xeon-platinum-8380-2p-smoke-run

2 x Intel Xeon Platinum 8380 testing with a Intel M50CYP2SB2U (SE5C6200.86B.0022.D08.2103221623 BIOS) and ASPEED 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 2105012-IB-XEONPLATI04
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AV1 2 Tests
Timed Code Compilation 6 Tests
C/C++ Compiler Tests 6 Tests
CPU Massive 11 Tests
Creator Workloads 13 Tests
Cryptography 3 Tests
Encoding 4 Tests
Game Development 5 Tests
HPC - High Performance Computing 4 Tests
Imaging 2 Tests
Machine Learning 2 Tests
Molecular Dynamics 2 Tests
Multi-Core 16 Tests
NVIDIA GPU Compute 3 Tests
OpenMPI Tests 2 Tests
Programmer / Developer System Benchmarks 6 Tests
Python Tests 5 Tests
Renderers 2 Tests
Scientific Computing 2 Tests
Software Defined Radio 4 Tests
Server CPU Tests 11 Tests
Single-Threaded 3 Tests
Texture Compression 4 Tests
Video Encoding 4 Tests
Common Workstation Benchmarks 2 Tests

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  Test
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r1
April 28 2021
  1 Day, 1 Minute
r1a
April 29 2021
  11 Hours, 50 Minutes
r2
April 29 2021
  1 Minute
r2a
April 29 2021
  1 Hour, 9 Minutes
r2b
April 29 2021
  18 Hours, 2 Minutes
r3
April 30 2021
  17 Hours, 57 Minutes
r4
April 30 2021
  17 Hours, 55 Minutes
r5
May 01 2021
  46 Minutes
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xeon-platinum-8380-2p-smoke-run Suite 1.0.0 System Test suite extracted from xeon-platinum-8380-2p-smoke-run . pts/onednn-1.7.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU pts/aom-av1-2.3.0 --cpu-used=9 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p pts/aom-av1-2.3.0 --cpu-used=8 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p pts/aom-av1-2.3.0 --cpu-used=6 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p pts/aom-av1-2.3.0 --cpu-used=6 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p pts/aom-av1-2.3.0 --cpu-used=6 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K pts/aom-av1-2.3.0 --cpu-used=8 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K pts/aom-av1-2.3.0 --cpu-used=6 Bosphorus_3840x2160.y4m Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K pts/aom-av1-2.3.0 --cpu-used=9 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K pts/svt-vp9-1.3.0 -tune 1 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p pts/svt-hevc-1.2.0 -encMode 10 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: 10 - Input: Bosphorus 1080p pts/intel-mlc-1.0.0 --idle_latency Test: Idle Latency pts/aom-av1-2.3.0 --cpu-used=4 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p pts/aom-av1-2.3.0 --cpu-used=4 Bosphorus_3840x2160.y4m Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K pts/svt-vp9-1.3.0 -tune 0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p pts/svt-hevc-1.2.0 -encMode 7 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: 7 - Input: Bosphorus 1080p pts/build-erlang-1.1.0 Time To Compile pts/aom-av1-2.3.0 --cpu-used=0 --limit=20 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p pts/luxcorerender-1.3.0 LuxCore2.1Benchmark/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: LuxCore Benchmark - Acceleration: CPU pts/aom-av1-2.3.0 --cpu-used=0 --limit=20 Bosphorus_3840x2160.y4m Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K pts/svt-hevc-1.2.0 -encMode 1 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: 1 - Input: Bosphorus 1080p pts/luxcorerender-1.3.0 DanishMood/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: Danish Mood - Acceleration: CPU pts/incompact3d-2.0.2 input_129_nodes.i3d Input: input.i3d 129 Cells Per Direction pts/incompact3d-2.0.2 input_193_nodes.i3d Input: input.i3d 193 Cells Per Direction pts/incompact3d-2.0.2 input.i3d Input: X3D-benchmarking input.i3d pts/avifenc-1.1.1 -s 6 Encoder Speed: 6 pts/avifenc-1.1.1 -s 6 -l Encoder Speed: 6, Lossless pts/avifenc-1.1.1 -s 2 Encoder Speed: 2 pts/luaradio-1.0.0 Test: Complex Phase pts/avifenc-1.1.1 -s 10 -l Encoder Speed: 10, Lossless pts/build-wasmer-1.0.0 Time To Compile pts/build-linux-kernel-1.11.0 Time To Compile pts/avifenc-1.1.1 -s 0 Encoder Speed: 0 pts/luaradio-1.0.0 Test: FM Deemphasis Filter pts/build-nodejs-1.0.0 Time To Compile pts/xmrig-1.0.0 --bench=1M Variant: Monero - Hash Count: 1M pts/build-mesa-1.0.0 Time To Compile pts/luxcorerender-1.3.0 DLSC/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: DLSC - Acceleration: CPU pts/build-llvm-1.3.1 Build