3950X Sep

AMD Ryzen 9 3950X 16-Core testing with a ASUS ROG CROSSHAIR VII HERO (WI-FI) (3103 BIOS) and Sapphire AMD Radeon RX 470 4GB on Ubuntu 22.04 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 2209044-NE-3950XSEP507
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A
September 03 2022
  1 Hour, 56 Minutes
B
September 03 2022
  2 Hours, 15 Minutes
C
September 03 2022
  2 Hours, 17 Minutes
D
September 03 2022
  2 Hours, 18 Minutes
E
September 03 2022
  13 Hours, 13 Minutes
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  4 Hours, 24 Minutes

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3950X SepOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 3950X 16-Core @ 3.50GHz (16 Cores)ASUS ROG CROSSHAIR VII HERO (WI-FI) (3103 BIOS)AMD Starship/Matisse16GBSamsung SSD 970 EVO 250GBSapphire AMD Radeon RX 470 4GB (1260/1750MHz)AMD Ellesmere HDMI AudioDELL S2409WIntel I211 + Realtek RTL8822BE 802.11a/b/g/n/acUbuntu 22.045.19.0-051900daily20220813-generic (x86_64)GNOME Shell 42.2X Server + Wayland4.6 Mesa 22.0.5 (LLVM 13.0.1 DRM 3.48)1.3.204GCC 11.2.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen Resolution3950X Sep BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-gBFGDP/gcc-11-11.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-gBFGDP/gcc-11-11.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - NONE / errors=remount-ro,relatime,rw / Block Size: 4096- Scaling Governor: acpi-cpufreq schedutil (Boost: Enabled) - CPU Microcode: 0x8701021 - Python 3.10.4- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of IBPB + 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: always-on STIBP: forced RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

ABCDEResult OverviewPhoronix Test Suite100%116%132%148%etcdNatronMobile Neural Network7-Zip CompressionTimed PHP CompilationTimed Erlang/OTP CompilationGraphicsMagickC-BloscUnpacking The Linux KernelOpenVINOTimed Wasmer CompilationTimed CPython CompilationTimed Node.js Compilation

3950X Sepetcd: RANGE - 50 - 100 - Average Latencyetcd: RANGE - 50 - 100etcd: PUT - 500 - 100 - Average Latencyetcd: PUT - 500 - 100etcd: RANGE - 100 - 100 - Average Latencyetcd: PUT - 100 - 100 - Average Latencyetcd: RANGE - 100 - 100etcd: PUT - 50 - 100 - Average Latencyetcd: PUT - 100 - 100etcd: PUT - 50 - 100etcd: RANGE - 500 - 100etcd: RANGE - 500 - 100 - Average Latencyetcd: RANGE - 500 - 1000 - Average Latencyetcd: RANGE - 500 - 1000etcd: PUT - 500 - 1000 - Average Latencyetcd: PUT - 500 - 1000etcd: PUT - 50 - 1000 - Average Latencymnn: SqueezeNetV1.0openvino: Vehicle Detection FP16 - CPUmnn: squeezenetv1.1openvino: Vehicle Detection FP16 - CPUmnn: MobileNetV2_224compress-7zip: Compression Ratingmnn: mobilenetV3mnn: nasnetopenvino: Person Detection FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUopenvino: Machine Translation EN To DE FP16 - CPUgraphics-magick: Rotateopenvino: Face Detection FP16 - CPUopenvino: Person Detection FP32 - CPUopenvino: Person Detection FP16 - CPUmnn: resnet-v2-50graphics-magick: Resizingopenvino: Person Detection FP32 - CPUgraphics-magick: HWB Color Spaceopenvino: Age Gender Recognition Retail 0013 FP16 - CPUblosc: blosclz shufflemnn: inception-v3build-erlang: Time To Compileopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUbuild-php: Time To Compileopenvino: Face Detection FP16 - CPUgraphics-magick: Swirlbuild-python: Released Build, PGO + LTO Optimizedgraphics-magick: Sharpenopenvino: Age Gender Recognition Retail 0013 FP16 - CPUblosc: blosclz bitshuffleopenvino: Vehicle Detection FP16-INT8 - CPUopenvino: Vehicle Detection FP16-INT8 - CPUunpack-linux: linux-5.19.tar.xzmnn: mobilenet-v1-1.0openvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16-INT8 - CPUopenvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPUgraphics-magick: Enhancedopenvino: Face Detection FP16-INT8 - CPUbuild-wasmer: Time To Compileopenvino: Face Detection FP16-INT8 - CPUopenvino: Weld Porosity Detection FP16 - CPUopenvino: Weld Porosity Detection FP16 - CPUcompress-7zip: Decompression Ratinggraphics-magick: Noise-Gaussianbuild-nodejs: Time To Compilebuild-python: Defaultopenvino: Person Vehicle Bike Detection FP16 - CPUopenvino: Person Vehicle Bike Detection FP16 - CPUnatron: Spaceshipetcd: RANGE - 100 - 1000 - Average Latencyetcd: RANGE - 100 - 1000etcd: RANGE - 50 - 1000 - Average Latencyetcd: RANGE - 50 - 1000etcd: PUT - 100 - 1000 - Average Latencyetcd: PUT - 100 - 1000etcd: PUT - 50 - 1000ABCDE3.330099.58133.329940.61613.73.326866.57593.329893.434230093.385818991.52395.314.865917.241214.766273.0768115.421351.333.37911.373.592842052.01312.9782.37110.0136.324681258.341659.891668.8520.17716882.3972910973.6714794.427.847111.9391.0160.3783.16659272.5782511.4410091.19.13437.737.6982.698570.8128.0115767.85364695.5257.3525.74321.7812.4175100290497.1918.361504.467.923.311.784607.34371190098.199511.685435.511190351.73066.216178.2496.116446.37866.2616165.5907616572.280116614.853516096.47416.214.865709.454114.865970.609911.15.566343.853.37411.613.571823502.00613.0612.38110.9236.044631255.921637.811661.5320.06416742.4272211065.9614622.127.608112.06160.6273.16657272.3582511.4310039.29.14397.6822.692572.4127.9215826.05363693.7857.3175.76321.1812.4374832289497.08118.414503.247.933.411.784592.90721189816.411911.784546.061289723.13166.315954.55576.315901.95266.26.316010.01466.315915.464515974.855215859.12486.314.865751.575214.865829.2852115.401344.153.27911.63.542832911.97112.7982.39110.8436.064611271.041641.561663.2620.32116842.4172211106.2414763.627.76112.666160.573.14658272.8032511.4310074.19.09439.427.6532.7572.8427.9115841.7364692.657.325.77321.3812.4275045289495.67418.379504.037.923.311.684946.78541189932.694411.684943.4389853.1686.415613.65856.415561.35946.46.415511.56426.415687.981615721.313215521.42516.414.865750.654614.865753.482311.15.541344.263.3711.63.508840962.01413.0572.41110.5536.154621274.451643.311645.120.06916732.4272311031.8414684.227.825113.131160.493.13657272.4892511.4410053.49.1438.997.6752.69572.1927.9415834.93363693.8357.6185.76321.9912.474994289496.20418.366504.367.923.411.784795.25441190539.598811.784669.789289674.36127.413528.95826.615135.46517.36.513662.18316.415439.577715591.583512552.82918.020.547997.950618.852164.511413.75.380340.863.31211.713.506834731.97212.8102.39111.7935.754611269.031661.551654.2920.03216662.3972011013.0814626.627.527112.5941.0160.0393.14653274.5852491.4410021.89.15436.567.6482.683569.2528.0815751.27362696.4057.3535.74320.4112.4674898289496.36618.387503.157.943.318.155692.008417.557913.176816.062573.154672969.6471OpenBenchmarking.org

etcd

Etcd is a distributed, reliable key-value store intended for critical data of a distributed system. Etcd is written in Golang and part of the Cloud Native Computing Foundation (CNCF) and used by Kubernetes, Rook, CoreDNS, and other open-source software. This test profile uses Etcd's built-in benchmark to stress the PUT and RANGE performance of a single node / local system. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: RANGE - Connections: 50 - Clients: 100 - Average LatencyABCDE246810SE +/- 0.07, N = 73.36.26.36.47.4

