999989768184605054557323455810546875,
198.259999999999990905052982270717620849609375,
196.099999999999994315658113919198513031005859375,
194.020000000000010231815394945442676544189453125,
198.539999999999992041921359486877918243408203125,
195.6299999999999954525264911353588104248046875,
196.289999999999992041921359486877918243408203125,
196.56999999999999317878973670303821563720703125,
201.1100000000000136424205265939235687255859375,
196.030000000000001136868377216160297393798828125
]
},
"c": {
"value": 9.1400000000000005684341886080801486968994140625,
"raw_values": [
8.8817213667591996539840693003498017787933349609375,
9.2028433398582993874015301116742193698883056640625,
9.5227006098778002041171930613927543163299560546875,
9.108896924629899416459011263214051723480224609375,
8.9880619811775996907954322523437440395355224609375,
8.813792666080399129668876412324607372283935546875,
9.4285036210316999216729527688585221767425537109375,
9.2182219405602996431525752996094524860382080078125,
8.9630644258333003193683907738886773586273193359375,
9.4115054399303001986254457733593881130218505859375,
8.6568483126194006871401143143884837627410888671875,
9.442547112751100257810321636497974395751953125
],
"min_result": [
"6.86"
],
"max_result": [
"9.99"
],
"test_run_times": [
198.979999999999989768184605054557323455810546875,
195.580000000000012505552149377763271331787109375,
192.31000000000000227373675443232059478759765625,
196.229999999999989768184605054557323455810546875,
198.909999999999996589394868351519107818603515625,
200.6100000000000136424205265939235687255859375,
192.960000000000007958078640513122081756591796875,
196.56000000000000227373675443232059478759765625,
197.8799999999999954525264911353588104248046875,
194.740000000000009094947017729282379150390625,
202.759999999999990905052982270717620849609375,
193.669999999999987494447850622236728668212890625
]
}
}
},
"06433753eb3461ed54a6c8a439305e4be1795a41": {
"identifier": "pts\/pytorch-1.0.1",
"title": "PyTorch",
"app_version": "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": 9.5800000000000000710542735760100185871124267578125,
"raw_values": [
9.5822977206863004795422966708429157733917236328125
],
"min_result": [
"8.52"
],
"max_result": [
"9.8"
],
"test_run_times": [
119.6299999999999954525264911353588104248046875
]
},
"b": {
"value": 9.46000000000000085265128291212022304534912109375,
"raw_values": [
9.5237220263524005048338949563913047313690185546875,
9.399677954941299873325988301075994968414306640625,
9.4528289478001994439182453788816928863525390625
],
"min_result": [
"8.4"
],
"max_result": [
"9.86"
],
"test_run_times": [
120.0100000000000051159076974727213382720947265625,
121.349999999999994315658113919198513031005859375,
120.81000000000000227373675443232059478759765625
]
},
"c": {
"value": 9.480000000000000426325641456060111522674560546875,
"raw_values": [
9.50759456579410056065171374939382076263427734375,
9.4821569042838991236976653453893959522247314453125,
9.44764933978130017067087464965879917144775390625
],
"min_result": [
"8.48"
],
"max_result": [
"9.81"
],
"test_run_times": [
120.1099999999999994315658113919198513031005859375,
120.5400000000000062527760746888816356658935546875,
120.9500000000000028421709430404007434844970703125
]
}
}
},
"c2e61282c984934f432761184e26030c16efcb9a": {
"identifier": "pts\/pytorch-1.0.1",
"title": "PyTorch",
"app_version": "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": [
6.21633414754170043892145258723758161067962646484375
],
"min_result": [
"5.85"
],
"max_result": [
"6.47"
],
"test_run_times": [
297.33999999999997498889570124447345733642578125
]
},
"b": {
"value": 6.28000000000000024868995751603506505489349365234375,
"raw_values": [
6.3456892146003998078640506719239056110382080078125,
6.24089273943330002936136224889196455478668212890625,
6.25204989515760001239641496795229613780975341796875
],
"min_result": [
"5.5"
],
"max_result": [
"6.59"
],
"test_run_times": [
293.8899999999999863575794734060764312744140625,
297.45999999999997953636921010911464691162109375,
298.6499999999999772626324556767940521240234375
]
},
"c": {
"value": 6.29999999999999982236431605997495353221893310546875,
"raw_values": [
6.21599101825780042673841307987459003925323486328125,
6.23774667074080024775639685685746371746063232421875,
6.43808313849779967341646624845452606678009033203125
],
"min_result": [
"5.7"
],
"max_result": [
"6.6"
],
"test_run_times": [
298.81999999999999317878973670303821563720703125,
298.68000000000000682121026329696178436279296875,
293.17000000000001591615728102624416351318359375
]
}
}
},
"3a48ff0a7df267f1cad54d0160f1013f6bfa0da6": {
"identifier": "pts\/quicksilver-1.0.0",
"title": "Quicksilver",
"app_version": "20230818",
"arguments": "..\/Examples\/CTS2_Benchmark\/CTS2.inp",
"description": "Input: CTS2",
"scale": "Figure Of Merit",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 11390000,
"test_run_times": [
444.8899999999999863575794734060764312744140625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -O3 -march=native"
}
}
},
"b": {
"value": 11406667,
"raw_values": [
11370000,
11400000,
11450000
],
"test_run_times": [
445.56000000000000227373675443232059478759765625,
444.31999999999999317878973670303821563720703125,
442.44999999999998863131622783839702606201171875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -O3 -march=native"
}
}
},
"c": {
"value": 11416667,
"raw_values": [
11430000,
11390000,
11430000
],
"test_run_times": [
443.279999999999972715158946812152862548828125,
445.01999999999998181010596454143524169921875,
443.240000000000009094947017729282379150390625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -O3 -march=native"
}
}
}
}
},
"0083d93c7c846aae457cdffe798d6ed7a26cafbe": {
"identifier": "pts\/quicksilver-1.0.0",
"title": "Quicksilver",
"app_version": "20230818",
"arguments": "..\/Examples\/CORAL2_Benchmark\/Problem1\/Coral2_P1.inp",
"description": "Input: CORAL2 P1",
"scale": "Figure Of Merit",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 11990000,
"test_run_times": [
92.4800000000000039790393202565610408782958984375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -O3 -march=native"
}
}
},
"b": {
"value": 11966667,
"raw_values": [
12000000,
11940000,
11960000
],
"test_run_times": [
92.4599999999999937472239253111183643341064453125,
92.81000000000000227373675443232059478759765625,
92.7300000000000039790393202565610408782958984375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -O3 -march=native"
}
}
},
"c": {
"value": 11953333,
"raw_values": [
11960000,
11970000,
11930000
],
"test_run_times": [
92.68000000000000682121026329696178436279296875,
92.650000000000005684341886080801486968994140625,
92.9200000000000017053025658242404460906982421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -O3 -march=native"
}
}
}
}
},
"a110d5740af9dd951854d42f541e1d01365f586e": {
"identifier": "pts\/quicksilver-1.0.0",
"title": "Quicksilver",
"app_version": "20230818",
"arguments": "..\/Examples\/CORAL2_Benchmark\/Problem2\/Coral2_P2.inp",
"description": "Input: CORAL2 P2",
"scale": "Figure Of Merit",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 22560000,
"test_run_times": [
208.169999999999987494447850622236728668212890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -O3 -march=native"
}
}
},
"b": {
"value": 22713333,
"raw_values": [
22830000,
22800000,
22510000
],
"test_run_times": [
205.729999999999989768184605054557323455810546875,
205.81999999999999317878973670303821563720703125,
208.580000000000012505552149377763271331787109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -O3 -march=native"
}
}
},
"c": {
"value": 22536667,
"raw_values": [
22560000,
22460000,
22590000
],
"test_run_times": [
208.159999999999996589394868351519107818603515625,
209.020000000000010231815394945442676544189453125,
