start-q2-2022-epyc

2 x AMD EPYC 7773X 64-Core testing with a AMD DAYTONA_X (TYM1008C BIOS) and ASPEED 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 2204090-NE-STARTQ22075
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BLAS (Basic Linear Algebra Sub-Routine) Tests 3 Tests
Chess Test Suite 2 Tests
Timed Code Compilation 6 Tests
C/C++ Compiler Tests 5 Tests
CPU Massive 12 Tests
Creator Workloads 13 Tests
Fortran Tests 5 Tests
Game Development 5 Tests
HPC - High Performance Computing 15 Tests
Java 2 Tests
LAPACK (Linear Algebra Pack) Tests 2 Tests
Linear Algebra 2 Tests
Machine Learning 2 Tests
Molecular Dynamics 5 Tests
MPI Benchmarks 6 Tests
Multi-Core 24 Tests
NVIDIA GPU Compute 3 Tests
Intel oneAPI 5 Tests
OpenMPI Tests 11 Tests
Programmer / Developer System Benchmarks 8 Tests
Python Tests 5 Tests
Quantum Mechanics 2 Tests
Raytracing 3 Tests
Renderers 5 Tests
Scientific Computing 9 Tests
Server CPU Tests 9 Tests
Texture Compression 2 Tests
Common Workstation Benchmarks 2 Tests

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Identifier
Performance Per
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Date
Run
  Test
  Duration
EPYC 75F3 2P A
March 31 2022
  3 Hours, 13 Minutes
2 x AMD EPYC 75F3 32-Core
March 31 2022
  2 Hours, 50 Minutes
7573X 1P A
March 31 2022
  2 Hours, 18 Minutes
EPYC 7573X
March 31 2022
  3 Hours, 36 Minutes
AMD EPYC 7373X
April 01 2022
  3 Hours, 27 Minutes
EPYC 7573X 2P
April 01 2022
  3 Hours, 39 Minutes
7573X 2P AMD
April 01 2022
  2 Hours, 46 Minutes
EPYC 7763
April 01 2022
  8 Hours, 22 Minutes
EPYC 7763 1P
April 02 2022
  3 Hours, 41 Minutes
AMD 7763
April 02 2022
  8 Hours, 19 Minutes
AMD EPYC 7763
April 02 2022
  46 Minutes
EPYC 7763 2P
April 02 2022
  6 Hours, 38 Minutes
AMD 7763 2P
April 03 2022
  3 Hours, 58 Minutes
7763 2P
April 03 2022
  4 Hours, 13 Minutes
7763 TwoP
April 07 2022
  9 Minutes
7773X 1P
April 07 2022
  3 Hours, 36 Minutes
EPYC 7773X
April 07 2022
  3 Hours, 38 Minutes
AMD EPYC 7773X
April 07 2022
  2 Hours, 27 Minutes
7773X AMD
April 07 2022
  7 Hours, 58 Minutes
EPYC 7773X 2P
April 08 2022
  3 Hours, 10 Minutes
AMD EPYC 7773X 2P
April 08 2022
  4 Hours, 11 Minutes
AMD 7773X 2P
April 08 2022
  4 Hours, 5 Minutes
7773X 2P AMD
April 08 2022
  6 Hours, 15 Minutes
Q
April 09 2022
  2 Hours, 37 Minutes
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  4 Hours

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start-q2-2022-epyc Suite 1.0.0 System Test suite extracted from start-q2-2022-epyc . pts/wrf-1.0.1 -i conus 2.5km Input: conus 2.5km pts/brl-cad-1.2.0 VGR Performance Metric pts/openvkl-1.1.0 vklBenchmark --benchmark_filter=ispc Benchmark: vklBenchmark ISPC pts/openvkl-1.1.0 vklBenchmark --benchmark_filter=scalar Benchmark: vklBenchmark Scalar pts/java-jmh-1.0.1 Throughput pts/incompact3d-2.0.2 input.i3d Input: X3D-benchmarking input.i3d pts/java-gradle-perf-1.1.0 TEST_REACTOR Gradle Build: Reactor pts/askap-2.1.0 tConvolveMT Test: tConvolve MT - Degridding pts/askap-2.1.0 tConvolveMT Test: tConvolve MT - Gridding pts/qe-1.3.1 ausurf.in Input: AUSURF112 pts/ospray-2.9.0 --benchmark_filter=particle_volume/pathtracer/real_time Benchmark: particle_volume/pathtracer/real_time pts/ospray-2.9.0 --benchmark_filter=particle_volume/scivis/real_time Benchmark: particle_volume/scivis/real_time pts/relion-1.0.1 --iter 1 --cpu --j 2 Test: Basic - Device: CPU pts/lammps-1.3.2 benchmark_20k_atoms.in Model: 20k Atoms pts/blender-3.0.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: Barbershop - Compute: CPU-Only pts/build-linux-kernel-1.13.0 allmodconfig Build: allmodconfig pts/build-llvm-1.4.0 Build System: Unix Makefiles pts/ospray-2.9.0 --benchmark_filter=particle_volume/ao/real_time Benchmark: particle_volume/ao/real_time pts/ospray-studio-1.0.1 --cameras 1 1 --resolution 1920 1080 --spp 32 --renderer pathtracer Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer pts/ospray-studio-1.0.1 --cameras 2 2 --resolution 1920 1080 --spp 32 --renderer pathtracer Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer pts/ospray-studio-1.0.1 --cameras 1 1 --resolution 1920 1080 --spp 16 --renderer pathtracer Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer pts/ospray-studio-1.0.1 --cameras 2 2 --resolution 1920 1080 --spp 16 --renderer