EPYC 7F32 Last

AMD EPYC 7F32 8-Core testing with a Supermicro H11DSi-NT v2.00 (2.1 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 2012274-HA-EPYC7F32L08
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Audio Encoding 4 Tests
Timed Code Compilation 2 Tests
CPU Massive 2 Tests
Creator Workloads 5 Tests
Encoding 4 Tests
HPC - High Performance Computing 2 Tests
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Programmer / Developer System Benchmarks 2 Tests

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Run 1
December 26 2020
  1 Hour, 54 Minutes
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December 26 2020
  1 Hour, 37 Minutes
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December 27 2020
  1 Hour, 38 Minutes
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December 27 2020
  1 Hour, 37 Minutes
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EPYC 7F32 Last Suite 1.0.0 System Test suite extracted from EPYC 7F32 Last. pts/ncnn-1.1.0 -1 Target: CPU - Model: googlenet pts/ncnn-1.1.0 -1 Target: CPU - Model: squeezenet_ssd pts/ncnn-1.1.0 -1 Target: CPU - Model: mnasnet pts/unpack-linux-1.1.1 linux-4.15.tar.xz pts/clomp-1.1.1 Static OMP Speedup pts/ncnn-1.1.0 -1 Target: CPU - Model: yolov4-tiny pts/onednn-1.6.1 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU pts/ncnn-1.1.0 -1 Target: CPU - Model: blazeface pts/onednn-1.6.1 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/ncnn-1.1.0 -1 Target: CPU - Model: efficientnet-b0 pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/ncnn-1.1.0 -1 Target: CPU - Model: regnety_400m pts/ncnn-1.1.0 -1 Target: CPU-v3-v3 - Model: mobilenet-v3 pts/unpack-firefox-1.0.0 Extracting: firefox-84.0.source.tar.xz pts/ncnn-1.1.0 -1 Target: CPU - Model: resnet18 pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/ncnn-1.1.0 -1 Target: CPU - Model: mobilenet pts/ncnn-1.1.0 -1 Target: CPU - Model: resnet50 pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/build2-1.1.0 Time To Compile pts/ncnn-1.1.0 -1 Target: CPU-v2-v2 - Model: mobilenet-v2 pts/onednn-1.6.1 --matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU pts/ncnn-1.1.0 -1 Target: CPU - Model: vgg16 pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU pts/ncnn-1.1.0 -1 Target: CPU - Model: shufflenet-v2 pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU pts/ncnn-1.1.0 -1 Target: CPU - Model: alexnet pts/build-eigen-1.1.0 Time To Compile pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU pts/onednn-1.6.1 --matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU pts/encode-ape-1.4.0 WAV To APE pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU pts/encode-ogg-1.6.1 WAV To Ogg pts/onednn-1.6.1 --ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.6.1 --deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU pts/encode-opus-1.1.1 WAV To Opus Encode pts/encode-wavpack-1.4.1 WAV To WavPack pts/onednn-1.6.1 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU