christmas comet Intel Core i7-10700T testing with a Logic Supply RXM-181 (Z01-0002A026 BIOS) and Intel UHD 630 CML GT2 30GB on Ubuntu 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2212231-NE-CHRISTMAS95&sor .
christmas comet Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server OpenGL OpenCL Vulkan Compiler File-System Screen Resolution a b c Intel Core i7-10700T @ 4.50GHz (8 Cores / 16 Threads) Logic Supply RXM-181 (Z01-0002A026 BIOS) Intel Comet Lake PCH 32GB 256GB TS256GMTS800 Intel UHD 630 CML GT2 30GB (1200MHz) Realtek ALC233 DELL P2415Q Intel I219-LM + Intel I210 Ubuntu 22.04 5.15.0-52-generic (x86_64) GNOME Shell 42.2 X Server + Wayland 4.6 Mesa 22.0.1 OpenCL 3.0 1.3.204 GCC 11.3.0 ext4 1920x1080 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --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-xKiWfi/gcc-11-11.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-xKiWfi/gcc-11-11.3.0/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 Processor Details - Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xf0 - Thermald 2.4.9 Python Details - Python 3.10.6 Security Details - itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Mitigation of Enhanced IBRS + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Mitigation of Microcode + tsx_async_abort: Not affected
christmas comet fluidx3d: FP32-FP32 fluidx3d: FP32-FP16C fluidx3d: FP32-FP16S nekrs: TurboPipe Periodic rav1e: 1 rav1e: 5 rav1e: 6 rav1e: 10 svt-av1: Preset 4 - Bosphorus 4K svt-av1: Preset 8 - Bosphorus 4K svt-av1: Preset 12 - Bosphorus 4K svt-av1: Preset 13 - Bosphorus 4K svt-av1: Preset 4 - Bosphorus 1080p svt-av1: Preset 8 - Bosphorus 1080p svt-av1: Preset 12 - Bosphorus 1080p svt-av1: Preset 13 - Bosphorus 1080p openvkl: vklBenchmark ISPC openvkl: vklBenchmark Scalar stargate: 44100 - 512 stargate: 96000 - 512 stargate: 192000 - 512 stargate: 44100 - 1024 stargate: 480000 - 512 stargate: 96000 - 1024 stargate: 192000 - 1024 stargate: 480000 - 1024 build-linux-kernel: defconfig build-linux-kernel: allmodconfig onednn: IP Shapes 1D - f32 - CPU onednn: IP Shapes 3D - f32 - CPU onednn: IP Shapes 1D - u8s8f32 - CPU onednn: IP Shapes 3D - u8s8f32 - CPU onednn: Convolution Batch Shapes Auto - f32 - CPU onednn: Deconvolution Batch shapes_1d - f32 - CPU onednn: Deconvolution Batch shapes_3d - f32 - CPU onednn: Convolution Batch Shapes Auto - u8s8f32 - CPU onednn: Deconvolution Batch shapes_1d - u8s8f32 - CPU onednn: Deconvolution Batch shapes_3d - u8s8f32 - CPU onednn: Recurrent Neural Network Training - f32 - CPU onednn: Recurrent Neural Network Inference - f32 - CPU onednn: Recurrent Neural Network Training - u8s8f32 - CPU onednn: Recurrent Neural Network Inference - u8s8f32 - CPU onednn: Matrix Multiply Batch Shapes Transformer - f32 - CPU onednn: Recurrent Neural Network Training - bf16bf16bf16 - CPU onednn: Recurrent Neural Network Inference - bf16bf16bf16 - CPU onednn: Matrix Multiply Batch Shapes Transformer - u8s8f32 - CPU cockroach: MoVR - 128 cockroach: MoVR - 256 cockroach: MoVR - 512 cockroach: MoVR - 1024 cockroach: KV, 10% Reads - 128 cockroach: KV, 10% Reads - 256 cockroach: KV, 10% Reads - 512 cockroach: KV, 50% Reads - 128 cockroach: KV, 50% Reads - 256 cockroach: KV, 50% Reads - 512 cockroach: KV, 60% Reads - 128 cockroach: KV, 60% Reads - 256 cockroach: KV, 60% Reads - 512 cockroach: KV, 95% Reads - 128 cockroach: KV, 95% Reads - 256 cockroach: KV, 95% Reads - 512 cockroach: KV, 10% Reads - 1024 cockroach: KV, 50% Reads - 1024 cockroach: KV, 60% Reads - 1024 cockroach: KV, 95% Reads - 1024 blender: BMW27 - CPU-Only blender: