tri

tri

HTML result view exported from: https://openbenchmarking.org/result/2407017-NE-TRI91491891&grw.

triProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelDisplay ServerDisplay DriverOpenCLVulkanCompilerFile-SystemScreen ResolutionSystem LayertriAMD 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 11.4.0ext41280x800KVMOpenBenchmarking.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

tritensorflow: CPU - 16 - VGG-16tensorflow: GPU - 16 - VGG-16tensorflow: CPU - 16 - AlexNettensorflow: GPU - 16 - AlexNettensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - ResNet-50tensorflow: GPU - 16 - GoogLeNettensorflow: GPU - 16 - ResNet-50ai-benchmark: Device Inference Scoreai-benchmark: Device Training Scoreai-benchmark: Device AI Scorepytorch: CPU - 16 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 16 - Efficientnet_v2_ltri3.251.1444.2214.4425.548.5311.623.40716814153014.815.763.88OpenBenchmarking.org

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: VGG-16tri0.73131.46262.19392.92523.6565SE +/- 0.00, N = 33.25

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: VGG-16tri0.25650.5130.76951.0261.2825SE +/- 0.00, N = 31.14

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: AlexNettri1020304050SE +/- 0.04, N = 344.22

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: AlexNettri48121620SE +/- 0.01, N = 314.44

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: GoogLeNettri612182430SE +/- 0.06, N = 325.54

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: ResNet-50tri246810SE +/- 0.03, N = 38.53

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: GoogLeNettri3691215SE +/- 0.06, N = 311.62

TensorFlow

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

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: GPU - Batch Size: 16 - Model: ResNet-50tri0.7651.532.2953.063.825SE +/- 0.01, N = 33.40

AI Benchmark Alpha

Device Inference Score

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device Inference Scoretri150300450600750716

AI Benchmark Alpha

Device Training Score

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device Training Scoretri2004006008001000814

AI Benchmark Alpha

Device AI Score

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device AI Scoretri300600900120015001530

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50tri48121620SE +/- 0.03, N = 314.81MIN: 14.22 / MAX: 15.13

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152tri1.2962.5923.8885.1846.48SE +/- 0.04, N = 35.76MIN: 5.11 / MAX: 5.88

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_ltri0.8731.7462.6193.4924.365SE +/- 0.05, N = 93.88MIN: 3.53 / MAX: 4.09

Phoronix Test Suite v10.8.5