System: Unix Makefiles pts/mnn-1.2.0 Model: mobilenet-v1-1.0 pts/liquid-dsp-1.0.0 -n 1 -b 256 -f 57 Threads: 1 - Buffer Length: 256 - Filter Length: 57 pts/xmrig-1.0.0 -a rx/wow --bench=1M Variant: Wownero - Hash Count: 1M pts/srslte-1.0.1 lib/test/phy/phy_dl_test -p 100 -s 20000 -m 28 Test: PHY_DL_Test pts/toybrot-1.2.0 raymarched/STDTASKS/rmSTD_TASKS Implementation: C++ Tasks pts/stockfish-1.3.0 Total Time pts/vosk-1.0.1 pts/onednn-1.7.0 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/liquid-dsp-1.0.0 -n 16 -b 256 -f 57 Threads: 16 - Buffer Length: 256 - Filter Length: 57 pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU pts/luxcorerender-1.3.0 OrangeJuice/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: Orange Juice - Acceleration: CPU pts/liquid-dsp-1.0.0 -n 8 -b 256 -f 57 Threads: 8 - Buffer Length: 256 - Filter Length: 57 pts/onednn-1.7.0 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/toybrot-1.2.0 raymarched/STDTHREADS/rmSTD_THREADS Implementation: C++ Threads pts/hammerdb-mariadb-1.0.0 64 500 Virtual Users: 64 - Warehouses: 500 pts/gmpbench-1.3.0 Total Time pts/tjbench-1.2.0 decompression-throughput Test: Decompression Throughput pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/luaradio-1.0.0 Test: Hilbert Transform pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU pts/toybrot-1.2.0 raymarched/TBB/rmTBB Implementation: TBB pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU pts/liquid-dsp-1.0.0 -n 32 -b 256 -f 57 Threads: 32 - Buffer Length: 256 - Filter Length: 57 pts/mysqlslap-1.1.1 --concurrency=4 Clients: 4 pts/liquid-dsp-1.0.0 -n 4 -b 256 -f 57 Threads: 4 - Buffer Length: 256 - Filter Length: 57 pts/intel-mlc-1.0.0 -X --peak_injection_bandwidth Test: Peak Injection Bandwidth - 1:1 Reads-Writes pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU pts/build-llvm-1.3.1 Ninja Build System: Ninja pts/onednn-1.7.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU pts/liquid-dsp-1.0.0 -n 2 -b 256 -f 57 Threads: 2 - 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/toktx-1.0.0 --uastc 3 Settings: UASTC 3 pts/onednn-1.7.0 --conv --batch=inputs/conv/shapes_auto --cfg=bf16bf16bf16 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU pts/toybrot-1.2.0 raymarched/OMP/rmOpenMP Implementation: OpenMP pts/mnn-1.2.0 Model: inception-v3 pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU pts/mysqlslap-1.1.1 --concurrency=128 Clients: 128 pts/onednn-1.7.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=bf16bf16bf16 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU pts/toktx-1.0.0 --zcmp 19 Settings: Zstd Compression 19 pts/onednn-1.7.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU pts/onednn-1.7.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU pts/botan-1.6.0 AES-256 Test: AES-256 pts/onednn-1.7.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU pts/botan-1.6.0 KASUMI Test: KASUMI pts/basis-1.1.0 -uastc -uastc_level 2 Settings: UASTC Level 2 pts/botan-1.6.0 CAST-256 Test: CAST-256 pts/botan-1.6.0 ChaCha20Poly1305 Test: ChaCha20Poly1305 pts/liquid-dsp-1.0.0 -n 64 -b 256 -f 57 Threads: 64 - Buffer Length: 256 - Filter Length: 57 pts/botan-1.6.0 ChaCha20Poly1305 Test: ChaCha20Poly1305 - Decrypt pts/securemark-1.0.0 Benchmark: SecureMark-TLS pts/botan-1.6.0 Blowfish Test: Blowfish pts/draco-1.0.0 -i church.ply Model: Church Facade pts/botan-1.6.0 Twofish Test: Twofish pts/onednn-1.7.0 --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 160 -b 256 -f 57 Threads: 160 - Buffer Length: 256 - Filter Length: 57 pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU pts/onednn-1.7.0 --ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU pts/onednn-1.7.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU pts/helsing-1.0.0 10000000000000 99999999999999 Digit Range: 14 digit pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/blender-1.9.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: Fishy Cat - Compute: CPU-Only pts/draco-1.0.0 -i lion.ply Model: Lion pts/blender-1.9.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: Classroom - Compute: CPU-Only pts/intel-mlc-1.0.0 -X --max_bandwidth Test: Max Bandwidth - 1:1 Reads-Writes pts/intel-mlc-1.0.0 -X --peak_injection_bandwidth Test: Peak Injection Bandwidth - 2:1 Reads-Writes pts/intel-mlc-1.0.0 -X --max_bandwidth Test: Max Bandwidth - 2:1 Reads-Writes pts/srslte-1.0.1 lib/src/phy/dft/test/ofdm_test -N 2048 -n 100 -r 500000 Test: OFDM_Test pts/astcenc-1.1.0 -medium Preset: Medium pts/intel-mlc-1.0.0 -X --peak_injection_bandwidth Test: Peak Injection Bandwidth - All Reads pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU pts/basis-1.1.0 Settings: ETC1S pts/mysqlslap-1.1.1 --concurrency=8 Clients: 8 pts/blender-1.9.