Classroom - CPU-Only blender: Fishy Cat - CPU-Only blender: Barbershop - CPU-Only blender: Pabellon Barcelona - CPU-Only openvino: Face Detection FP16 - CPU openvino: Face Detection FP16 - CPU openvino: Person Detection FP16 - CPU openvino: Person Detection FP16 - CPU openvino: Person Detection FP32 - CPU openvino: Person Detection FP32 - CPU openvino: Vehicle Detection FP16 - CPU openvino: Vehicle Detection FP16 - CPU openvino: Face Detection FP16-INT8 - CPU openvino: Face Detection FP16-INT8 - CPU openvino: Vehicle Detection FP16-INT8 - CPU openvino: Vehicle Detection FP16-INT8 - CPU openvino: Weld Porosity Detection FP16 - CPU openvino: Weld Porosity Detection FP16 - CPU openvino: Machine Translation EN To DE FP16 - CPU openvino: Machine Translation EN To DE FP16 - CPU openvino: Weld Porosity Detection FP16-INT8 - CPU openvino: Weld Porosity Detection FP16-INT8 - CPU openvino: Person Vehicle Bike Detection FP16 - CPU openvino: Person Vehicle Bike Detection FP16 - CPU openvino: Age Gender Recognition Retail 0013 FP16 - CPU openvino: Age Gender Recognition Retail 0013 FP16 - CPU openvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPU openvino: Age Gender Recognition Retail 0013 FP16-INT8 - CPU numenta-nab: KNN CAD numenta-nab: Relative Entropy numenta-nab: Windowed Gaussian numenta-nab: Earthgecko Skyline numenta-nab: Bayesian Changepoint numenta-nab: Contextual Anomaly Detector OSE scikit-learn: MNIST Dataset scikit-learn: TSNE MNIST Dataset scikit-learn: Sparse Rand Projections, 100 Iterations a b c 201 173 357 25130200000 0.413 2.238 3.125 8.33 1.229 16.499 73.506 79.105 4.392 51.631 323.225 356.085 93 46 1.69939 1.204979 0.791489 1.798704 1.638868 1.293792 0.867297 1.731054 190.421 2642.392 5.11104 10.8363 2.37749 2.48501 17.1397 11.6929 8.30947 15.5046 3.80985 5.02536 6850.49 3625.06 6878.39 3622.8 3.99763 6869.52 3640.28 2.23303 174.4 174.8 173.9 173.6 12318.5 21256.3 22167.5 21728.4 25273.3 25227.2 24369.6 26268.4 25923.7 31139.2 30543 29621.9 21256.4 23641.5 24536.7 28002.8 306.09 902.53 417.83 3260.14 1083.6 1.37 2907.95 0.86 4564.3 0.85 4627.4 105.44 37.9 2.57 1552.62 164.79 24.25 124.59 32.08 14.9 268.31 260.1 30.73 181.05 22.07 3609.48 2.2 3914.1 2.03 364.397 32.183 18.272 200.783 56.706 69.885 251.412 109.345 3294.519 201 175 377 25286500000 0.417 2.269 3.163 8.621 1.247 16.693 75.452 80.31 4.433 53.451 324.322 356.327 94 46 1.717714 1.206529 0.794756 1.802469 1.651464 1.29592 0.870159 1.733011 189.627 2642.66 5.03425 10.8813 2.26968 2.47157 17.1202 12.5886 8.38301 15.5676 3.77816 5.05109 6861.12 3632.36 6904.88 3783.41 4.01087 6897.51 3657.32 2.2057 175.2 175.2 172.1 171.6 12364.9 21051.4 22053.8 21711.8 25267.5 25164.2 24360.3 26246.9 25936.5 30808.9 30259.7 29633.5 21125.9 23487.2 24424.9 27948 305.77 904.16 417.45 3257.91 1086.78 1.37 2900.79 0.86 4567.98 0.85 4705.67 104.28 38.33 2.57 1555.24 164.14 24.35 124.97 31.98 14.92 267.76 258.24 30.96 177.44 22.52 3595.44 2.21 3925.52 2.03 364.876 32.448 18.344 193.302 60.654 70.238 252.299 108.375 3294.87 200 175 381 25386800000 0.416 2.284 3.155 8.654 1.247 16.673 74.668 80.973 4.446 53.145 328.002 364.038 94 46 1.704004 1.206909 0.792159 1.802314 1.649194 1.295966 0.870579 1.737779 189.634 2688.942 67.4107 47.6781 40.0963 51.5073 17.2961 11.7109 8.47927 15.4711 3.78238 5.15364 6832.22 3629.54 6850.47 3612.19 3.99005 6842.96 3636.49 2.14039 173.1 167 173.1 168.9 12422.9 21050.4 22080.3 21625.8 25133.1 25045.3 24267.8 26188 26058.7 30644.9 30253.2 29572.8 21160.8 23596 24231 27834.5 307.76 905.71 417.82 3234.94 1083.92 1.38 2889.56 0.86 4555.58 0.85 4632.94 104.85 38.12 2.58 1548.9 164.12 24.35 125.45 31.85 14.93 267.65 257.58 31.03 174.87 22.85 3620.42 2.2 3970.02 2 360.585 34.335 18.648 201.311 60.22 69.625 251.815 110.002 3302.545 OpenBenchmarking.org
FluidX3D Test: FP32-FP32 OpenBenchmarking.org MLUPs/s, More Is Better FluidX3D 1.4 Test: FP32-FP32 b a c 40 80 120 160 200 201 201 200
FluidX3D Test: FP32-FP16C OpenBenchmarking.org MLUPs/s, More Is Better FluidX3D 1.4 Test: FP32-FP16C c b a 40 80 120 160 200 175 175 173
FluidX3D Test: FP32-FP16S OpenBenchmarking.org MLUPs/s, More Is Better FluidX3D 1.4 Test: FP32-FP16S c b a 80 160 240 320 400 381 377 357
nekRS Input: TurboPipe Periodic OpenBenchmarking.org FLOP/s, More Is Better nekRS 22.0 Input: TurboPipe Periodic c b a 5000M 10000M 15000M 20000M 25000M 25386800000 25286500000 25130200000 1. (CXX) g++ options: -fopenmp -O2 -march=native -mtune=native -ftree-vectorize -lmpi_cxx -lmpi
rav1e Speed: 1 OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.6.1 Speed: 1 b c a 0.0938 0.1876 0.2814 0.3752 0.469 0.417 0.416 0.413
rav1e Speed: 5 OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.6.1 Speed: 5 c b a 0.5139 1.0278 1.5417 2.0556 2.5695 2.284 2.269 2.238
rav1e Speed: 6 OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.6.1 Speed: 6 b c a 0.7117 1.4234 2.1351 2.8468 3.5585 3.163 3.155 3.125
rav1e Speed: 10 OpenBenchmarking.org Frames Per Second, More Is Better rav1e 0.6.1 Speed: 10 c b a 2 4 6 8 10 8.654 8.621 8.330
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.4 Encoder Mode: Preset 4 - Input: Bosphorus 4K c b a 0.2806 0.5612 0.8418 1.1224 1.403 1.247 1.247 1.229 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.4 Encoder Mode: Preset 8 - Input: Bosphorus 4K b c a 4 8 12 16 20 16.69 16.67 16.50 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.4 Encoder Mode: Preset 12 - Input: Bosphorus 4K b c a 20 40 60 80 100 75.45 74.67 73.51 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.4 Encoder Mode: Preset 13 - Input: Bosphorus 4K c b a 20 40 60 80 100 80.97 80.31 79.11 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.4 Encoder Mode: Preset 4 - Input: Bosphorus 1080p c b a 1.0004 2.0008 3.0012 4.0016 5.002 4.446 4.433 4.392 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.4 Encoder Mode: Preset 8 - Input: Bosphorus 1080p b c a 12 24 36 48 60 53.45 53.15 51.63 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.4 Encoder Mode: Preset 12 - Input: Bosphorus 1080p c b a 70 140 210 280 350 328.00 324.32 323.23 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.4 Encoder Mode: Preset 13 - Input: Bosphorus 1080p c b a 80 160 240 320 400 364.04 356.33 356.09 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
OpenVKL Benchmark: vklBenchmark ISPC OpenBenchmarking.org Items / Sec, More Is Better OpenVKL 1.3.1 Benchmark: vklBenchmark ISPC c b a 20 40 60 80 100 94 94 93 MIN: 10 / MAX: 1453 MIN: 10 / MAX: 1446 MIN: 10 / MAX: 1436
OpenVKL Benchmark: vklBenchmark Scalar OpenBenchmarking.org Items / Sec, More Is Better OpenVKL 1.3.1 Benchmark: vklBenchmark Scalar c b a 10 20 30 40 50 46 46 46 MIN: 5 / MAX: 1066 MIN: 5 / MAX: 1072 MIN: 5 / MAX: 1052
Stargate Digital Audio Workstation Sample Rate: 44100 - Buffer Size: 512 OpenBenchmarking.org Render Ratio, More Is Better Stargate Digital Audio Workstation 22.11.5 Sample Rate: 44100 - Buffer Size: 512 b c a 0.3865 0.773 1.1595 1.546 1.9325 1.717714 1.704004 1.699390 1. (CXX) g++ options: -lpthread -lsndfile -lm -O3 -march=native -ffast-math -funroll-loops -fstrength-reduce -fstrict-aliasing -finline-functions