207.81000000000000227373675443232059478759765625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-fopenmp -O3 -march=native"
}
}
}
}
},
"93bc104ddb9a82866ad3ee28e684ab1e91e3076b": {
"identifier": "pts\/speedb-1.0.1",
"title": "Speedb",
"app_version": "2.7",
"arguments": "--benchmarks=\"fillrandom\"",
"description": "Test: Random Fill",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 819366,
"test_run_times": [
60.42999999999999971578290569595992565155029296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 821234,
"raw_values": [
822307,
818224,
823170
],
"test_run_times": [
60.32000000000000028421709430404007434844970703125,
60.49000000000000198951966012828052043914794921875,
60.28999999999999914734871708787977695465087890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"c": {
"value": 818673,
"raw_values": [
813936,
820333,
821750
],
"test_run_times": [
60.36999999999999744204615126363933086395263671875,
60.42999999999999971578290569595992565155029296875,
60.38000000000000255795384873636066913604736328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"757309f598b6fa292b3c923df538e6639d00b732": {
"identifier": "pts\/speedb-1.0.1",
"title": "Speedb",
"app_version": "2.7",
"arguments": "--benchmarks=\"readrandom\"",
"description": "Test: Random Read",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 51459190,
"test_run_times": [
60.10000000000000142108547152020037174224853515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 51062544,
"raw_values": [
50961795,
51127925,
51097913
],
"test_run_times": [
60.10000000000000142108547152020037174224853515625,
60.10000000000000142108547152020037174224853515625,
60.10000000000000142108547152020037174224853515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"c": {
"value": 51108888,
"raw_values": [
51228655,
50959771,
51138237
],
"test_run_times": [
60.1099999999999994315658113919198513031005859375,
60.1099999999999994315658113919198513031005859375,
60.10000000000000142108547152020037174224853515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"5ec248f11366563043c89a66b4fb53d8527b826d": {
"identifier": "pts\/speedb-1.0.1",
"title": "Speedb",
"app_version": "2.7",
"arguments": "--benchmarks=\"updaterandom\"",
"description": "Test: Update Random",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 458594,
"test_run_times": [
60.14999999999999857891452847979962825775146484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 472342,
"raw_values": [
472577,
470780,
473670
],
"test_run_times": [
60.159999999999996589394868351519107818603515625,
60.27000000000000312638803734444081783294677734375,
60.14999999999999857891452847979962825775146484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"c": {
"value": 474392,
"raw_values": [
475589,
476748,
470839
],
"test_run_times": [
60.13000000000000255795384873636066913604736328125,
60.14999999999999857891452847979962825775146484375,
60.28999999999999914734871708787977695465087890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"fbf21e19ecfd4182dbaecc664b2090d6795a1167": {
"identifier": "pts\/speedb-1.0.1",
"title": "Speedb",
"app_version": "2.7",
"arguments": "--benchmarks=\"fillseq\"",
"description": "Test: Sequential Fill",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 933961,
"test_run_times": [
17.32000000000000028421709430404007434844970703125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 935621,
"raw_values": [
940088,
936836,
929939
],
"test_run_times": [
17.21000000000000085265128291212022304534912109375,
17.269999999999999573674358543939888477325439453125,
17.39999999999999857891452847979962825775146484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"c": {
"value": 944900,
"raw_values": [
949826,
938167,
946707
],
"test_run_times": [
17.030000000000001136868377216160297393798828125,
17.230000000000000426325641456060111522674560546875,
17.0799999999999982946974341757595539093017578125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"adf326b1a3adc67d5dab125b2bc476bf918c06e0": {
"identifier": "pts\/speedb-1.0.1",
"title": "Speedb",
"app_version": "2.7",
"arguments": "--benchmarks=\"fillsync\"",
"description": "Test: Random Fill Sync",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 11900,
"test_run_times": [
61.85000000000000142108547152020037174224853515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 6186,
"raw_values": [
11453,
5568,
5755,
3820,
6059,
7305,
4131,
6467,
6212,
5547,
6336,
6071,
6058,
5936,
6065
],
"test_run_times": [
61.8900000000000005684341886080801486968994140625,
71.2699999999999960209606797434389591217041015625,
64.2300000000000039790393202565610408782958984375,
64.31000000000000227373675443232059478759765625,
67.06000000000000227373675443232059478759765625,
64.5499999999999971578290569595992565155029296875,
63.63000000000000255795384873636066913604736328125,
65,
65.7300000000000039790393202565610408782958984375,
65.8299999999999982946974341757595539093017578125,
65.2399999999999948840923025272786617279052734375,
64.7900000000000062527760746888816356658935546875,
65.5799999999999982946974341757595539093017578125,
66.25,
64.8599999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"c": {
"value": 5060,
"raw_values": [
11224,
6288,
3594,
5615,
6052,
5216,
5558,
3738,
5774,
3303,
4020,
4216,
3521,
3783,
4000
],
"test_run_times": [
61.909999999999996589394868351519107818603515625,
67.2699999999999960209606797434389591217041015625,
63.659999999999996589394868351519107818603515625,
63.77000000000000312638803734444081783294677734375,
65.469999999999998863131622783839702606201171875,
65.0199999999999960209606797434389591217041015625,
66.06000000000000227373675443232059478759765625,
64.5199999999999960209606797434389591217041015625,
65.849999999999994315658113919198513031005859375,
63.18999999999999772626324556767940521240234375,
63.8900000000000005684341886080801486968994140625,
65.43000000000000682121026329696178436279296875,
63.82000000000000028421709430404007434844970703125,
63.63000000000000255795384873636066913604736328125,
63.4500000000000028421709430404007434844970703125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"32c4a9e7c95dcd035b29407cebc1edcf994c08a8": {
"identifier": "pts\/speedb-1.0.1",
"title": "Speedb",
"app_version": "2.7",
"arguments": "--benchmarks=\"readwhilewriting\"",
"description": "Test: Read While Writing",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 3035137,
"test_run_times": [
60.1099999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 2842258,
"raw_values": [
2861194,
2793117,
2872462
],
"test_run_times": [
60.25999999999999801048033987171947956085205078125,
60.1099999999999994315658113919198513031005859375,
60.25
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"c": {
"value": 2960839,
"raw_values": [
2975832,
3023563,
2883121
],
"test_run_times": [
60.14999999999999857891452847979962825775146484375,
60.2999999999999971578290569595992565155029296875,
60.13000000000000255795384873636066913604736328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"7d528ef8894f8e807676044900c7eeeb467b17a1": {
"identifier": "pts\/speedb-1.0.1",
"title": "Speedb",
"app_version": "2.7",
"arguments": "--benchmarks=\"readrandomwriterandom\"",
"description": "Test: Read Random Write Random",
"scale": "Op\/s",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 1769691,
"test_run_times": [
60.280000000000001136868377216160297393798828125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"b": {
"value": 1776164,
"raw_values": [
1774322,
1782991,
1771179
],
"test_run_times": [
60.22999999999999687361196265555918216705322265625,
60.11999999999999744204615126363933086395263671875,
60.25999999999999801048033987171947956085205078125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
},
"c": {
"value": 1778569,
"raw_values": [
1779026,
1779263,
1777417
],
"test_run_times": [
60.1400000000000005684341886080801486968994140625,
60.13000000000000255795384873636066913604736328125,
60.159999999999996589394868351519107818603515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread"
}
}
}
}
},
"33a7b90a826a7c6d0fce4559c190319d632d5c8f": {
"identifier": "pts\/tensorflow-2.1.1",
"title": "TensorFlow",
"app_version": "2.12",
"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": {
"a": {
"value": 1.4299999999999999378275106209912337362766265869140625,
"test_run_times": [
79.7300000000000039790393202565610408782958984375
]
},
"b": {
"value": 1.4499999999999999555910790149937383830547332763671875,
"raw_values": [
1.4499999999999999555910790149937383830547332763671875,
1.4499999999999999555910790149937383830547332763671875,
1.439999999999999946709294817992486059665679931640625
],
"test_run_times": [
77.81000000000000227373675443232059478759765625,
78.1299999999999954525264911353588104248046875,
78.1400000000000005684341886080801486968994140625
]
},
"c": {
"value": 1.45999999999999996447286321199499070644378662109375,
"raw_values": [
1.45999999999999996447286321199499070644378662109375,
1.45999999999999996447286321199499070644378662109375,
1.45999999999999996447286321199499070644378662109375
],
"test_run_times": [
77.3599999999999994315658113919198513031005859375,
77.5400000000000062527760746888816356658935546875,
77.4500000000000028421709430404007434844970703125
]
}
}
},
"f7f842cc42f7e1ed869ec6ef2ce0bbeaf19bdfb9": {
"identifier": "pts\/tensorflow-2.1.1",
"title": "TensorFlow",
"app_version": "2.12",
"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": [
25.559999999999998721023075631819665431976318359375
]
},
"b": {
"value": 4.69000000000000039079850466805510222911834716796875,
"raw_values": [
4.69000000000000039079850466805510222911834716796875,
4.67999999999999971578290569595992565155029296875,
4.69000000000000039079850466805510222911834716796875
],
"test_run_times": [
25.120000000000000994759830064140260219573974609375,
25.160000000000000142108547152020037174224853515625,
25.160000000000000142108547152020037174224853515625
]
},
"c": {
"value": 4.70999999999999996447286321199499070644378662109375,
"raw_values": [
4.70000000000000017763568394002504646778106689453125,
4.71999999999999975131004248396493494510650634765625,
4.70000000000000017763568394002504646778106689453125
],
"test_run_times": [
25.03999999999999914734871708787977695465087890625,
24.969999999999998863131622783839702606201171875,
25.050000000000000710542735760100185871124267578125
]
}
}
},
"3fbe75850075f543842076e3c2d8f292f0186e73": {
"identifier": "pts\/tensorflow-2.1.1",
"title": "TensorFlow",
"app_version": "2.12",
"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": {
"a": {
"value": 3.5,
"test_run_times": [
504.92000000000001591615728102624416351318359375
]
},
"b": {
"value": 3.520000000000000017763568394002504646778106689453125,
"raw_values": [
3.520000000000000017763568394002504646778106689453125,
3.520000000000000017763568394002504646778106689453125,
3.529999999999999804600747665972448885440826416015625
],
"test_run_times": [
502.6399999999999863575794734060764312744140625,
502.490000000000009094947017729282379150390625,
501.3799999999999954525264911353588104248046875
]
},
"c": {
"value": 3.54000000000000003552713678800500929355621337890625,
"raw_values": [
3.529999999999999804600747665972448885440826416015625,
3.54000000000000003552713678800500929355621337890625,
3.54000000000000003552713678800500929355621337890625
],
"test_run_times": [
500.1100000000000136424205265939235687255859375,
499.20999999999997953636921010911464691162109375,
499.33999999999997498889570124447345733642578125
]
}
}
},
"af6eaa334bdf76b113725dd052a9c20f8478f446": {
"identifier": "pts\/tensorflow-2.1.1",
"title": "TensorFlow",
"app_version": "2.12",
"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": 40.0499999999999971578290569595992565155029296875,
"test_run_times": [
45.75999999999999801048033987171947956085205078125
]
},
"b": {
