pytorch icelake

Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus ICL GT2 16GB on Ubuntu 23.04 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 2311164-NE-PYTORCHIC86
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November 16 2023
  1 Hour, 17 Minutes
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November 16 2023
  1 Hour, 20 Minutes
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November 16 2023
  1 Hour, 19 Minutes
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pytorch icelakeOpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads)Dell 06CDVY (1.0.9 BIOS)Intel Ice Lake-LP DRAM16GBToshiba KBG40ZPZ512G NVMe 512GBIntel Iris Plus ICL GT2 16GB (1100MHz)Realtek ALC289Intel Ice Lake-LP PCH CNVi WiFiUbuntu 23.046.2.0-35-generic (x86_64)GNOME Shell 44.3X Server + Wayland4.6 Mesa 23.0.4-0ubuntu1~23.04.1OpenCL 3.0GCC 12.3.0ext41920x1200ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLOpenCLCompilerFile-SystemScreen ResolutionPytorch Icelake BenchmarksSystem Logs- Transparent Huge Pages: madvise- Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xbc - Thermald 2.5.2 - Python 3.11.4- gather_data_sampling: Mitigation of Microcode + 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_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Mitigation of Microcode + tsx_async_abort: Not affected

abcResult OverviewPhoronix Test Suite100%109%117%126%135%PyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchCPU - 1 - ResNet-152CPU - 16 - ResNet-50CPU - 16 - ResNet-152CPU - 256 - ResNet-50CPU - 512 - ResNet-50CPU - 1 - Efficientnet_v2_lCPU - 1 - ResNet-50CPU - 512 - ResNet-152CPU - 256 - ResNet-152CPU - 16 - Efficientnet_v2_lCPU - 512 - Efficientnet_v2_lCPU - 256 - Efficientnet_v2_l

pytorch icelakepytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-50pytorch: CPU - 512 - ResNet-50pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_lpytorch: CPU - 512 - Efficientnet_v2_labc20.968.498.893.648.588.003.463.514.552.472.422.4421.766.367.763.368.398.343.363.394.402.412.412.4421.428.568.903.428.138.343.393.404.382.402.412.42OpenBenchmarking.org

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50abc51015202520.9621.7621.42MIN: 16.4 / MAX: 22.22MIN: 17.9 / MAX: 22.71MIN: 18.9 / MAX: 22.08

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152abc2468108.496.368.56MIN: 6.35 / MAX: 9.32MIN: 5.69 / MAX: 9.22MIN: 7.47 / MAX: 9.14

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50abc2468108.897.768.90MIN: 8.06 / MAX: 10.08MIN: 7.29 / MAX: 9.67MIN: 7.69 / MAX: 10.29

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152abc0.8191.6382.4573.2764.0953.643.363.42MIN: 3.31 / MAX: 4.51MIN: 3.25 / MAX: 4.17MIN: 3.26 / MAX: 4.14

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50abc2468108.588.398.13MIN: 6.92 / MAX: 10.34MIN: 7.8 / MAX: 9.76MIN: 6.05 / MAX: 9.53

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50abc2468108.008.348.34MIN: 7.22 / MAX: 8.96MIN: 7.45 / MAX: 9.54MIN: 7.74 / MAX: 9.75

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152abc0.77851.5572.33553.1143.89253.463.363.39MIN: 3.03 / MAX: 4.01MIN: 3.23 / MAX: 4.14MIN: 3.18 / MAX: 4.19

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152abc0.78981.57962.36943.15923.9493.513.393.40MIN: 2.9 / MAX: 4.19MIN: 3.19 / MAX: 4.18MIN: 3.26 / MAX: 4.12

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_labc1.02382.04763.07144.09525.1194.554.404.38MIN: 4.07 / MAX: 6.31MIN: 4.2 / MAX: 6.5MIN: 3.81 / MAX: 6.1

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_labc0.55581.11161.66742.22322.7792.472.412.40MIN: 2.2 / MAX: 3.04MIN: 2.19 / MAX: 2.95MIN: 2.22 / MAX: 3

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_labc0.54451.0891.63352.1782.72252.422.412.41MIN: 2.23 / MAX: 2.98MIN: 1.7 / MAX: 2.99MIN: 2.23 / MAX: 3.06

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_labc0.5491.0981.6472.1962.7452.442.442.42MIN: 2.24 / MAX: 3.22MIN: 2.27 / MAX: 3.04MIN: 2.18 / MAX: 3