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bits

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Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
bits
June 30
  3 Hours, 47 Minutes
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bitsOpenBenchmarking.orgPhoronix Test SuiteAMD EPYC 7543P 32-Core (4 Cores / 8 Threads)Blade Shadow ShadowM v2.0 (1.1.3 BIOS)Intel 82G33/G31/P35/P31 + ICH91 x 16GB RAM-2400MT/s Blade 2MEVPUH6DW9W57-PYL215GB QEMU HDDRed Hat QXL paravirtual graphic card 20GBRed Hat Virtio deviceUbuntu 22.045.15.0-113-generic (x86_64)X ServerNVIDIAOpenCL 3.0 CUDA 12.4.1311.3.277GCC 11.4.0ext41280x800KVMProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelDisplay ServerDisplay DriverOpenCLVulkanCompilerFile-SystemScreen ResolutionSystem LayerBits PerformanceSystem Logs- Transparent Huge Pages: madvise- CPU Microcode: 0xa0011d1- 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 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; BHI: Not affected + srbds: Not affected + tsx_async_abort: Not affected

bitstensorflow: GPU - 16 - VGG-16tensorflow: CPU - 16 - VGG-16tensorflow: GPU - 16 - ResNet-50pytorch: CPU - 16 - ResNet-50pytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 16 - ResNet-152tensorflow: CPU - 16 - ResNet-50tensorflow: GPU - 16 - GoogLeNettensorflow: GPU - 16 - AlexNettensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - AlexNetbits1.143.243.4114.573.835.848.4011.6114.4125.1543.81OpenBenchmarking.org

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: VGG-16bits0.25650.5130.76951.0261.2825SE +/- 0.00, N = 31.14

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: VGG-16bits0.7291.4582.1872.9163.645SE +/- 0.00, N = 33.24

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: ResNet-50bits0.76731.53462.30193.06923.8365SE +/- 0.00, N = 33.41

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: CPU - Batch Size: 16 - Model: ResNet-50bits48121620SE +/- 0.16, N = 1214.57MIN: 10.4 / MAX: 15.29

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lbits0.86181.72362.58543.44724.309SE +/- 0.00, N = 33.83MIN: 3.8 / MAX: 3.85

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152bits1.3142.6283.9425.2566.57SE +/- 0.04, N = 35.84MIN: 5.68 / MAX: 5.94

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: ResNet-50bits246810SE +/- 0.03, N = 38.40

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: GoogLeNetbits3691215SE +/- 0.07, N = 311.61

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: AlexNetbits48121620SE +/- 0.03, N = 314.41

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: GoogLeNetbits612182430SE +/- 0.10, N = 325.15

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: AlexNetbits1020304050SE +/- 0.10, N = 343.81