big bench

AMD Ryzen Threadripper 7980X 64-Cores testing with a ASUS Pro WS TRX50-SAGE WIFI (0217 BIOS) and AMD Radeon RX 7900 XT 20GB on Ubuntu 23.10 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2401079-PTS-BIGBENCH30
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January 07
  5 Hours, 4 Minutes
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January 07
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January 07
  1 Hour, 40 Minutes
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big benchOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen Threadripper 7980X 64-Cores @ 8.21GHz (64 Cores / 128 Threads)ASUS Pro WS TRX50-SAGE WIFI (0217 BIOS)AMD Device 14a4128GB2000GB Corsair MP700 PRO + 1000GB Western Digital WDS100T1X0E-00AFY0AMD Radeon RX 7900 XT 20GB (2025/1249MHz)Realtek ALC1220DELL U2723QEAquantia Device 04c0 + Intel I226-LM + MEDIATEK MT7922 802.11ax PCIUbuntu 23.106.7.0-060700rc2daily20231126-generic (x86_64)GNOME Shell 45.0X Server 1.21.1.7 + Wayland4.6 Mesa 23.2.1-1ubuntu3 (LLVM 15.0.7 DRM 3.56)GCC 13.2.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionBig Bench 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,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v - Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa108105- Python 3.11.6- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Mitigation of Safe RET + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

abcResult OverviewPhoronix Test Suite100%100%100%100%PyTorchTensorFlowQuicksilver

big benchtensorflow: CPU - 1 - VGG-16quicksilver: CORAL2 P2tensorflow: CPU - 1 - AlexNettensorflow: CPU - 16 - VGG-16tensorflow: CPU - 32 - VGG-16tensorflow: CPU - 64 - VGG-16tensorflow: CPU - 16 - AlexNettensorflow: CPU - 256 - VGG-16tensorflow: CPU - 32 - AlexNettensorflow: CPU - 512 - VGG-16tensorflow: CPU - 64 - AlexNettensorflow: CPU - 1 - GoogLeNettensorflow: CPU - 1 - ResNet-50tensorflow: CPU - 256 - AlexNettensorflow: CPU - 512 - AlexNetquicksilver: CORAL2 P1tensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - ResNet-50tensorflow: CPU - 32 - GoogLeNettensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 64 - GoogLeNettensorflow: CPU - 64 - ResNet-50tensorflow: CPU - 256 - GoogLeNettensorflow: CPU - 256 - ResNet-50tensorflow: CPU - 512 - GoogLeNettensorflow: CPU - 512 - ResNet-50pytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 512 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lquicksilver: CTS2pytorch: CPU - 512 - Efficientnet_v2_labc9.741977666725.7244.4148.8952.95311.9757.14510.6657.97740.4621.827.191070.731145.6626026667187.9254.70226.8569.43272.1680.0311.6091.12315.4995.0559.0421.9447.4747.4747.5718.6847.4318.7647.5418.6918.9918.9612.197.527.497.467.47200233337.479.731973333325.8144.548.9353312.0857.11508.5257.97741.7722.597.261073.521148.3826010000188.554.44231.6169.49272.2279.77311.2391.13315.8395.0859.2221.9147.4147.2447.2218.6547.2418.6745.9718.6218.8018.4912.297.467.457.457.40199733337.529.721982000025.9644.4848.8152.91312.1457.15510.457.99741.0422.377.251075.091151.2725920000188.5254.72222.0469.17272.8479.87311.7391.11316.0495.0459.6921.8047.6048.1247.8118.7143.0719.0246.6019.3819.1018.8212.277.507.527.527.54200900007.48OpenBenchmarking.org

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: VGG-16cba3691215SE +/- 0.01, N = 39.729.739.74

Quicksilver

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P2bac4M8M12M16M20MSE +/- 57831.17, N = 3SE +/- 23333.33, N = 31973333319776667198200001. (CXX) g++ options: -fopenmp -O3 -march=native

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: AlexNetabc612182430SE +/- 0.03, N = 325.7225.8125.96

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: VGG-16acb1020304050SE +/- 0.01, N = 344.4144.4844.50

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: VGG-16cab1122334455SE +/- 0.07, N = 348.8148.8948.93

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: VGG-16cab1224364860SE +/- 0.06, N = 352.9152.9553.00

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNetabc70140210280350SE +/- 0.95, N = 3311.97312.08312.14

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: VGG-16bac1326395265SE +/- 0.02, N = 357.1157.1457.15

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: AlexNetbca110220330440550SE +/- 0.43, N = 3508.52510.40510.66

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: VGG-16abc1326395265SE +/- 0.02, N = 357.9757.9757.99

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: AlexNetacb160320480640800SE +/- 0.53, N = 3740.46741.04741.77

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: GoogLeNetacb510152025SE +/- 0.29, N = 1521.8222.3722.59

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 1 - Model: ResNet-50acb246810SE +/- 0.04, N = 37.197.257.26

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: AlexNetabc2004006008001000SE +/- 2.11, N = 31070.731073.521075.09

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: AlexNetabc2004006008001000SE +/- 0.89, N = 31145.661148.381151.27

Quicksilver

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CORAL2 P1cba6M12M18M24M30MSE +/- 79372.54, N = 3SE +/- 92796.07, N = 32592000026010000260266671. (CXX) g++ options: -fopenmp -O3 -march=native

