bench_bytorch_GPU_all

bench_bytorch_GPU_all wsl testing on Ubuntu 22.04 via the Phoronix

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2403304-NE-BENCHBYTO71
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Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
bench_bytorch_GPU_all
March 30
  7 Minutes
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bench_bytorch_GPU_allOpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 9 7950X 16-Core (16 Cores / 32 Threads)64GB0GB Virtual Disk + 17GB Virtual Disk + 1100GB Virtual DiskNVIDIA GeForce RTX 4090 24GBUbuntu 22.045.15.146.1-microsoft-standard-WSL2 (x86_64)Waylandnouveau4.2 Mesa 23.2.1-1ubuntu3.1~22.04.21.3.255GCC 11.4.0ext4wslProcessorMemoryDiskGraphicsOSKernelDisplay ServerDisplay DriverOpenGLVulkanCompilerFile-SystemSystem LayerBench_bytorch_GPU_all BenchmarksSystem Logs- Transparent Huge Pages: always- CPU Microcode: 0xffffffff- 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 no microcode + 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: conditional RSB filling PBRSB-eIBRS: 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: 1 - Model: Efficientnet_v2_lbench_bytorch_GPU_all1326395265SE +/- 0.71, N = 1560.31MIN: 11.34 / MAX: 66.39

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152bench_bytorch_GPU_all306090120150SE +/- 1.28, N = 3127.87MIN: 38.04 / MAX: 134.51

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50bench_bytorch_GPU_all80160240320400SE +/- 1.19, N = 3359.62MIN: 112.01 / MAX: 374.79