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: RANGE - Connections: 50 - Clients: 100ABCDE6K12K18K24K30KSE +/- 119.86, N = 730099.5816178.2515954.5615613.6613528.96

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: PUT - Connections: 500 - Clients: 100 - Average LatencyABCDE246810SE +/- 0.07, N = 63.36.16.36.46.6

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: PUT - Connections: 500 - Clients: 100ABCDE6K12K18K24K30KSE +/- 148.13, N = 629940.6216446.3815901.9515561.3615135.47

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: RANGE - Connections: 100 - Clients: 100 - Average LatencyABCDE246810SE +/- 0.11, N = 93.76.26.26.47.3

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: PUT - Connections: 100 - Clients: 100 - Average LatencyABCDE246810SE +/- 0.00, N = 33.36.06.36.46.5

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: RANGE - Connections: 100 - Clients: 100ABCDE6K12K18K24K30KSE +/- 215.62, N = 926866.5816165.5916010.0115511.5613662.18

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: PUT - Connections: 50 - Clients: 100 - Average LatencyABCDE246810SE +/- 0.00, N = 33.36.06.36.46.4

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: PUT - Connections: 100 - Clients: 100ABCDE6K12K18K24K30KSE +/- 18.08, N = 329893.4316572.2815915.4615687.9815439.58

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: PUT - Connections: 50 - Clients: 100ABCDE6K12K18K24K30KSE +/- 9.73, N = 330093.3916614.8515974.8615721.3115591.58

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: RANGE - Connections: 500 - Clients: 100ABCDE4K8K12K16K20KSE +/- 112.68, N = 718991.5216096.4715859.1215521.4312552.83

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: RANGE - Connections: 500 - Clients: 100 - Average LatencyABCDE246810SE +/- 0.08, N = 75.36.26.36.48.0

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: RANGE - Connections: 500 - Clients: 1000 - Average LatencyABCDE510152025SE +/- 0.14, N = 1514.814.814.814.820.5

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: RANGE - Connections: 500 - Clients: 1000ABCDE14K28K42K56K70KSE +/- 337.08, N = 1565917.2465709.4565751.5865750.6547997.95

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: PUT - Connections: 500 - Clients: 1000 - Average LatencyABCDE510152025SE +/- 0.21, N = 1514.714.814.814.818.8

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: PUT - Connections: 500 - Clients: 1000ABCDE14K28K42K56K70KSE +/- 625.45, N = 1566273.0865970.6165829.2965753.4852164.51

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: PUT - Connections: 50 - Clients: 1000 - Average LatencyABCDE48121620SE +/- 0.21, N = 1511.011.111.011.113.7

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: SqueezeNetV1.0ABCDE1.25242.50483.75725.00966.262SE +/- 0.019, N = 35.4215.5665.4015.5415.380MIN: 5.35 / MAX: 21.72MIN: 5.51 / MAX: 6.67MIN: 5.35 / MAX: 6.22MIN: 5.49 / MAX: 6.76MIN: 5.3 / MAX: 6.521. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16 - Device: CPUABCDE80160240320400SE +/- 2.43, N = 3351.33343.85344.15344.26340.861. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: squeezenetv1.1ABCDE0.76031.52062.28093.04123.8015SE +/- 0.008, N = 33.3793.3743.2793.3703.312MIN: 3.34 / MAX: 4.37MIN: 3.33 / MAX: 4.48MIN: 3.24 / MAX: 4.29MIN: 3.32 / MAX: 4.47MIN: 3.26 / MAX: 4.421. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16 - Device: CPUABCDE3691215SE +/- 0.08, N = 311.3711.6111.6011.6011.71MIN: 10.52 / MAX: 21.67MIN: 10.6 / MAX: 28.3MIN: 10.53 / MAX: 23.08MIN: 10.66 / MAX: 22.12MIN: 10.26 / MAX: 21.141. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: MobileNetV2_224ABCDE0.80821.61642.42463.23284.041SE +/- 0.022, N = 33.5923.5713.5423.5083.506MIN: 3.55 / MAX: 6.84MIN: 3.53 / MAX: 4.69MIN: 3.5 / MAX: 5.07MIN: 3.47 / MAX: 4.6MIN: 3.44 / MAX: 9.591. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

7-Zip Compression

This is a test of 7-Zip compression/decompression with its integrated benchmark feature. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Compression RatingABCDE20K40K60K80K100KSE +/- 30.72, N = 384205823508329184096834731. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: mobilenetV3ABCDE0.45320.90641.35961.81282.266SE +/- 0.009, N = 32.0132.0061.9712.0141.972MIN: 1.99 / MAX: 3.11MIN: 1.98 / MAX: 2.75MIN: 1.94 / MAX: 3.07MIN: 1.99 / MAX: 2.25MIN: 1.93 / MAX: 3.061. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: nasnetABCDE3691215SE +/- 0.02, N = 312.9813.0612.8013.0612.81MIN: 12.88 / MAX: 19.14MIN: 12.97 / MAX: 19.07MIN: 12.68 / MAX: 19.17MIN: 12.94 / MAX: 19.32MIN: 12.68 / MAX: 30.811. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Person Detection FP16 - Device: CPUABCDE0.54231.08461.62692.16922.7115SE +/- 0.01, N = 32.372.382.392.412.391. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Machine Translation EN To DE FP16 - Device: CPUABCDE306090120150SE +/- 0.33, N = 3110.01110.92110.84110.55111.79MIN: 85.11 / MAX: 135.51MIN: 92.03 / MAX: 133.28MIN: 84.72 / MAX: 133.04MIN: 89.56 / MAX: 138.28MIN: 86.68 / MAX: 133.951. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Machine Translation EN To DE FP16 - Device: CPUABCDE816243240SE +/- 0.10, N = 336.3236.0436.0636.1535.751. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

GraphicsMagick

This is a test of GraphicsMagick with its OpenMP implementation that performs various imaging tests on a sample 6000x4000 pixel JPEG image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.38Operation: RotateABCDE100200300400500SE +/- 0.33, N = 34684634614624611. (CC) gcc options: -fopenmp -O2 -ljbig -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Face Detection FP16 - Device: CPUABCDE30060090012001500SE +/- 1.95, N = 31258.341255.921271.041274.451269.03MIN: 1201.93 / MAX: 1341.23MIN: 1206.49 / MAX: 1356.42MIN: 1241.13 / MAX: 1380.49MIN: 1226.87 / MAX: 1355.68MIN: 1210.75 / MAX: 1378.291. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Person Detection FP32 - Device: CPUABCDE400800120016002000SE +/- 11.54, N = 31659.891637.811641.561643.311661.55MIN: 1461.24 / MAX: 1823.91MIN: 1490.45 / MAX: 1850.31MIN: 1477.93 / MAX: 1797.33MIN: 1495.03 / MAX: 1843.12MIN: 1464.72 / MAX: 1861.451. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Person Detection FP16 - Device: CPUABCDE400800120016002000SE +/- 9.27, N = 31668.851661.531663.261645.101654.29MIN: 1447.91 / MAX: 1780.07MIN: 1480.92 / MAX: 1803.33MIN: 1482.48 / MAX: 1805.04MIN: 1489.68 / MAX: 1839.49MIN: 1481.86 / MAX: 1868.971. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: resnet-v2-50ABCDE510152025SE +/- 0.07, N = 320.1820.0620.3220.0720.03MIN: 19.89 / MAX: 26.06MIN: 19.82 / MAX: 36.51MIN: 20.04 / MAX: 36.83MIN: 19.84 / MAX: 34.96MIN: 19.6 / MAX: 34.61. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