"value": 40.340000000000003410605131648480892181396484375,
"raw_values": [
40.3599999999999994315658113919198513031005859375,
40.28999999999999914734871708787977695465087890625,
40.3599999999999994315658113919198513031005859375
],
"test_run_times": [
45.4200000000000017053025658242404460906982421875,
45.5,
45.4200000000000017053025658242404460906982421875
]
},
"c": {
"value": 40.39999999999999857891452847979962825775146484375,
"raw_values": [
40.3599999999999994315658113919198513031005859375,
40.43999999999999772626324556767940521240234375,
40.3900000000000005684341886080801486968994140625
],
"test_run_times": [
45.409999999999996589394868351519107818603515625,
45.35000000000000142108547152020037174224853515625,
45.35000000000000142108547152020037174224853515625
]
}
}
},
"bd5f54a420eb34245418300a8e9ccf0beb3abdc5": {
"identifier": "pts\/tensorflow-2.1.1",
"title": "TensorFlow",
"app_version": "2.12",
"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": 12.1699999999999999289457264239899814128875732421875,
"test_run_times": [
11.660000000000000142108547152020037174224853515625
]
},
"b": {
"value": 12.2200000000000006394884621840901672840118408203125,
"raw_values": [
12.1500000000000003552713678800500929355621337890625,
12.230000000000000426325641456060111522674560546875,
12.269999999999999573674358543939888477325439453125
],
"test_run_times": [
11.6400000000000005684341886080801486968994140625,
11.5800000000000000710542735760100185871124267578125,
11.5600000000000004973799150320701301097869873046875
]
},
"c": {
"value": 12.050000000000000710542735760100185871124267578125,
"raw_values": [
11.699999999999999289457264239899814128875732421875,
12.199999999999999289457264239899814128875732421875,
12.2400000000000002131628207280300557613372802734375
],
"test_run_times": [
12.0099999999999997868371792719699442386627197265625,
11.6099999999999994315658113919198513031005859375,
11.5600000000000004973799150320701301097869873046875
]
}
}
},
"092870ce54d68f9a733b3087de8f6cac555c6faf": {
"identifier": "pts\/tensorflow-2.1.1",
"title": "TensorFlow",
"app_version": "2.12",
"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": 5.089999999999999857891452847979962825775146484375,
"test_run_times": [
25.0799999999999982946974341757595539093017578125
]
},
"b": {
"value": 5.12999999999999989341858963598497211933135986328125,
"raw_values": [
5.12999999999999989341858963598497211933135986328125,
5.13999999999999968025576890795491635799407958984375,
5.12999999999999989341858963598497211933135986328125
],
"test_run_times": [
24.839999999999999857891452847979962825775146484375,
24.8299999999999982946974341757595539093017578125,
24.879999999999999005240169935859739780426025390625
]
},
"c": {
"value": 5.1500000000000003552713678800500929355621337890625,
"raw_values": [
5.160000000000000142108547152020037174224853515625,
5.1500000000000003552713678800500929355621337890625,
5.1500000000000003552713678800500929355621337890625
],
"test_run_times": [
24.739999999999998436805981327779591083526611328125,
24.760000000000001563194018672220408916473388671875,
24.769999999999999573674358543939888477325439453125
]
}
}
},
"8830b09e158de8a9d2b1f8cc75119beba467c9be": {
"identifier": "pts\/tensorflow-2.1.1",
"title": "TensorFlow",
"app_version": "2.12",
"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": 21.120000000000000994759830064140260219573974609375,
"test_run_times": [
86.0499999999999971578290569595992565155029296875
]
},
"b": {
"value": 21.199999999999999289457264239899814128875732421875,
"raw_values": [
21.160000000000000142108547152020037174224853515625,
21.21000000000000085265128291212022304534912109375,
21.219999999999998863131622783839702606201171875
],
"test_run_times": [
85.840000000000003410605131648480892181396484375,
85.68999999999999772626324556767940521240234375,
85.650000000000005684341886080801486968994140625
]
},
"c": {
"value": 21.25,
"raw_values": [
