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&grt&sor&rro.

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-50cba163248648057.4457.4671.81MIN: 56.19 / MAX: 58.2MIN: 56.35 / MAX: 68.07MIN: 70.12 / MAX: 72.04

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-152bca71421283528.3528.4728.55MIN: 28 / MAX: 28.43MIN: 28 / MAX: 28.54MIN: 27.88 / MAX: 28.63

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50acb102030405042.9743.5544.23MIN: 9.78 / MAX: 44.95MIN: 9.79 / MAX: 45.11MIN: 9.75 / MAX: 45.13

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-50cab102030405039.1043.5743.69MIN: 38.31 / MAX: 39.18MIN: 10.28 / MAX: 45.23MIN: 10 / MAX: 44.93

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-50bca102030405038.8342.4443.57MIN: 9.43 / MAX: 42.63MIN: 10.09 / MAX: 44.94MIN: 9.83 / MAX: 45.65

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152acb4812162016.8216.8216.83MIN: 5.94 / MAX: 17.56MIN: 6.29 / MAX: 17.63MIN: 6.26 / MAX: 17.61

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-50bac102030405042.9643.6243.70MIN: 11.33 / MAX: 44.99MIN: 10.53 / MAX: 45.39MIN: 10.24 / MAX: 45.38

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-152abc4812162015.7616.6616.85MIN: 5.85 / MAX: 17.62MIN: 6.55 / MAX: 17.53MIN: 5.47 / MAX: 17.6

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-50bac102030405038.4339.6343.51MIN: 9.91 / MAX: 43.83MIN: 11.63 / MAX: 44.96MIN: 10.48 / MAX: 45.09

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-152bac4812162016.7116.8616.86MIN: 6.13 / MAX: 17.52MIN: 7.09 / MAX: 17.62MIN: 6.25 / MAX: 17.63

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-152bca4812162016.7916.8016.87MIN: 6.54 / MAX: 17.58MIN: 6.4 / MAX: 17.6MIN: 6.32 / MAX: 17.66

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-152bca4812162014.6714.8216.81MIN: 5.69 / MAX: 15.6MIN: 5.9 / MAX: 17.52MIN: 6.53 / MAX: 17.63

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_labc369121512.9313.0013.02MIN: 4.5 / MAX: 16.83MIN: 3.43 / MAX: 17.41MIN: 4.51 / MAX: 17.18

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_lacb36912158.5411.4311.46MIN: 4.87 / MAX: 8.84MIN: 4.47 / MAX: 11.86MIN: 5.04 / MAX: 11.96

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_lcba36912159.6910.3611.38MIN: 5.03 / MAX: 11.97MIN: 4.64 / MAX: 10.76MIN: 5.03 / MAX: 11.89

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_lacb36912158.6510.4011.62MIN: 4.77 / MAX: 8.82MIN: 4.47 / MAX: 10.8MIN: 4.95 / MAX: 12.01

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_lacb369121511.1511.4711.53MIN: 4.59 / MAX: 11.97MIN: 4.87 / MAX: 11.96MIN: 4.97 / MAX: 12

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_lbac36912158.6411.0711.54MIN: 4.69 / MAX: 8.91MIN: 4.44 / MAX: 11.86MIN: 4.96 / MAX: 11.96

Phoronix Test Suite v10.8.5