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNetabc4080120160200SE +/- 0.56, N = 3187.92188.50188.52

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-50bac1224364860SE +/- 0.07, N = 354.4454.7054.72

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: GoogLeNetcab50100150200250SE +/- 0.94, N = 3222.04226.85231.61

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: ResNet-50cab1530456075SE +/- 0.03, N = 369.1769.4369.49

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: GoogLeNetabc60120180240300SE +/- 0.93, N = 3272.16272.22272.84

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: ResNet-50bca20406080100SE +/- 0.06, N = 379.7779.8780.00

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: GoogLeNetbac70140210280350SE +/- 0.26, N = 3311.23311.60311.73

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: ResNet-50cab20406080100SE +/- 0.03, N = 391.1191.1291.13

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: GoogLeNetabc70140210280350SE +/- 0.17, N = 3315.49315.83316.04

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: ResNet-50cab20406080100SE +/- 0.01, N = 395.0495.0595.08

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50abc1326395265SE +/- 0.52, N = 3SE +/- 0.39, N = 1459.0459.2259.69MIN: 49.45 / MAX: 62.07MIN: 49.85 / MAX: 62.35MIN: 53.84 / MAX: 61.85

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152cba510152025SE +/- 0.08, N = 3SE +/- 0.08, N = 321.8021.9121.94MIN: 21.22 / MAX: 22.14MIN: 20.97 / MAX: 22.39MIN: 20.91 / MAX: 22.35

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50bac1122334455SE +/- 0.15, N = 3SE +/- 0.21, N = 347.4147.4747.60MIN: 43.15 / MAX: 48.78MIN: 43.56 / MAX: 48.81MIN: 43.77 / MAX: 48.91

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50bac1122334455SE +/- 0.43, N = 13SE +/- 0.12, N = 347.2447.4748.12MIN: 40.13 / MAX: 49.58MIN: 43.75 / MAX: 48.83MIN: 44.48 / MAX: 49.1

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50bac1122334455SE +/- 0.32, N = 3SE +/- 0.18, N = 347.2247.5747.81MIN: 43.76 / MAX: 48.92MIN: 43.64 / MAX: 49.11MIN: 43.73 / MAX: 48.84

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152bac510152025SE +/- 0.17, N = 3SE +/- 0.05, N = 318.6518.6818.71MIN: 17.9 / MAX: 19.22MIN: 18.15 / MAX: 18.95MIN: 18.25 / MAX: 18.96

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50cba1122334455SE +/- 0.65, N = 3SE +/- 0.44, N = 643.0747.2447.43MIN: 39.73 / MAX: 45.38MIN: 39.04 / MAX: 49.14MIN: 39.54 / MAX: 49.38

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152bac510152025SE +/- 0.14, N = 318.6718.7619.02MIN: 17.72 / MAX: 18.87MIN: 18.21 / MAX: 19.24MIN: 18.53 / MAX: 19.21

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50bca1122334455SE +/- 0.26, N = 345.9746.6047.54MIN: 43.46 / MAX: 48.21MIN: 43.8 / MAX: 47.68MIN: 43.78 / MAX: 49.15

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152bac510152025SE +/- 0.03, N = 318.6218.6919.38MIN: 18.09 / MAX: 18.8MIN: 18.14 / MAX: 18.93MIN: 18.61 / MAX: 19.57

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152bac510152025SE +/- 0.08, N = 318.8018.9919.10MIN: 18.29 / MAX: 19.02MIN: 18.38 / MAX: 19.33MIN: 18.59 / MAX: 19.3

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152bca510152025SE +/- 0.05, N = 318.4918.8218.96MIN: 18.01 / MAX: 18.69MIN: 18.25 / MAX: 19.03MIN: 18.41 / MAX: 19.25

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lacb3691215SE +/- 0.03, N = 312.1912.2712.29MIN: 11.91 / MAX: 12.38MIN: 12 / MAX: 12.4MIN: 12.13 / MAX: 12.42

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lbca246810SE +/- 0.02, N = 37.467.507.52MIN: 6.82 / MAX: 8.06MIN: 7.02 / MAX: 8.12MIN: 6.92 / MAX: 8.16

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lbac246810SE +/- 0.01, N = 37.457.497.52MIN: 6.99 / MAX: 8.1MIN: 6.96 / MAX: 8.11MIN: 7.05 / MAX: 8.13

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lbac246810SE +/- 0.02, N = 37.457.467.52MIN: 6.98 / MAX: 8.07MIN: 6.94 / MAX: 8.17MIN: 5.94 / MAX: 8.1

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lbac246810SE +/- 0.01, N = 37.407.477.54MIN: 6.92 / MAX: 8.06MIN: 6.98 / MAX: 8.1MIN: 7.01 / MAX: 8.17

Quicksilver

OpenBenchmarking.orgFigure Of Merit, More Is BetterQuicksilver 20230818Input: CTS2bac4M8M12M16M20MSE +/- 49103.07, N = 3SE +/- 40960.69, N = 31997333320023333200900001. (CXX) g++ options: -fopenmp -O3 -march=native

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lacb246810SE +/- 0.01, N = 37.477.487.52MIN: 6.97 / MAX: 8.13MIN: 7.03 / MAX: 8.13MIN: 7.01 / MAX: 8.06