pytorch 2.2 raptor lake

Intel Core i9-14900K testing with a ASUS PRIME Z790-P WIFI (1402 BIOS) and ASUS Intel RPL-S 31GB on Ubuntu 23.10 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2403267-PTS-PYTORCH238&grw&sor.

pytorch 2.2 raptor lakeProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionabcIntel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads)ASUS PRIME Z790-P WIFI (1402 BIOS)Intel Device 7a272 x 16GB DRAM-6000MT/s Corsair CMK32GX5M2B6000C36Western Digital WD_BLACK SN850X 1000GBASUS Intel RPL-S 31GB (1650MHz)Realtek ALC897ASUS VP28UUbuntu 23.106.8.0-phx (x86_64)GNOME Shell 45.1X Server 1.21.1.74.6 Mesa 24.0~git2312240600.c05261~oibaf~m (git-c05261a 2023-12-24 mantic-oibaf-ppa)GCC 13.2.0ext43840x2160OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseProcessor Details- Scaling Governor: intel_pstate powersave (EPP: performance) - CPU Microcode: 0x122 - Thermald 2.5.4Python Details- Python 3.11.6Security Details- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + reg_file_data_sampling: Mitigation of Clear Register File + retbleed: Not affected + 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 / Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

pytorch 2.2 raptor lakepytorch: 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_lpytorch: CPU - 512 - Efficientnet_v2_labc71.8128.5542.9743.5743.5716.8243.6215.7639.6316.8616.8716.8112.938.5411.388.6511.1511.0757.4628.3544.2343.6938.8316.8342.9616.6638.4316.7116.7914.6713.0011.4610.3611.6211.538.6457.4428.4743.5539.1042.4416.8243.7016.8543.5116.8616.8014.8213.0211.439.6910.4011.4711.54OpenBenchmarking.org

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-50abc163248648071.8157.4657.44MIN: 70.12 / MAX: 72.04MIN: 56.35 / MAX: 68.07MIN: 56.19 / MAX: 58.2

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-152acb71421283528.5528.4728.35MIN: 27.88 / MAX: 28.63MIN: 28 / MAX: 28.54MIN: 28 / MAX: 28.43

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50bca102030405044.2343.5542.97MIN: 9.75 / MAX: 45.13MIN: 9.79 / MAX: 45.11MIN: 9.78 / MAX: 44.95

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-50bac102030405043.6943.5739.10MIN: 10 / MAX: 44.93MIN: 10.28 / MAX: 45.23MIN: 38.31 / MAX: 39.18

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-50acb102030405043.5742.4438.83MIN: 9.83 / MAX: 45.65MIN: 10.09 / MAX: 44.94MIN: 9.43 / MAX: 42.63

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152bca4812162016.8316.8216.82MIN: 6.26 / MAX: 17.61MIN: 6.29 / MAX: 17.63MIN: 5.94 / MAX: 17.56

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-50cab102030405043.7043.6242.96MIN: 10.24 / MAX: 45.38MIN: 10.53 / MAX: 45.39MIN: 11.33 / MAX: 44.99

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-152cba4812162016.8516.6615.76MIN: 5.47 / MAX: 17.6MIN: 6.55 / MAX: 17.53MIN: 5.85 / MAX: 17.62

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-50cab102030405043.5139.6338.43MIN: 10.48 / MAX: 45.09MIN: 11.63 / MAX: 44.96MIN: 9.91 / MAX: 43.83

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-152cab4812162016.8616.8616.71MIN: 6.25 / MAX: 17.63MIN: 7.09 / MAX: 17.62MIN: 6.13 / MAX: 17.52

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-152acb4812162016.8716.8016.79MIN: 6.32 / MAX: 17.66MIN: 6.4 / MAX: 17.6MIN: 6.54 / MAX: 17.58

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-152acb4812162016.8114.8214.67MIN: 6.53 / MAX: 17.63MIN: 5.9 / MAX: 17.52MIN: 5.69 / MAX: 15.6

PyTorch

Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lcba369121513.0213.0012.93MIN: 4.51 / MAX: 17.18MIN: 3.43 / MAX: 17.41MIN: 4.5 / MAX: 16.83

PyTorch

Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lbca369121511.4611.438.54MIN: 5.04 / MAX: 11.96MIN: 4.47 / MAX: 11.86MIN: 4.87 / MAX: 8.84

PyTorch

Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_labc369121511.3810.369.69MIN: 5.03 / MAX: 11.89MIN: 4.64 / MAX: 10.76MIN: 5.03 / MAX: 11.97

PyTorch

Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lbca369121511.6210.408.65MIN: 4.95 / MAX: 12.01MIN: 4.47 / MAX: 10.8MIN: 4.77 / MAX: 8.82

PyTorch

Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lbca369121511.5311.4711.15MIN: 4.97 / MAX: 12MIN: 4.87 / MAX: 11.96MIN: 4.59 / MAX: 11.97

PyTorch

Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lcab369121511.5411.078.64MIN: 4.96 / MAX: 11.96MIN: 4.44 / MAX: 11.86MIN: 4.69 / MAX: 8.91

Phoronix Test Suite v10.8.5