bits

bits

HTML result view exported from: https://openbenchmarking.org/result/2406302-NE-BITS3822089&grr.

bitsProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelDisplay DriverOpenCLVulkanCompilerFile-SystemScreen ResolutionSystem LayerbitsAMD 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 1IE18UKJRN5SEN-HKA215GB QEMU HDDRed Hat QXL paravirtual graphic card 20GBRed Hat Virtio deviceUbuntu 22.045.15.0-113-generic (x86_64)NVIDIAOpenCL 3.0 CUDA 12.4.891.3.277GCC 11.4.0ext41280x800KVMOpenBenchmarking.org- 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-16pytorch: CPU - 16 - Efficientnet_v2_ltensorflow: CPU - 16 - VGG-16tensorflow: GPU - 16 - ResNet-50pytorch: CPU - 16 - ResNet-152tensorflow: CPU - 16 - ResNet-50tensorflow: GPU - 16 - GoogLeNettensorflow: GPU - 16 - AlexNetpytorch: CPU - 16 - ResNet-50tensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - AlexNetbits1.144.113.243.445.858.4211.7514.4115.1625.5943.77OpenBenchmarking.org

TensorFlow

Device: GPU - Batch Size: 16 - Model: VGG-16

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

PyTorch

Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lbits0.92481.84962.77443.69924.624SE +/- 0.05, N = 94.11MIN: 3.73 / MAX: 4.36

TensorFlow

Device: CPU - Batch Size: 16 - Model: VGG-16

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

TensorFlow

Device: GPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: ResNet-50bits0.7741.5482.3223.0963.87SE +/- 0.02, N = 33.44

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152bits1.31632.63263.94895.26526.5815SE +/- 0.04, N = 35.85MIN: 5.18 / MAX: 5.94

TensorFlow

Device: CPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: ResNet-50bits246810SE +/- 0.04, N = 38.42

TensorFlow

Device: GPU - Batch Size: 16 - Model: GoogLeNet

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: GoogLeNetbits3691215SE +/- 0.01, N = 311.75

TensorFlow

Device: GPU - Batch Size: 16 - Model: AlexNet

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: AlexNetbits48121620SE +/- 0.00, N = 314.41

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50bits48121620SE +/- 0.18, N = 315.16MIN: 13.27 / MAX: 15.71

TensorFlow

Device: CPU - Batch Size: 16 - Model: GoogLeNet

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: GoogLeNetbits612182430SE +/- 0.05, N = 325.59

TensorFlow

Device: CPU - Batch Size: 16 - Model: AlexNet

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: AlexNetbits1020304050SE +/- 0.14, N = 343.77

Phoronix Test Suite v10.8.5