Stargate Digital Audio Workstation Sample Rate: 96000 - Buffer Size: 512 OpenBenchmarking.org Render Ratio, More Is Better Stargate Digital Audio Workstation 22.11.5 Sample Rate: 96000 - Buffer Size: 512 c b a 0.2716 0.5432 0.8148 1.0864 1.358 1.206909 1.206529 1.204979 1. (CXX) g++ options: -lpthread -lsndfile -lm -O3 -march=native -ffast-math -funroll-loops -fstrength-reduce -fstrict-aliasing -finline-functions
Stargate Digital Audio Workstation Sample Rate: 192000 - Buffer Size: 512 OpenBenchmarking.org Render Ratio, More Is Better Stargate Digital Audio Workstation 22.11.5 Sample Rate: 192000 - Buffer Size: 512 b c a 0.1788 0.3576 0.5364 0.7152 0.894 0.794756 0.792159 0.791489 1. (CXX) g++ options: -lpthread -lsndfile -lm -O3 -march=native -ffast-math -funroll-loops -fstrength-reduce -fstrict-aliasing -finline-functions
Stargate Digital Audio Workstation Sample Rate: 44100 - Buffer Size: 1024 OpenBenchmarking.org Render Ratio, More Is Better Stargate Digital Audio Workstation 22.11.5 Sample Rate: 44100 - Buffer Size: 1024 b c a 0.4056 0.8112 1.2168 1.6224 2.028 1.802469 1.802314 1.798704 1. (CXX) g++ options: -lpthread -lsndfile -lm -O3 -march=native -ffast-math -funroll-loops -fstrength-reduce -fstrict-aliasing -finline-functions
Stargate Digital Audio Workstation Sample Rate: 480000 - Buffer Size: 512 OpenBenchmarking.org Render Ratio, More Is Better Stargate Digital Audio Workstation 22.11.5 Sample Rate: 480000 - Buffer Size: 512 b c a 0.3716 0.7432 1.1148 1.4864 1.858 1.651464 1.649194 1.638868 1. (CXX) g++ options: -lpthread -lsndfile -lm -O3 -march=native -ffast-math -funroll-loops -fstrength-reduce -fstrict-aliasing -finline-functions
Stargate Digital Audio Workstation Sample Rate: 96000 - Buffer Size: 1024 OpenBenchmarking.org Render Ratio, More Is Better Stargate Digital Audio Workstation 22.11.5 Sample Rate: 96000 - Buffer Size: 1024 c b a 0.2916 0.5832 0.8748 1.1664 1.458 1.295966 1.295920 1.293792 1. (CXX) g++ options: -lpthread -lsndfile -lm -O3 -march=native -ffast-math -funroll-loops -fstrength-reduce -fstrict-aliasing -finline-functions
Stargate Digital Audio Workstation Sample Rate: 192000 - Buffer Size: 1024 OpenBenchmarking.org Render Ratio, More Is Better Stargate Digital Audio Workstation 22.11.5 Sample Rate: 192000 - Buffer Size: 1024 c b a 0.1959 0.3918 0.5877 0.7836 0.9795 0.870579 0.870159 0.867297 1. (CXX) g++ options: -lpthread -lsndfile -lm -O3 -march=native -ffast-math -funroll-loops -fstrength-reduce -fstrict-aliasing -finline-functions
Stargate Digital Audio Workstation Sample Rate: 480000 - Buffer Size: 1024 OpenBenchmarking.org Render Ratio, More Is Better Stargate Digital Audio Workstation 22.11.5 Sample Rate: 480000 - Buffer Size: 1024 c b a 0.391 0.782 1.173 1.564 1.955 1.737779 1.733011 1.731054 1. (CXX) g++ options: -lpthread -lsndfile -lm -O3 -march=native -ffast-math -funroll-loops -fstrength-reduce -fstrict-aliasing -finline-functions
Timed Linux Kernel Compilation Build: defconfig OpenBenchmarking.org Seconds, Fewer Is Better Timed Linux Kernel Compilation 6.1 Build: defconfig b c a 40 80 120 160 200 189.63 189.63 190.42
Timed Linux Kernel Compilation Build: allmodconfig OpenBenchmarking.org Seconds, Fewer Is Better Timed Linux Kernel Compilation 6.1 Build: allmodconfig a b c 600 1200 1800 2400 3000 2642.39 2642.66 2688.94