GraphicsMagick

This is a test of GraphicsMagick with its OpenMP implementation that performs various imaging tests on a sample 6000x4000 pixel JPEG image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.38Operation: ResizingABCDE400800120016002000SE +/- 3.67, N = 3168816741684167316661. (CC) gcc options: -fopenmp -O2 -ljbig -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Person Detection FP32 - Device: CPUABCDE0.54451.0891.63352.1782.7225SE +/- 0.02, N = 32.392.422.412.422.391. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

GraphicsMagick

This is a test of GraphicsMagick with its OpenMP implementation that performs various imaging tests on a sample 6000x4000 pixel JPEG image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.38Operation: HWB Color SpaceABCDE160320480640800SE +/- 0.58, N = 37297227227237201. (CC) gcc options: -fopenmp -O2 -ljbig -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16 - Device: CPUABCDE2K4K6K8K10KSE +/- 33.81, N = 310973.6711065.9611106.2411031.8411013.081. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

C-Blosc

C-Blosc (c-blosc2) simple, compressed, fast and persistent data store library for C. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterC-Blosc 2.3Test: blosclz shuffleABCDE3K6K9K12K15KSE +/- 39.75, N = 314794.414622.114763.614684.214626.61. (CC) gcc options: -std=gnu99 -O3 -lrt -lm

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: inception-v3ABCDE714212835SE +/- 0.09, N = 327.8527.6127.7627.8327.53MIN: 27.42 / MAX: 33.72MIN: 27.19 / MAX: 34.67MIN: 27.3 / MAX: 72.79MIN: 27.33 / MAX: 33.14MIN: 27.08 / MAX: 47.121. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

Timed Erlang/OTP Compilation

This test times how long it takes to compile Erlang/OTP. Erlang is a programming language and run-time for massively scalable soft real-time systems with high availability requirements. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Erlang/OTP Compilation 25.0Time To CompileABCDE306090120150SE +/- 0.20, N = 3111.94112.06112.67113.13112.59

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUABCDE0.22730.45460.68190.90921.1365SE +/- 0.00, N = 31.011.001.001.001.01MIN: 0.95 / MAX: 7.42MIN: 0.95 / MAX: 7.42MIN: 0.95 / MAX: 7.16MIN: 0.95 / MAX: 5.25MIN: 0.95 / MAX: 17.361. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

Timed PHP Compilation

This test times how long it takes to build PHP. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed PHP Compilation 8.1.9Time To CompileABCDE1428425670SE +/- 0.22, N = 360.3860.6360.5760.4960.04

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Face Detection FP16 - Device: CPUABCDE0.7111.4222.1332.8443.555SE +/- 0.00, N = 33.163.163.143.133.141. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

GraphicsMagick

This is a test of GraphicsMagick with its OpenMP implementation that performs various imaging tests on a sample 6000x4000 pixel JPEG image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.38Operation: SwirlABCDE140280420560700SE +/- 1.20, N = 36596576586576531. (CC) gcc options: -fopenmp -O2 -ljbig -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread

Timed CPython Compilation

This test times how long it takes to build the reference Python implementation, CPython, with optimizations and LTO enabled for a release build. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed CPython Compilation 3.10.6Build Configuration: Released Build, PGO + LTO OptimizedABCDE60120180240300272.58272.36272.80272.49274.59

GraphicsMagick

This is a test of GraphicsMagick with its OpenMP implementation that performs various imaging tests on a sample 6000x4000 pixel JPEG image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.38Operation: SharpenABCDE50100150200250SE +/- 0.67, N = 32512512512512491. (CC) gcc options: -fopenmp -O2 -ljbig -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16 - Device: CPUABCDE0.3240.6480.9721.2961.62SE +/- 0.00, N = 31.441.431.431.441.44MIN: 1.23 / MAX: 17.9MIN: 1.27 / MAX: 18.12MIN: 1.25 / MAX: 17.38MIN: 1.27 / MAX: 18.07MIN: 1.26 / MAX: 17.81. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

C-Blosc

C-Blosc (c-blosc2) simple, compressed, fast and persistent data store library for C. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterC-Blosc 2.3Test: blosclz bitshuffleABCDE2K4K6K8K10KSE +/- 4.68, N = 310091.110039.210074.110053.410021.81. (CC) gcc options: -std=gnu99 -O3 -lrt -lm

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUABCDE3691215SE +/- 0.01, N = 39.139.109.099.109.15MIN: 8.85 / MAX: 16.16MIN: 8.83 / MAX: 15.74MIN: 8.83 / MAX: 25.56MIN: 8.85 / MAX: 25.66MIN: 8.87 / MAX: 26.461. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Vehicle Detection FP16-INT8 - Device: CPUABCDE100200300400500SE +/- 0.31, N = 3437.73439.00439.42438.99436.561. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

Unpacking The Linux Kernel

This test measures how long it takes to extract the .tar.xz Linux kernel source tree package. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterUnpacking The Linux Kernel 5.19linux-5.19.tar.xzABCDE246810SE +/- 0.009, N = 47.6987.6827.6537.6757.648

Mobile Neural Network

MNN is the Mobile Neural Network as a highly efficient, lightweight deep learning framework developed by Alibaba. This MNN test profile is building the OpenMP / CPU threaded version for processor benchmarking and not any GPU-accelerated test. MNN does allow making use of AVX-512 extensions. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.1Model: mobilenet-v1-1.0ABCDE0.60751.2151.82252.433.0375SE +/- 0.024, N = 32.6982.6922.7002.6902.683MIN: 2.66 / MAX: 3.73MIN: 2.65 / MAX: 3.77MIN: 2.66 / MAX: 3.68MIN: 2.65 / MAX: 3.76MIN: 2.61 / MAX: 3.751. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -rdynamic -pthread -ldl

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUABCDE120240360480600SE +/- 0.37, N = 3570.81572.41572.84572.19569.251. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16-INT8 - Device: CPUABCDE714212835SE +/- 0.02, N = 328.0127.9227.9127.9428.08MIN: 27.19 / MAX: 33.76MIN: 27.09 / MAX: 44.07MIN: 27.1 / MAX: 34.12MIN: 27.08 / MAX: 44.05MIN: 27.25 / MAX: 44.191. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPUABCDE3K6K9K12K15KSE +/- 1.59, N = 315767.8515826.0515841.7015834.9315751.271. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

GraphicsMagick

This is a test of GraphicsMagick with its OpenMP implementation that performs various imaging tests on a sample 6000x4000 pixel JPEG image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.38Operation: EnhancedABCDE80160240320400SE +/- 0.33, N = 33643633643633621. (CC) gcc options: -fopenmp -O2 -ljbig -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Face Detection FP16-INT8 - Device: CPUABCDE150300450600750SE +/- 0.32, N = 3695.52693.78692.60693.83696.40MIN: 691.3 / MAX: 708.41MIN: 686.88 / MAX: 717.7MIN: 686.95 / MAX: 699.35MIN: 684.96 / MAX: 701.04MIN: 688.69 / MAX: 721.061. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

Timed Wasmer Compilation

This test times how long it takes to compile Wasmer. Wasmer is written in the Rust programming language and is a WebAssembly runtime implementation that supports WASI and EmScripten. This test profile builds Wasmer with the Cranelift and Singlepast compiler features enabled. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Wasmer Compilation 2.3Time To CompileABCDE1326395265SE +/- 0.11, N = 357.3557.3257.3257.6257.351. (CC) gcc options: -m64 -ldl -lgcc_s -lutil -lrt -lpthread -lm -lc -pie -nodefaultlibs

