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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2402041-NE-HA1HYPERS87 ha1-hyperscalers-with-l40s-pytorch Processor: 2 x AMD EPYC 9174F 16-Core @ 4.10GHz (32 Cores / 63 Threads), Motherboard: ASUS RS700A-E12-RS4U K14PP-D24 (1002 BIOS), Chipset: AMD Device 14a4, Memory: 24 x 32 GB 4800MT/s Samsung M321R4GA3BB6-CQKEG, Disk: 500GB CT500P3PSSD8 + 3841GB DAPUSTOR DPH311T4T003T8 + 960GB HUSMR7696BDP3Y1, Graphics: llvmpipe, Monitor: ACER KA220HQ, Network: 2 x Intel X710 for 10GBASE-T + 2 x Intel X710 for 10GbE SFP+
OS: Ubuntu 20.04, Kernel: 5.15.0-91-generic (x86_64), Desktop: GNOME Shell 3.36.9, Display Server: X Server 1.20.13, Display Driver: NVIDIA 535.154.05, OpenGL: 4.5 Mesa 21.2.6 (LLVM 12.0.0 256 bits), OpenCL: OpenCL 3.0 CUDA 12.2.148, Vulkan: 1.3.242, Compiler: GCC 9.4.0, File-System: ext4, Screen Resolution: 1280x1024
Kernel Notes: Transparent Huge Pages: madviseProcessor Notes: Scaling Governor: acpi-cpufreq ondemand (Boost: Enabled) - CPU Microcode: 0xa10113ePython Notes: Python 3.8.10Security Notes: 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
PyTorch This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Currently this test profile is catered to CPU-based testing. Learn more via the OpenBenchmarking.org test page.
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 ha1-hyperscalers-with-l40s-pytorch 5 10 15 20 25 SE +/- 1.96, N = 12 19.41 MIN: 0.32 / MAX: 36.03
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 ha1-hyperscalers-with-l40s-pytorch 3 6 9 12 15 SE +/- 0.35, N = 12 10.11 MIN: 0.36 / MAX: 14.68
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 ha1-hyperscalers-with-l40s-pytorch 7 14 21 28 35 SE +/- 0.39, N = 3 31.25 MIN: 1.05 / MAX: 34.01
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 ha1-hyperscalers-with-l40s-pytorch 7 14 21 28 35 SE +/- 0.34, N = 3 31.18 MIN: 1.66 / MAX: 33.91
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 ha1-hyperscalers-with-l40s-pytorch 7 14 21 28 35 SE +/- 0.28, N = 3 30.06 MIN: 1.35 / MAX: 32.82
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 ha1-hyperscalers-with-l40s-pytorch 3 6 9 12 15 SE +/- 0.14, N = 4 11.86 MIN: 0.71 / MAX: 13.16
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 ha1-hyperscalers-with-l40s-pytorch 7 14 21 28 35 SE +/- 0.15, N = 3 29.90 MIN: 1.12 / MAX: 32.3
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 ha1-hyperscalers-with-l40s-pytorch 3 6 9 12 15 SE +/- 0.09, N = 12 11.90 MIN: 0.25 / MAX: 13.59
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 ha1-hyperscalers-with-l40s-pytorch 7 14 21 28 35 SE +/- 0.30, N = 3 29.50 MIN: 0.4 / MAX: 32.68
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 ha1-hyperscalers-with-l40s-pytorch 3 6 9 12 15 SE +/- 0.17, N = 3 11.87 MIN: 0.34 / MAX: 13.03
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 ha1-hyperscalers-with-l40s-pytorch 3 6 9 12 15 SE +/- 0.08, N = 3 12.00 MIN: 0.36 / MAX: 13.08
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-152 ha1-hyperscalers-with-l40s-pytorch 3 6 9 12 15 SE +/- 0.11, N = 6 11.70 MIN: 0.6 / MAX: 13.06
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l ha1-hyperscalers-with-l40s-pytorch 2 4 6 8 10 SE +/- 0.05, N = 3 7.44 MIN: 0.51 / MAX: 8.22
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l ha1-hyperscalers-with-l40s-pytorch 0.3015 0.603 0.9045 1.206 1.5075 SE +/- 0.00, N = 3 1.34 MIN: 0.41 / MAX: 1.95
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l ha1-hyperscalers-with-l40s-pytorch 0.3038 0.6076 0.9114 1.2152 1.519 SE +/- 0.01, N = 3 1.35 MIN: 0.71 / MAX: 1.9
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l ha1-hyperscalers-with-l40s-pytorch 0.306 0.612 0.918 1.224 1.53 SE +/- 0.01, N = 3 1.36 MIN: 0.84 / MAX: 1.89
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l ha1-hyperscalers-with-l40s-pytorch 0.306 0.612 0.918 1.224 1.53 SE +/- 0.00, N = 3 1.36 MIN: 0.61 / MAX: 1.94
OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l ha1-hyperscalers-with-l40s-pytorch 0.3038 0.6076 0.9114 1.2152 1.519 SE +/- 0.00, N = 3 1.35 MIN: 0.6 / MAX: 1.91
ha1-hyperscalers-with-l40s-pytorch Processor: 2 x AMD EPYC 9174F 16-Core @ 4.10GHz (32 Cores / 63 Threads), Motherboard: ASUS RS700A-E12-RS4U K14PP-D24 (1002 BIOS), Chipset: AMD Device 14a4, Memory: 24 x 32 GB 4800MT/s Samsung M321R4GA3BB6-CQKEG, Disk: 500GB CT500P3PSSD8 + 3841GB DAPUSTOR DPH311T4T003T8 + 960GB HUSMR7696BDP3Y1, Graphics: llvmpipe, Monitor: ACER KA220HQ, Network: 2 x Intel X710 for 10GBASE-T + 2 x Intel X710 for 10GbE SFP+
OS: Ubuntu 20.04, Kernel: 5.15.0-91-generic (x86_64), Desktop: GNOME Shell 3.36.9, Display Server: X Server 1.20.13, Display Driver: NVIDIA 535.154.05, OpenGL: 4.5 Mesa 21.2.6 (LLVM 12.0.0 256 bits), OpenCL: OpenCL 3.0 CUDA 12.2.148, Vulkan: 1.3.242, Compiler: GCC 9.4.0, File-System: ext4, Screen Resolution: 1280x1024
Kernel Notes: Transparent Huge Pages: madviseProcessor Notes: Scaling Governor: acpi-cpufreq ondemand (Boost: Enabled) - CPU Microcode: 0xa10113ePython Notes: Python 3.8.10Security Notes: 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
Testing initiated at 2 February 2024 15:58 by user root.