pytourch Resnet-50 R9-7950X-A600048GB

AMD Ryzen 9 7950X3D 16-Core testing with a MSI MAG X670E TOMAHAWK WIFI (MS-7E12) v1.0 (1.80 BIOS) and NVIDIA RTX A6000 48GB on Ubuntu 22.04 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 2407052-SIDD-PYTOURC67
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Result
Identifier
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Performance Per
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Date
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  Test
  Duration
Pytourch RESNET-50
July 05
  3 Minutes


pytourch Resnet-50 R9-7950X-A600048GBOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 7950X3D 16-Core @ 5.76GHz (16 Cores / 32 Threads)MSI MAG X670E TOMAHAWK WIFI (MS-7E12) v1.0 (1.80 BIOS)AMD Device 14d84 x 32GB DRAM-3600MT/s F5-6800J3445G32G2000GB Samsung SSD 990 PRO 2TB + 2 x 6001GB TOSHIBA MG08ADA6NVIDIA RTX A6000 48GBNVIDIA GA102 HD AudioBenQ GW2480LRealtek RTL8125 2.5GbE + MEDIATEK Device 0616Ubuntu 22.046.5.0-41-generic (x86_64)GNOME Shell 42.9X Server 1.21.1.4NVIDIA 535.183.014.6.0OpenCL 3.0 CUDA 12.2.1481.3.242GCC 11.4.0 + CUDA 12.2ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLVulkanCompilerFile-SystemScreen ResolutionPytourch Resnet-50 R9-7950X-A600048GB BenchmarksSystem Logs- Transparent Huge Pages: madvise- Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa601206 - Python 3.10.12- 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 + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS; IBPB: conditional; STIBP: always-on; RSB filling; PBRSB-eIBRS: Not affected; BHI: Not affected + srbds: Not affected + tsx_async_abort: Not affected

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50Pytourch RESNET-5080160240320400SE +/- 3.94, N = 15371.49MIN: 135.42 / MAX: 401.37