oneDNN Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU b a c 15 30 45 60 75 5.03425 5.11104 67.41070 MIN: 4.43 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU a b c 11 22 33 44 55 10.84 10.88 47.68 MIN: 10.2 MIN: 10.22 MIN: 10.77 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU b a c 9 18 27 36 45 2.26968 2.37749 40.09630 MIN: 1.93 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU b a c 12 24 36 48 60 2.47157 2.48501 51.50730 MIN: 2.51 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU b a c 4 8 12 16 20 17.12 17.14 17.30 MIN: 16.99 MIN: 17.01 MIN: 17 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU a c b 3 6 9 12 15 11.69 11.71 12.59 MIN: 7.4 MIN: 7.33 MIN: 7.47 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU a b c 2 4 6 8 10 8.30947 8.38301 8.47927 MIN: 7.97 MIN: 8.01 MIN: 8.09 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU c a b 4 8 12 16 20 15.47 15.50 15.57 MIN: 15.23 MIN: 14.98 MIN: 15.25 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU b c a 0.8572 1.7144 2.5716 3.4288 4.286 3.77816 3.78238 3.80985 MIN: 2.87 MIN: 2.9 MIN: 2.87 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU a b c 1.1596 2.3192 3.4788 4.6384 5.798 5.02536 5.05109 5.15364 MIN: 4.65 MIN: 4.66 MIN: 4.63 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU c a b 1500 3000 4500 6000 7500 6832.22 6850.49 6861.12 MIN: 6683.82 MIN: 6698.29 MIN: 6709.14 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU a c b 800 1600 2400 3200 4000 3625.06 3629.54 3632.36 MIN: 3495.85 MIN: 3500.37 MIN: 3504.4 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU c a b 1500 3000 4500 6000 7500 6850.47 6878.39 6904.88 MIN: 6689.16 MIN: 6697.57 MIN: 6753.33 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU c a b 800 1600 2400 3200 4000 3612.19 3622.80 3783.41 MIN: 3493.86 MIN: 3501.52 MIN: 3514.1 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU c a b 0.9024 1.8048 2.7072 3.6096 4.512 3.99005 3.99763 4.01087 MIN: 3.8 MIN: 3.84 MIN: 3.89 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU c a b 1500 3000 4500 6000 7500 6842.96 6869.52 6897.51 MIN: 6686.11 MIN: 6707.44 MIN: 6737.21 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU c a b 800 1600 2400 3200 4000 3636.49 3640.28 3657.32 MIN: 3511.21 MIN: 3508.09 MIN: 3527.16 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
oneDNN Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU OpenBenchmarking.org ms, Fewer Is Better oneDNN 3.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU c b a 0.5024 1.0048 1.5072 2.0096 2.512 2.14039 2.20570 2.23303 MIN: 1.66 MIN: 1.65 MIN: 1.66 1. (CXX) g++ options: -O3 -march=native -fopenmp -msse4.1 -fPIC -pie -ldl
CockroachDB Workload: MoVR - Concurrency: 128 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: MoVR - Concurrency: 128 b a c 40 80 120 160 200 175.2 174.4 173.1
CockroachDB Workload: MoVR - Concurrency: 256 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: MoVR - Concurrency: 256 b a c 40 80 120 160 200 175.2 174.8 167.0
CockroachDB Workload: MoVR - Concurrency: 512 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: MoVR - Concurrency: 512 a c b 40 80 120 160 200 173.9 173.1 172.1
CockroachDB Workload: MoVR - Concurrency: 1024 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: MoVR - Concurrency: 1024 a b c 40 80 120 160 200 173.6 171.6 168.9
CockroachDB Workload: KV, 10% Reads - Concurrency: 128 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 128 c b a 3K 6K 9K 12K 15K 12422.9 12364.9 12318.5
CockroachDB Workload: KV, 10% Reads - Concurrency: 256 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 256 a b c 5K 10K 15K 20K 25K 21256.3 21051.4 21050.4
CockroachDB Workload: KV, 10% Reads - Concurrency: 512 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 512 a c b 5K 10K 15K 20K 25K 22167.5 22080.3 22053.8
CockroachDB Workload: KV, 50% Reads - Concurrency: 128 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 128 a b c 5K 10K 15K 20K 25K 21728.4 21711.8 21625.8
CockroachDB Workload: KV, 50% Reads - Concurrency: 256 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 256 a b c 5K 10K 15K 20K 25K 25273.3 25267.5 25133.1
CockroachDB Workload: KV, 50% Reads - Concurrency: 512 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 512 a b c 5K 10K 15K 20K 25K 25227.2 25164.2 25045.3
CockroachDB Workload: KV, 60% Reads - Concurrency: 128 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 128 a b c 5K 10K 15K 20K 25K 24369.6 24360.3 24267.8
CockroachDB Workload: KV, 60% Reads - Concurrency: 256 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 256 a b c 6K 12K 18K 24K 30K 26268.4 26246.9 26188.0
CockroachDB Workload: KV, 60% Reads - Concurrency: 512 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 512 c b a 6K 12K 18K 24K 30K 26058.7 25936.5 25923.7
CockroachDB Workload: KV, 95% Reads - Concurrency: 128 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 128 a b c 7K 14K 21K 28K 35K 31139.2 30808.9 30644.9
CockroachDB Workload: KV, 95% Reads - Concurrency: 256 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 256 a b c 7K 14K 21K 28K 35K 30543.0 30259.7 30253.2
CockroachDB Workload: KV, 95% Reads - Concurrency: 512 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 512 b a c 6K 12K 18K 24K 30K 29633.5 29621.9 29572.8
CockroachDB Workload: KV, 10% Reads - Concurrency: 1024 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 10% Reads - Concurrency: 1024 a c b 5K 10K 15K 20K 25K 21256.4 21160.8 21125.9
CockroachDB Workload: KV, 50% Reads - Concurrency: 1024 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 50% Reads - Concurrency: 1024 a c b 5K 10K 15K 20K 25K 23641.5 23596.0 23487.2
CockroachDB Workload: KV, 60% Reads - Concurrency: 1024 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 60% Reads - Concurrency: 1024 a b c 5K 10K 15K 20K 25K 24536.7 24424.9 24231.0
CockroachDB Workload: KV, 95% Reads - Concurrency: 1024 OpenBenchmarking.org ops/s, More Is Better CockroachDB 22.2 Workload: KV, 95% Reads - Concurrency: 1024 a b c 6K 12K 18K 24K 30K 28002.8 27948.0 27834.5
Blender Blend File: BMW27 - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.4 Blend File: BMW27 - Compute: CPU-Only b a c 70 140 210 280 350 305.77 306.09 307.76
Blender Blend File: Classroom - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.4 Blend File: Classroom - Compute: CPU-Only a b c 200 400 600 800 1000 902.53 904.16 905.71
Blender Blend File: Fishy Cat - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.4 Blend File: Fishy Cat - Compute: CPU-Only b c a 90 180 270 360 450 417.45 417.82 417.83
Blender Blend File: Barbershop - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.4 Blend File: Barbershop - Compute: CPU-Only c b a 700 1400 2100 2800 3500 3234.94 3257.91 3260.14
Blender Blend File: Pabellon Barcelona - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 3.4 Blend File: Pabellon Barcelona - Compute: CPU-Only a c b 200 400 600 800 1000 1083.60 1083.92 1086.78
OpenVINO Model: Face Detection FP16 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Face Detection FP16 - Device: CPU c b a 0.3105 0.621 0.9315 1.242 1.5525 1.38 1.37 1.37 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Face Detection FP16 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Face Detection FP16 - Device: CPU c b a 600 1200 1800 2400 3000 2889.56 2900.79 2907.95 MIN: 2130.02 / MAX: 3082.08 MIN: 1935.99 / MAX: 3085.36 MIN: 2048.8 / MAX: 3076.74 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Person Detection FP16 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Person Detection FP16 - Device: CPU c b a 0.1935 0.387 0.5805 0.774 0.9675 0.86 0.86 0.86 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Person Detection FP16 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Person Detection FP16 - Device: CPU c a b 1000 2000 3000 4000 5000 4555.58 4564.30 4567.98 MIN: 3391.76 / MAX: 4917.08 MIN: 3395.41 / MAX: 4924.67 MIN: 3311.82 / MAX: 4914.52 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Person Detection FP32 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Person Detection FP32 - Device: CPU c b a 0.1913 0.3826 0.5739 0.7652 0.9565 0.85 0.85 0.85 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Person Detection FP32 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Person Detection FP32 - Device: CPU a c b 1000 2000 3000 4000 5000 4627.40 4632.94 4705.67 MIN: 3461.83 / MAX: 5004.23 MIN: 3246.77 / MAX: 4955.57 MIN: 3414.61 / MAX: 4954.48 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Vehicle Detection FP16 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Vehicle Detection FP16 - Device: CPU a c b 20 40 60 80 100 105.44 104.85 104.28 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Vehicle Detection FP16 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Vehicle Detection FP16 - Device: CPU a c b 9 18 27 36 45 37.90 38.12 38.33 MIN: 25.27 / MAX: 84.62 MIN: 26.05 / MAX: 83.42 MIN: 26.97 / MAX: 86.94 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Face Detection FP16-INT8 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Face Detection FP16-INT8 - Device: CPU c b a 0.5805 1.161 1.7415 2.322 2.9025 2.58 2.57 2.57 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Face Detection FP16-INT8 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Face Detection FP16-INT8 - Device: CPU c a b 300 600 900 1200 1500 1548.90 1552.62 1555.24 MIN: 1000.5 / MAX: 1643.06 MIN: 994.18 / MAX: 1658.73 MIN: 987.74 / MAX: 1638.42 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Vehicle Detection FP16-INT8 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Vehicle Detection FP16-INT8 - Device: CPU a b c 40 80 120 160 200 164.79 164.14 164.12 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Vehicle Detection FP16-INT8 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Vehicle Detection FP16-INT8 - Device: CPU a b c 6 12 18 24 30 24.25 24.35 24.35 MIN: 14.38 / MAX: 63.86 MIN: 15.05 / MAX: 64.68 MIN: 14.89 / MAX: 63.77 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Weld Porosity Detection FP16 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Weld Porosity Detection FP16 - Device: CPU c b a 30 60 90 120 150 125.45 124.97 124.59 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Weld Porosity Detection FP16 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Weld Porosity Detection FP16 - Device: CPU c b a 7 14 21 28 35 31.85 31.98 32.08 MIN: 20.23 / MAX: 81.16 MIN: 18.51 / MAX: 81.22 MIN: 19.86 / MAX: 78.3 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Machine Translation EN To DE FP16 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Machine Translation EN To DE FP16 - Device: CPU c b a 4 8 12 16 20 14.93 14.92 14.90 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Machine Translation EN To DE FP16 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Machine Translation EN To DE FP16 - Device: CPU c b a 60 120 180 240 300 267.65 267.76 268.31 MIN: 158.54 / MAX: 333.85 MIN: 157 / MAX: 354.66 MIN: 173.59 / MAX: 305.62 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Weld Porosity Detection FP16-INT8 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Weld Porosity Detection FP16-INT8 - Device: CPU a b c 60 120 180 240 300 260.10 258.24 257.58 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Weld Porosity Detection FP16-INT8 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Weld Porosity Detection FP16-INT8 - Device: CPU a b c 7 14 21 28 35 30.73 30.96 31.03 MIN: 16.95 / MAX: 84.01 MIN: 18.67 / MAX: 47.56 MIN: 12.41 / MAX: 84.78 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Person Vehicle Bike Detection FP16 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Person Vehicle Bike Detection FP16 - Device: CPU a b c 40 80 120 160 200 181.05 177.44 174.87 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Person Vehicle Bike Detection FP16 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Person Vehicle Bike Detection FP16 - Device: CPU a b c 5 10 15 20 25 22.07 22.52 22.85 MIN: 12.92 / MAX: 53.87 MIN: 12.96 / MAX: 56.58 MIN: 13.11 / MAX: 56.73 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU c a b 800 1600 2400 3200 4000 3620.42 3609.48 3595.44 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU a c b 0.4973 0.9946 1.4919 1.9892 2.4865 2.20 2.20 2.21 MIN: 0.69 / MAX: 20 MIN: 0.75 / MAX: 7.41 MIN: 0.73 / MAX: 19.99 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU OpenBenchmarking.org FPS, More Is Better OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU c b a 900 1800 2700 3600 4500 3970.02 3925.52 3914.10 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
OpenVINO Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU OpenBenchmarking.org ms, Fewer Is Better OpenVINO 2022.3 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU c a b 0.4568 0.9136 1.3704 1.8272 2.284 2.00 2.03 2.03 MIN: 0.66 / MAX: 19.69 MIN: 0.7 / MAX: 26.99 MIN: 0.7 / MAX: 5.69 1. (CXX) g++ options: -fPIC -fsigned-char -ffunction-sections -fdata-sections -O3 -fno-strict-overflow -fwrapv -shared
Numenta Anomaly Benchmark Detector: KNN CAD OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: KNN CAD c a b 80 160 240 320 400 360.59 364.40 364.88
Numenta Anomaly Benchmark Detector: Relative Entropy OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Relative Entropy a b c 8 16 24 32 40 32.18 32.45 34.34
Numenta Anomaly Benchmark Detector: Windowed Gaussian OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Windowed Gaussian a b c 5 10 15 20 25 18.27 18.34 18.65
Numenta Anomaly Benchmark Detector: Earthgecko Skyline OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Earthgecko Skyline b a c 40 80 120 160 200 193.30 200.78 201.31
Numenta Anomaly Benchmark Detector: Bayesian Changepoint OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Bayesian Changepoint a c b 14 28 42 56 70 56.71 60.22 60.65
Numenta Anomaly Benchmark Detector: Contextual Anomaly Detector OSE OpenBenchmarking.org Seconds, Fewer Is Better Numenta Anomaly Benchmark 1.1 Detector: Contextual Anomaly Detector OSE c a b 16 32 48 64 80 69.63 69.89 70.24
Scikit-Learn Benchmark: MNIST Dataset OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.1.3 Benchmark: MNIST Dataset a c b 60 120 180 240 300 251.41 251.82 252.30
Scikit-Learn Benchmark: TSNE MNIST Dataset OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.1.3 Benchmark: TSNE MNIST Dataset b a c 20 40 60 80 100 108.38 109.35 110.00
Scikit-Learn Benchmark: Sparse Random Projections, 100 Iterations OpenBenchmarking.org Seconds, Fewer Is Better Scikit-Learn 1.1.3 Benchmark: Sparse Random Projections, 100 Iterations a b c 700 1400 2100 2800 3500 3294.52 3294.87 3302.55
Phoronix Test Suite v10.8.4