gpu-server-2u

2 x Intel Xeon E5-2697 v4 testing with a Dell PowerEdge R730 [0WCJNT] (2.19.0 BIOS) and NVIDIA GA102GL [RTX A5000] 24GB 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 2404153-NE-GPUSERVER09
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GPU-SERVER-2U-2xA5000
April 15
  1 Minute
2 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX
April 15
  28 Minutes
NVIDIA GA102GL
April 15
  1 Minute
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gpu-server-2uProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDisplay DriverVulkanCompilerFile-SystemScreen ResolutionOpenCLGPU-SERVER-2U-2xA50002 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTXNVIDIA GA102GL2 x Intel Xeon E5-2697 v4 @ 3.60GHz (36 Cores / 72 Threads)Dell PowerEdge R730 [0WCJNT] (2.19.0 BIOS)Intel Xeon E7 v4/Xeon8 x 32 GB DDR4-2400MT/s M393A4K40CB1-CRC2 x 1920GB SAMSUNG MZ7LH1T9NVIDIA GA102GL [RTX A5000] 24GBNVIDIA GA102 HD Audio2 x Intel 10-Gigabit X540-AT2 + 2 x Intel I350Ubuntu 22.045.15.0-102-generic (x86_64)NVIDIA1.3.277GCC 12.3.0ext41024x768OpenCL 3.0 CUDA 12.4.125OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseProcessor Details- GPU-SERVER-2U-2xA5000: Scaling Governor: intel_cpufreq schedutil - CPU Microcode: 0xb000040- 2 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX: Scaling Governor: intel_cpufreq performance - CPU Microcode: 0xb000040- NVIDIA GA102GL: Scaling Governor: intel_cpufreq performance - CPU Microcode: 0xb000040Python Details- GPU-SERVER-2U-2xA5000, 2 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX: Python 3.10.12Security Details- gather_data_sampling: Not affected + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Mitigation of PTE Inversion; VMX: conditional cache flushes SMT vulnerable + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Mitigation of PTI + mmio_stale_data: Mitigation of Clear buffers; SMT vulnerable + retbleed: Not affected + spec_rstack_overflow: Not affected + 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: Mitigation of Clear buffers; SMT vulnerable Graphics Details- NVIDIA GA102GL: BAR1 / Visible vRAM Size: 256 MiB - vBIOS Version: 94.02.6d.00.0d

gpu-server-2upytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: NVIDIA CUDA GPU - 512 - ResNet-152hashcat: SHA-512GPU-SERVER-2U-2xA50002 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTXNVIDIA GA102GL27.4810.3923.1022.5723.8433.723986400000OpenBenchmarking.org

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

GPU-SERVER-2U-2xA5000: The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'warnings'. Did you mean: 'hanning'?

2 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX: The test quit with a non-zero exit status. E: AttributeError: module 'numpy' has no attribute 'warnings'. Did you mean: 'hanning'?

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-502 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX612182430SE +/- 0.37, N = 327.48MIN: 11.6 / MAX: 29.11

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-1522 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX3691215SE +/- 0.10, N = 310.39MIN: 7.26 / MAX: 11.03

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-502 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX612182430SE +/- 0.19, N = 323.10MIN: 16.52 / MAX: 24.05

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-502 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX510152025SE +/- 0.27, N = 322.57MIN: 16.36 / MAX: 23.62

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-502 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX612182430SE +/- 0.29, N = 323.84MIN: 17.15 / MAX: 24.64

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-1522 x Intel Xeon E5-2697 v4 - NVIDIA GA102GL [RTX816243240SE +/- 0.10, N = 333.72MIN: 29.31 / MAX: 34.08

Hashcat

Hashcat is an open-source, advanced password recovery tool supporting GPU acceleration with OpenCL, NVIDIA CUDA, and Radeon ROCm. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterHashcat 6.2.4Benchmark: SHA-512NVIDIA GA102GL900M1800M2700M3600M4500MSE +/- 5750652.14, N = 33986400000