pathtracer Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer pts/ospray-studio-1.0.1 --cameras 3 3 --resolution 1920 1080 --spp 1 --renderer pathtracer Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer pts/ospray-studio-1.0.1 --cameras 2 2 --resolution 1920 1080 --spp 1 --renderer pathtracer Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer pts/ospray-studio-1.0.1 --cameras 3 3 --resolution 1920 1080 --spp 16 --renderer pathtracer Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer pts/ospray-studio-1.0.1 --cameras 1 1 --resolution 1920 1080 --spp 1 --renderer pathtracer Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer pts/ospray-studio-1.0.1 --cameras 3 3 --resolution 1920 1080 --spp 32 --renderer pathtracer Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer pts/build-nodejs-1.1.1 Time To Compile pts/build-llvm-1.4.0 Ninja Build System: Ninja pts/asmfish-1.1.2 1024 Hash Memory, 26 Depth pts/onnx-1.5.0 GPT2/model.onnx -e cpu Model: GPT-2 - Device: CPU - Executor: Standard pts/onnx-1.5.0 fcn-resnet101-11/model.onnx -e cpu -P Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 GPT2/model.onnx -e cpu -P Model: GPT-2 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 bertsquad-12/bertsquad-12.onnx -e cpu -P Model: bertsquad-12 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 resnet100/resnet100.onnx -e cpu -P Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 yolov4/yolov4.onnx -e cpu -P Model: yolov4 - Device: CPU - Executor: Parallel pts/onnx-1.5.0 fcn-resnet101-11/model.onnx -e cpu Model: fcn-resnet101-11 - Device: CPU - Executor: Standard pts/onnx-1.5.0 resnet100/resnet100.onnx -e cpu Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard pts/onnx-1.5.0 bertsquad-12/bertsquad-12.onnx -e cpu Model: bertsquad-12 - Device: CPU - Executor: Standard pts/onnx-1.5.0 yolov4/yolov4.onnx -e cpu Model: yolov4 - Device: CPU - Executor: Standard pts/onnx-1.5.0 super_resolution/super_resolution.onnx -e cpu Model: super-resolution-10 - Device: CPU - Executor: Standard pts/onnx-1.5.0 super_resolution/super_resolution.onnx -e cpu -P Model: super-resolution-10 - Device: CPU - Executor: Parallel pts/avifenc-1.2.0 -s 0 Encoder Speed: 0 pts/ospray-2.9.0 --benchmark_filter=gravity_spheres_volume/dim_512/pathtracer/real_time Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time pts/ospray-2.9.0 --benchmark_filter=gravity_spheres_volume/dim_512/scivis/real_time Benchmark: gravity_spheres_volume/dim_512/scivis/real_time pts/ospray-2.9.0 --benchmark_filter=gravity_spheres_volume/dim_512/ao/real_time Benchmark: gravity_spheres_volume/dim_512/ao/real_time pts/onednn-1.8.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.8.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.8.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU pts/onednn-1.8.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU pts/onednn-1.8.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.8.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU pts/blender-3.0.0 -b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: Pabellon Barcelona - Compute: CPU-Only pts/build-wasmer-1.1.0 Time To Compile pts/avifenc-1.2.0 -s 2 Encoder Speed: 2 pts/luxcorerender-1.4.0 OrangeJuice/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: Orange Juice - Acceleration: CPU pts/blender-3.0.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: Classroom - Compute: CPU-Only pts/luxcorerender-1.4.0 DanishMood/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: Danish Mood - Acceleration: CPU pts/luxcorerender-1.4.0 LuxCore2.1Benchmark/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: LuxCore Benchmark - Acceleration: CPU pts/luxcorerender-1.4.0 DLSC/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: DLSC - Acceleration: CPU pts/rocksdb-1.2.0 --benchmarks="updaterandom" Test: Update Random pts/rocksdb-1.2.0 --benchmarks="readrandomwriterandom" Test: Read Random Write Random pts/rocksdb-1.2.0 --benchmarks="readwhilewriting" Test: Read While Writing pts/rocksdb-1.2.0 --benchmarks="readrandom" Test: Random Read pts/build-godot-1.0.0 Time To Compile pts/toktx-1.0.1 --uastc 4 --zcmp 19 Settings: UASTC 4 + Zstd Compression 19 pts/gpaw-1.1.0 carbon-nanotube Input: Carbon Nanotube pts/gromacs-1.6.0 mpi-build water-cut1.0_GMX50_bare/1536 Implementation: MPI CPU - Input: water_GMX50_bare pts/amg-1.1.0 pts/blender-3.0.