ha1-hyperscalers-with-l40s-pytorch

2 x AMD EPYC 9174F 16-Core testing with a ASUS RS700A-E12-RS4U K14PP-D24 (1002 BIOS) and llvmpipe on Ubuntu 20.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2402041-NE-HA1HYPERS87&grw.

ha1-hyperscalers-with-l40s-pytorchProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLVulkanCompilerFile-SystemScreen Resolutionha1-hyperscalers-with-l40s-pytorch2 x AMD EPYC 9174F 16-Core @ 4.10GHz (32 Cores / 63 Threads)ASUS RS700A-E12-RS4U K14PP-D24 (1002 BIOS)AMD Device 14a424 x 32 GB 4800MT/s Samsung M321R4GA3BB6-CQKEG500GB CT500P3PSSD8 + 3841GB DAPUSTOR DPH311T4T003T8 + 960GB HUSMR7696BDP3Y1llvmpipeACER KA220HQ2 x Intel X710 for 10GBASE-T + 2 x Intel X710 for 10GbE SFP+Ubuntu 20.045.15.0-91-generic (x86_64)GNOME Shell 3.36.9X Server 1.20.13NVIDIA 535.154.054.5 Mesa 21.2.6 (LLVM 12.0.0 256 bits)OpenCL 3.0 CUDA 12.2.1481.3.242GCC 9.4.0ext41280x1024OpenBenchmarking.org- Transparent Huge Pages: madvise- Scaling Governor: acpi-cpufreq ondemand (Boost: Enabled) - CPU Microcode: 0xa10113e- Python 3.8.10- 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 and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

ha1-hyperscalers-with-l40s-pytorchpytorch: 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_lha1-hyperscalers-with-l40s-pytorch19.4110.1131.2531.1830.0611.8629.9011.9029.5011.8712.0011.707.441.341.351.361.361.35OpenBenchmarking.org

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ha1-hyperscalers-with-l40s-pytorch510152025SE +/- 1.96, N = 1219.41MIN: 0.32 / MAX: 36.03

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152ha1-hyperscalers-with-l40s-pytorch3691215SE +/- 0.35, N = 1210.11MIN: 0.36 / MAX: 14.68

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ha1-hyperscalers-with-l40s-pytorch714212835SE +/- 0.39, N = 331.25MIN: 1.05 / MAX: 34.01

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50ha1-hyperscalers-with-l40s-pytorch714212835SE +/- 0.34, N = 331.18MIN: 1.66 / MAX: 33.91

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50ha1-hyperscalers-with-l40s-pytorch714212835SE +/- 0.28, N = 330.06MIN: 1.35 / MAX: 32.82

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ha1-hyperscalers-with-l40s-pytorch3691215SE +/- 0.14, N = 411.86MIN: 0.71 / MAX: 13.16

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50ha1-hyperscalers-with-l40s-pytorch714212835SE +/- 0.15, N = 329.90MIN: 1.12 / MAX: 32.3

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ha1-hyperscalers-with-l40s-pytorch3691215SE +/- 0.09, N = 1211.90MIN: 0.25 / MAX: 13.59

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50ha1-hyperscalers-with-l40s-pytorch714212835SE +/- 0.30, N = 329.50MIN: 0.4 / MAX: 32.68

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152ha1-hyperscalers-with-l40s-pytorch3691215SE +/- 0.17, N = 311.87MIN: 0.34 / MAX: 13.03

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152ha1-hyperscalers-with-l40s-pytorch3691215SE +/- 0.08, N = 312.00MIN: 0.36 / MAX: 13.08

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152ha1-hyperscalers-with-l40s-pytorch3691215SE +/- 0.11, N = 611.70MIN: 0.6 / MAX: 13.06

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lha1-hyperscalers-with-l40s-pytorch246810SE +/- 0.05, N = 37.44MIN: 0.51 / MAX: 8.22

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lha1-hyperscalers-with-l40s-pytorch0.30150.6030.90451.2061.5075SE +/- 0.00, N = 31.34MIN: 0.41 / MAX: 1.95

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lha1-hyperscalers-with-l40s-pytorch0.30380.60760.91141.21521.519SE +/- 0.01, N = 31.35MIN: 0.71 / MAX: 1.9

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lha1-hyperscalers-with-l40s-pytorch0.3060.6120.9181.2241.53SE +/- 0.01, N = 31.36MIN: 0.84 / MAX: 1.89

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lha1-hyperscalers-with-l40s-pytorch0.3060.6120.9181.2241.53SE +/- 0.00, N = 31.36MIN: 0.61 / MAX: 1.94

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lha1-hyperscalers-with-l40s-pytorch0.30380.60760.91141.21521.519SE +/- 0.00, N = 31.35MIN: 0.6 / MAX: 1.91

Phoronix Test Suite v10.8.4