21.230000000000000426325641456060111522674560546875,
21.3299999999999982946974341757595539093017578125,
21.17999999999999971578290569595992565155029296875
],
"test_run_times": [
85.6099999999999994315658113919198513031005859375,
85.2000000000000028421709430404007434844970703125,
85.7900000000000062527760746888816356658935546875
]
}
}
},
"a19a31eae722217497dbf8e872f44816c3fc32f4": {
"identifier": "pts\/tensorflow-2.1.1",
"title": "TensorFlow",
"app_version": "2.12",
"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": 7.589999999999999857891452847979962825775146484375,
"test_run_times": [
235.31999999999999317878973670303821563720703125
]
},
"b": {
"value": 7.6500000000000003552713678800500929355621337890625,
"raw_values": [
7.6500000000000003552713678800500929355621337890625,
7.6500000000000003552713678800500929355621337890625,
7.660000000000000142108547152020037174224853515625
],
"test_run_times": [
233.3799999999999954525264911353588104248046875,
233.539999999999992041921359486877918243408203125,
233.3700000000000045474735088646411895751953125
]
},
"c": {
"value": 7.70000000000000017763568394002504646778106689453125,
"raw_values": [
7.69000000000000039079850466805510222911834716796875,
7.70000000000000017763568394002504646778106689453125,
7.70999999999999996447286321199499070644378662109375
],
"test_run_times": [
232.3700000000000045474735088646411895751953125,
231.979999999999989768184605054557323455810546875,
231.719999999999998863131622783839702606201171875
]
}
}
},
"208ffe3cae17332fa4307ff8cfb139b4f98e2365": {
"identifier": "pts\/y-cruncher-1.4.0",
"title": "Y-Cruncher",
"app_version": "0.8.3",
"arguments": "1b",
"description": "Pi Digits To Calculate: 1B",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 50.423000000000001818989403545856475830078125,
"test_run_times": [
52.93999999999999772626324556767940521240234375
]
},
"b": {
"value": 49.828000000000002955857780762016773223876953125,
"raw_values": [
49.8250000000000028421709430404007434844970703125,
49.840000000000003410605131648480892181396484375,
49.8190000000000026147972675971686840057373046875
],
"test_run_times": [
52.32000000000000028421709430404007434844970703125,
52.31000000000000227373675443232059478759765625,
52.219999999999998863131622783839702606201171875
]
},
"c": {
"value": 49.804000000000002046363078989088535308837890625,
"raw_values": [
49.81099999999999994315658113919198513031005859375,
49.74000000000000198951966012828052043914794921875,
49.86200000000000187583282240666449069976806640625
],
"test_run_times": [
52.27000000000000312638803734444081783294677734375,
52.1099999999999994315658113919198513031005859375,
52.24000000000000198951966012828052043914794921875
]
}
}
},
"680600dd10eb2d9f2993de9d934395e96f50622e": {
"identifier": "pts\/y-cruncher-1.4.0",
"title": "Y-Cruncher",
"app_version": "0.8.3",
"arguments": "500m",
"description": "Pi Digits To Calculate: 500M",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 23.263000000000001676880856393836438655853271484375,
"test_run_times": [
24.739999999999998436805981327779591083526611328125
]
},
"b": {
"value": 23.077000000000001733724275254644453525543212890625,
"raw_values": [
23.050999999999998379962562466971576213836669921875,
23.032000000000000028421709430404007434844970703125,
23.1490000000000009094947017729282379150390625
],
"test_run_times": [
24.489999999999998436805981327779591083526611328125,
24.510000000000001563194018672220408916473388671875,
24.5799999999999982946974341757595539093017578125
]
},
"c": {
"value": 22.89399999999999835154085303656756877899169921875,
"raw_values": [
22.876000000000001222133505507372319698333740234375,
22.876000000000001222133505507372319698333740234375,
22.928999999999998493649400188587605953216552734375
],
"test_run_times": [
24.32000000000000028421709430404007434844970703125,
24.3299999999999982946974341757595539093017578125,
24.379999999999999005240169935859739780426025390625
]
}
}
}
}
}