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: Fishy Cat - Compute: CPU-Only pts/npb-1.4.5 ep.D Test / Class: EP.D pts/askap-2.1.0 tConvolveMPI Test: tConvolve MPI - Gridding pts/askap-2.1.0 tConvolveMPI Test: tConvolve MPI - Degridding pts/blender-3.0.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: BMW27 - Compute: CPU-Only pts/build-linux-kernel-1.13.0 defconfig Build: defconfig pts/embree-1.2.1 pathtracer_ispc -c asian_dragon_obj/asian_dragon.ecs Binary: Pathtracer ISPC - Model: Asian Dragon Obj pts/embree-1.2.1 pathtracer -c asian_dragon_obj/asian_dragon.ecs Binary: Pathtracer - Model: Asian Dragon Obj pts/coremark-1.0.1 CoreMark Size 666 - Iterations Per Second pts/namd-1.2.1 ATPase Simulation - 327,506 Atoms pts/npb-1.4.5 bt.C Test / Class: BT.C pts/stockfish-1.3.0 Total Time pts/toktx-1.0.1 --zcmp 19 Settings: Zstd Compression 19 pts/onednn-1.8.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU pts/onednn-1.8.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU pts/liquid-dsp-1.0.0 -n 64 -b 256 -f 57 Threads: 64 - Buffer Length: 256 - Filter Length: 57 pts/liquid-dsp-1.0.0 -n 128 -b 256 -f 57 Threads: 128 - Buffer Length: 256 - Filter Length: 57 pts/lulesh-1.1.1 pts/incompact3d-2.0.2 input_193_nodes.i3d Input: input.i3d 193 Cells Per Direction pts/npb-1.4.5 sp.C Test / Class: SP.C pts/askap-2.1.0 tHogbomCleanOMP Test: Hogbom Clean OpenMP pts/onednn-1.8.0 --ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU pts/onednn-1.8.0 --ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU pts/npb-1.4.5 is.D Test / Class: IS.D pts/povray-1.2.1 Trace Time pts/avifenc-1.2.0 -s 6 -l Encoder Speed: 6, Lossless pts/onednn-1.8.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU pts/onednn-1.8.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU pts/avifenc-1.2.0 -s 10 -l Encoder Speed: 10, Lossless pts/npb-1.4.5 lu.C Test / Class: LU.C pts/build-mplayer-1.5.0 Time To Compile pts/askap-2.1.0 tConvolveOMP Test: tConvolve OpenMP - Degridding pts/embree-1.2.1 pathtracer_ispc -c asian_dragon/asian_dragon.ecs Binary: Pathtracer ISPC - Model: Asian Dragon pts/toktx-1.0.1 --uastc 3 --zcmp 19 Settings: UASTC 3 + Zstd Compression 19 pts/embree-1.2.1 pathtracer_ispc -c crown/crown.ecs Binary: Pathtracer ISPC - Model: Crown pts/askap-2.1.0 tConvolveOMP Test: tConvolve OpenMP - Gridding pts/embree-1.2.1 pathtracer -c asian_dragon/asian_dragon.ecs Binary: Pathtracer - Model: Asian Dragon pts/luxcorerender-1.4.0 RainbowColorsAndPrism/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: Rainbow Colors and Prism - Acceleration: CPU pts/onednn-1.8.0 --ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU pts/onednn-1.8.0 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/embree-1.2.1 pathtracer -c crown/crown.ecs Binary: Pathtracer - Model: Crown pts/draco-1.5.0 -i church.ply Model: Church Facade pts/mt-dgemm-1.2.0 Sustained Floating-Point Rate pts/npb-1.4.5 ft.C Test / Class: FT.C pts/draco-1.5.0 -i lion.ply Model: Lion pts/onednn-1.8.0 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/onednn-1.8.0 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/avifenc-1.2.0 -s 6 Encoder Speed: 6 pts/npb-1.4.5 cg.C Test / Class: CG.C pts/incompact3d-2.0.2 input_129_nodes.i3d Input: input.i3d 129 Cells Per Direction pts/npb-1.4.5 sp.B Test / Class: SP.B pts/toktx-1.0.1 --uastc 3 Settings: UASTC 3 pts/npb-1.4.5 ep.C Test / Class: EP.C pts/npb-1.4.5 mg.C Test / Class: MG.C pts/toktx-1.0.1 --zcmp 9 Settings: Zstd Compression 9 pts/onednn-1.8.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU pts/onednn-1.8.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU pts/lammps-1.3.2 in.rhodo Model: Rhodopsin Protein pts/onednn-1.8.0 --ip --batch=inputs/ip/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.8.0 --conv --batch=inputs/conv/shapes_auto --cfg=bf16bf16bf16 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.8.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=bf16bf16bf16 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.8.0 --ip --batch=inputs/ip/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.8.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.8.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU