pytorch emerald rapids

2 x INTEL XEON PLATINUM 8592+ testing with a Quanta Cloud QuantaGrid D54Q-2U S6Q-MB-MPS (3B05.TEL4P1 BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2403262-NE-PYTORCHEM92&grr&rdt.

pytorch emerald rapidsProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelDesktopDisplay ServerCompilerFile-SystemScreen Resolutionab2 x INTEL XEON PLATINUM 8592+ @ 3.90GHz (128 Cores / 256 Threads)Quanta Cloud QuantaGrid D54Q-2U S6Q-MB-MPS (3B05.TEL4P1 BIOS)Intel Device 1bce1008GB3201GB Micron_7450_MTFDKCC3T2TFSASPEED2 x Intel X710 for 10GBASE-TUbuntu 23.106.6.0-rc5-phx-patched (x86_64)GNOME Shell 45.0X Server 1.21.1.7GCC 13.2.0ext41920x1200OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseProcessor Details- Scaling Governor: intel_pstate performance (EPP: performance) - CPU Microcode: 0x21000161 Python 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 + 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 emerald rapidspytorch: CPU - 16 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 32 - ResNet-152pytorch: CPU - 64 - ResNet-152pytorch: CPU - 512 - ResNet-152pytorch: CPU - 1 - ResNet-152pytorch: CPU - 64 - ResNet-50pytorch: CPU - 256 - ResNet-50pytorch: CPU - 16 - ResNet-50pytorch: CPU - 512 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 1 - ResNet-50ab16.9817.3617.3117.0017.9119.1741.6143.4244.4843.2443.1349.7417.6917.3817.5217.5917.3919.5342.9844.7543.3044.7644.8748.46OpenBenchmarking.org

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ab4812162016.9817.69MIN: 8.88 / MAX: 17.73MIN: 12.47 / MAX: 18.03

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-152ab4812162017.3617.38MIN: 13.87 / MAX: 17.68MIN: 9.17 / MAX: 17.74

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ab4812162017.3117.52MIN: 7.61 / MAX: 17.66MIN: 8.47 / MAX: 17.81

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-152ab4812162017.0017.59MIN: 6.37 / MAX: 17.5MIN: 7.39 / MAX: 17.91

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-152ab4812162017.9117.39MIN: 6.7 / MAX: 18.43MIN: 8.92 / MAX: 17.83

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-152ab51015202519.1719.53MIN: 11.32 / MAX: 19.93MIN: 6.21 / MAX: 20.18

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-50ab102030405041.6142.98MIN: 21.64 / MAX: 43.52MIN: 18.82 / MAX: 44.16

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-50ab102030405043.4244.75MIN: 40.39 / MAX: 44.48MIN: 15.82 / MAX: 46.04

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ab102030405044.4843.30MIN: 19.94 / MAX: 45.71MIN: 18.44 / MAX: 45.93

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 512 - Model: ResNet-50ab102030405043.2444.76MIN: 40.07 / MAX: 44.05MIN: 21.38 / MAX: 45.97

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-50ab102030405043.1344.87MIN: 21.59 / MAX: 44.07MIN: 37.26 / MAX: 46.02

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ab112233445549.7448.46MIN: 20.74 / MAX: 51.83MIN: 22.49 / MAX: 51.23


Phoronix Test Suite v10.8.5