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Face Detection FP16-INT8 - Device: CPUABCDE1.29832.59663.89495.19326.4915SE +/- 0.00, N = 35.745.765.775.765.741. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16 - Device: CPUABCDE70140210280350SE +/- 0.08, N = 3321.78321.18321.38321.99320.411. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Weld Porosity Detection FP16 - Device: CPUABCDE3691215SE +/- 0.00, N = 312.4112.4312.4212.4012.46MIN: 10.44 / MAX: 22.3MIN: 10.42 / MAX: 17.91MIN: 10.48 / MAX: 15.98MIN: 10.39 / MAX: 18.88MIN: 10.39 / MAX: 27.741. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

7-Zip Compression

This is a test of 7-Zip compression/decompression with its integrated benchmark feature. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMIPS, More Is Better7-Zip Compression 22.01Test: Decompression RatingABCDE16K32K48K64K80KSE +/- 23.02, N = 375100748327504574994748981. (CXX) g++ options: -lpthread -ldl -O2 -fPIC

GraphicsMagick

This is a test of GraphicsMagick with its OpenMP implementation that performs various imaging tests on a sample 6000x4000 pixel JPEG image. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgIterations Per Minute, More Is BetterGraphicsMagick 1.3.38Operation: Noise-GaussianABCDE60120180240300SE +/- 0.33, N = 32902892892892891. (CC) gcc options: -fopenmp -O2 -ljbig -ltiff -lfreetype -ljpeg -lXext -lSM -lICE -lX11 -llzma -lbz2 -lxml2 -lz -lm -lpthread

Timed Node.js Compilation

This test profile times how long it takes to build/compile Node.js itself from source. Node.js is a JavaScript run-time built from the Chrome V8 JavaScript engine while itself is written in C/C++. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Node.js Compilation 18.8Time To CompileABCDE110220330440550SE +/- 0.12, N = 3497.19497.08495.67496.20496.37

Timed CPython Compilation

This test times how long it takes to build the reference Python implementation, CPython, with optimizations and LTO enabled for a release build. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed CPython Compilation 3.10.6Build Configuration: DefaultABCDE51015202518.3618.4118.3818.3718.39

OpenVINO

This is a test of the Intel OpenVINO, a toolkit around neural networks, using its built-in benchmarking support and analyzing the throughput and latency for various models. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterOpenVINO 2022.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUABCDE110220330440550SE +/- 0.63, N = 3504.46503.24504.03504.36503.151. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

OpenBenchmarking.orgms, Fewer Is BetterOpenVINO 2022.2.devModel: Person Vehicle Bike Detection FP16 - Device: CPUABCDE246810SE +/- 0.01, N = 37.927.937.927.927.94MIN: 7.59 / MAX: 24.31MIN: 7.45 / MAX: 12.66MIN: 7.6 / MAX: 12.54MIN: 7.52 / MAX: 15.54MIN: 7.58 / MAX: 38.471. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -flto -shared

Natron

Natron is an open-source, cross-platform compositing software for visual effects (VFX) and motion graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterNatron 2.4.3Input: SpaceshipABCDE0.7651.532.2953.063.825SE +/- 0.06, N = 123.33.43.33.43.3

etcd

Etcd is a distributed, reliable key-value store intended for critical data of a distributed system. Etcd is written in Golang and part of the Cloud Native Computing Foundation (CNCF) and used by Kubernetes, Rook, CoreDNS, and other open-source software. This test profile uses Etcd's built-in benchmark to stress the PUT and RANGE performance of a single node / local system. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: RANGE - Connections: 100 - Clients: 1000 - Average LatencyABCDE48121620SE +/- 0.46, N = 1511.711.711.611.718.1

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: RANGE - Connections: 100 - Clients: 1000ABCDE20K40K60K80K100KSE +/- 1989.42, N = 1584607.3484592.9184946.7984795.2555692.01

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: RANGE - Connections: 50 - Clients: 1000 - Average LatencyABCDE48121620SE +/- 0.51, N = 1511.011.011.011.017.5

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: RANGE - Connections: 50 - Clients: 1000ABCDE20K40K60K80K100KSE +/- 2395.30, N = 1590098.2089816.4189932.6990539.6057913.18

OpenBenchmarking.orgms, Fewer Is Betteretcd 3.5.4Test: PUT - Connections: 100 - Clients: 1000 - Average LatencyABCDE48121620SE +/- 0.35, N = 1511.611.711.611.716.0

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: PUT - Connections: 100 - Clients: 1000ABCDE20K40K60K80K100KSE +/- 1719.86, N = 1585435.5184546.0684943.4384669.7962573.15

OpenBenchmarking.orgRequests/sec, More Is Betteretcd 3.5.4Test: PUT - Connections: 50 - Clients: 1000ABCDE20K40K60K80K100KSE +/- 1306.71, N = 1590351.7389723.1389853.1789674.3672969.65

75 Results Shown

etcd:
  RANGE - 50 - 100 - Average Latency
  RANGE - 50 - 100
  PUT - 500 - 100 - Average Latency
  PUT - 500 - 100
  RANGE - 100 - 100 - Average Latency
  PUT - 100 - 100 - Average Latency
  RANGE - 100 - 100
  PUT - 50 - 100 - Average Latency
  PUT - 100 - 100
  PUT - 50 - 100
  RANGE - 500 - 100
  RANGE - 500 - 100 - Average Latency
  RANGE - 500 - 1000 - Average Latency
  RANGE - 500 - 1000
  PUT - 500 - 1000 - Average Latency
  PUT - 500 - 1000
  PUT - 50 - 1000 - Average Latency
Mobile Neural Network
OpenVINO
Mobile Neural Network
OpenVINO
Mobile Neural Network
7-Zip Compression
Mobile Neural Network:
  mobilenetV3
  nasnet
OpenVINO:
  Person Detection FP16 - CPU
  Machine Translation EN To DE FP16 - CPU
  Machine Translation EN To DE FP16 - CPU
GraphicsMagick
OpenVINO:
  Face Detection FP16 - CPU
  Person Detection FP32 - CPU
  Person Detection FP16 - CPU
Mobile Neural Network
GraphicsMagick
OpenVINO
GraphicsMagick
OpenVINO
C-Blosc
Mobile Neural Network
Timed Erlang/OTP Compilation
OpenVINO
Timed PHP Compilation
OpenVINO
GraphicsMagick
Timed CPython Compilation
GraphicsMagick
OpenVINO
C-Blosc
OpenVINO:
  Vehicle Detection FP16-INT8 - CPU:
    ms
    FPS
Unpacking The Linux Kernel
Mobile Neural Network
OpenVINO:
  Weld Porosity Detection FP16-INT8 - CPU:
    FPS
    ms
  Age Gender Recognition Retail 0013 FP16-INT8 - CPU:
    FPS
GraphicsMagick
OpenVINO
Timed Wasmer Compilation
OpenVINO:
  Face Detection FP16-INT8 - CPU
  Weld Porosity Detection FP16 - CPU
  Weld Porosity Detection FP16 - CPU
7-Zip Compression
GraphicsMagick
Timed Node.js Compilation
Timed CPython Compilation
OpenVINO:
  Person Vehicle Bike Detection FP16 - CPU:
    FPS
    ms
Natron
etcd:
  RANGE - 100 - 1000 - Average Latency
  RANGE - 100 - 1000
  RANGE - 50 - 1000 - Average Latency
  RANGE - 50 - 1000
  PUT - 100 - 1000 - Average Latency
  PUT - 100 - 1000
  PUT - 50 - 1000