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: BMW27 - Compute: CPU-Only pts/intel-mlc-1.0.0 -X --peak_injection_bandwidth Test: Peak Injection Bandwidth - 3:1 Reads-Writes pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU pts/intel-mlc-1.0.0 -X --max_bandwidth Test: Max Bandwidth - 3:1 Reads-Writes pts/sysbench-1.1.0 memory run Test: RAM / Memory pts/intel-mlc-1.0.0 -X --max_bandwidth Test: Max Bandwidth - All Reads pts/botan-1.6.0 CAST-256 Test: CAST-256 - Decrypt pts/mysqlslap-1.1.1 --concurrency=64 Clients: 64 pts/botan-1.6.0 AES-256 Test: AES-256 - Decrypt pts/mysqlslap-1.1.1 --concurrency=32 Clients: 32 pts/basis-1.1.0 -uastc -uastc_level 0 Settings: UASTC Level 0 pts/astcenc-1.1.0 -thorough Preset: Thorough pts/toktx-1.0.0 --uastc 4 --zcmp 19 Settings: UASTC 4 + Zstd Compression 19 pts/toktx-1.0.0 --uastc 3 --zcmp 19 Settings: UASTC 3 + Zstd Compression 19 pts/intel-mlc-1.0.0 -X --max_bandwidth Test: Max Bandwidth - Stream-Triad Like pts/intel-mlc-1.0.0 -X --peak_injection_bandwidth Test: Peak Injection Bandwidth - Stream-Triad Like pts/mysqlslap-1.1.1 --concurrency=16 Clients: 16 pts/botan-1.6.0 Twofish Test: Twofish - Decrypt pts/basis-1.1.0 -uastc -uastc_level 3 Settings: UASTC Level 3 pts/blender-1.9.0 -b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: Pabellon Barcelona - Compute: CPU-Only pts/hammerdb-mariadb-1.0.0 128 500 Virtual Users: 128 - Warehouses: 500 pts/astcenc-1.1.0 -exhaustive Preset: Exhaustive pts/botan-1.6.0 KASUMI Test: KASUMI - Decrypt pts/mnn-1.2.0 Model: SqueezeNetV1.0 pts/blender-1.9.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 NONE Blend File: Barbershop - Compute: CPU-Only pts/botan-1.6.0 Blowfish Test: Blowfish - Decrypt pts/sysbench-1.1.0 cpu run Test: CPU pts/mysqlslap-1.1.1 --concurrency=512 Clients: 512 pts/mysqlslap-1.1.1 --concurrency=256 Clients: 256 pts/cp2k-1.2.0 -i benchmarks/Fayalite-FIST/fayalite.inp Input: Fayalite-FIST pts/hammerdb-mariadb-1.0.0 128 250 Virtual Users: 128 - Warehouses: 250 pts/hammerdb-mariadb-1.0.0 64 250 Virtual Users: 64 - Warehouses: 250 pts/hammerdb-mariadb-1.0.0 32 500 Virtual Users: 32 - Warehouses: 500 pts/hammerdb-mariadb-1.0.0 32 250 Virtual Users: 32 - Warehouses: 250 pts/hammerdb-mariadb-1.0.0 16 500 Virtual Users: 16 - Warehouses: 500 pts/hammerdb-mariadb-1.0.0 16 250 Virtual Users: 16 - Warehouses: 250 pts/hammerdb-mariadb-1.0.0 8 500 Virtual Users: 8 - Warehouses: 500 pts/hammerdb-mariadb-1.0.0 8 250 Virtual Users: 8 - Warehouses: 250 pts/mnn-1.2.0 Model: MobileNetV2_224 pts/mnn-1.2.0 Model: resnet-v2-50 pts/toktx-1.0.0 --zcmp 9 Settings: Zstd Compression 9 pts/mysqlslap-1.1.1 --concurrency=1 Clients: 1 pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-TT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-TN pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-NT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-NN pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMV-T pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMV-N pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dDOT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dAXPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dCOPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sDOT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sAXPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sCOPY pts/onednn-1.7.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-1.7.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU pts/avifenc-1.1.1 -s 10 Encoder Speed: 10 pts/svt-vp9-1.3.0 -tune 2 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: VMAF Optimized - Input: Bosphorus 1080p pts/luxcorerender-1.3.0 RainbowColorsAndPrism/LuxCoreScene/render.cfg -D renderengine.type PATHCPU Scene: Rainbow Colors and Prism - Acceleration: CPU system/gnuradio-1.0.0 Test: Hilbert Transform system/gnuradio-1.0.0 Test: FM Deemphasis Filter system/gnuradio-1.0.0 Test: IIR Filter system/gnuradio-1.0.0 Test: FIR Filter system/gnuradio-1.0.0 Test: Signal Source (Cosine) system/gnuradio-1.0.0 Test: Five Back to Back FIR Filters pts/luaradio-1.0.0 Test: Five Back to Back FIR Filters