rpyc jan

AMD EPYC 7F32 8-Core testing with a ASRockRack EPYCD8 (P2.40 BIOS) and ASPEED on Debian 12 via the Phoronix Test Suite.

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BLAS (Basic Linear Algebra Sub-Routine) Tests 2 Tests
CPU Massive 4 Tests
HPC - High Performance Computing 5 Tests
Machine Learning 5 Tests
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a
January 14
  2 Days, 18 Hours, 59 Minutes
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January 14
  2 Days, 19 Hours
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rpyc jan AMD EPYC 7F32 8-Core testing with a ASRockRack EPYCD8 (P2.40 BIOS) and ASPEED on Debian 12 via the Phoronix Test Suite. ,,"a","b" Processor,,AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads),AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads) Motherboard,,ASRockRack EPYCD8 (P2.40 BIOS),ASRockRack EPYCD8 (P2.40 BIOS) Chipset,,AMD Starship/Matisse,AMD Starship/Matisse Memory,,7 x 4 GB DDR4-2666MT/s Micron 9ASF51272PZ-2G6B1,7 x 4 GB DDR4-2666MT/s Micron 9ASF51272PZ-2G6B1 Disk,,Samsung SSD 970 EVO Plus 250GB,Samsung SSD 970 EVO Plus 250GB Graphics,,ASPEED,ASPEED Network,,2 x Intel I350,2 x Intel I350 OS,,Debian 12,Debian 12 Kernel,,6.1.0-11-amd64 (x86_64),6.1.0-11-amd64 (x86_64) Display Server,,X Server,X Server Compiler,,GCC 12.2.0,GCC 12.2.0 File-System,,ext4,ext4 Screen Resolution,,1024x768,1024x768 ,,"a","b" "Apache Spark TPC-DS - Scale Factor: 1 - Q01 (sec)",LIB,4.1,4.03 "Apache Spark TPC-DS - Scale Factor: 1 - Q02 (sec)",LIB,4.52,4.6 "Apache Spark TPC-DS - Scale Factor: 1 - 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Q12 (sec)",LIB,2.36,2.36 "Apache Spark TPC-DS - Scale Factor: 10 - Q13 (sec)",LIB,5.85,5.5 "Apache Spark TPC-DS - Scale Factor: 10 - Q14 (sec)",LIB,8.92,8.34 "Apache Spark TPC-DS - Scale Factor: 10 - Q15 (sec)",LIB,5.2,5.49 "Apache Spark TPC-DS - Scale Factor: 10 - Q17 (sec)",LIB,14.2,14.18 "Apache Spark TPC-DS - Scale Factor: 10 - Q18 (sec)",LIB,6.46,6.64 "Apache Spark TPC-DS - Scale Factor: 10 - Q19 (sec)",LIB,5.85,5.73 "Apache Spark TPC-DS - Scale Factor: 10 - Q20 (sec)",LIB,2.26,2.26 "Apache Spark TPC-DS - Scale Factor: 10 - Q21 (sec)",LIB,5.25,5.49 "Apache Spark TPC-DS - Scale Factor: 10 - Q22 (sec)",LIB,11.93,12.19 "Apache Spark TPC-DS - Scale Factor: 10 - Q23 (sec)",LIB,15.49,15.13 "Apache Spark TPC-DS - Scale Factor: 10 - Q24 (sec)",LIB,6.34,6.26 "Apache Spark TPC-DS - Scale Factor: 10 - Q25 (sec)",LIB,14.15,14.41 "Apache Spark TPC-DS - Scale Factor: 10 - Q26 (sec)",LIB,5.63,5.06 "Apache Spark TPC-DS - Scale Factor: 10 - Q27 (sec)",LIB,5.85,6.49 "Apache Spark TPC-DS - Scale Factor: 10 - 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Q73 (sec)",LIB,5.49,6.02 "Apache Spark TPC-DS - Scale Factor: 10 - Q74 (sec)",LIB,9.42,9.48 "Apache Spark TPC-DS - Scale Factor: 10 - Q75 (sec)",LIB,13.69,14 "Apache Spark TPC-DS - Scale Factor: 10 - Q76 (sec)",LIB,6.1,5.59 "Apache Spark TPC-DS - Scale Factor: 10 - Q77 (sec)",LIB,7.08,7.56 "Apache Spark TPC-DS - Scale Factor: 10 - Q78 (sec)",LIB,19.55,19.54 "Apache Spark TPC-DS - Scale Factor: 10 - Q79 (sec)",LIB,5.38,5.01 "Apache Spark TPC-DS - Scale Factor: 10 - Q80 (sec)",LIB,17.99,17.99 "Apache Spark TPC-DS - Scale Factor: 10 - Q81 (sec)",LIB,5.63,5.65 "Apache Spark TPC-DS - Scale Factor: 10 - Q82 (sec)",LIB,6.45,6.66 "Apache Spark TPC-DS - Scale Factor: 10 - Q83 (sec)",LIB,5.39,5.27 "Apache Spark TPC-DS - Scale Factor: 10 - Q84 (sec)",LIB,5.16,5.09 "Apache Spark TPC-DS - Scale Factor: 10 - Q85 (sec)",LIB,8.18,7.8 "Apache Spark TPC-DS - Scale Factor: 10 - Q86 (sec)",LIB,4,3.87 "Apache Spark TPC-DS - Scale Factor: 10 - Q87 (sec)",LIB,8.37,8.02 "Apache Spark TPC-DS - Scale Factor: 10 - Q88 (sec)",LIB,8.63,8.16 "Apache Spark TPC-DS - Scale Factor: 10 - Q89 (sec)",LIB,4.99,4.78 "Apache Spark TPC-DS - Scale Factor: 10 - Q90 (sec)",LIB,4.03,3.2 "Apache Spark TPC-DS - Scale Factor: 10 - Q91 (sec)",LIB,4.94,4.93 "Apache Spark TPC-DS - Scale Factor: 10 - Q92 (sec)",LIB,4.16,4.53 "Apache Spark TPC-DS - Scale Factor: 10 - Q93 (sec)",LIB,11.76,11.31 "Apache Spark TPC-DS - Scale Factor: 10 - Q94 (sec)",LIB,4.49,4.48 "Apache Spark TPC-DS - Scale Factor: 10 - Q95 (sec)",LIB,4.68,4.51 "Apache Spark TPC-DS - Scale Factor: 10 - Q96 (sec)",LIB,3.23,3.04 "Apache Spark TPC-DS - Scale Factor: 10 - Q97 (sec)",LIB,8.04,7.22 "Apache Spark TPC-DS - Scale Factor: 10 - Q98 (sec)",LIB,2.34,2.24 "Apache Spark TPC-DS - Scale Factor: 10 - Q99 (sec)",LIB,4.43,3.99 "CacheBench - Test: Read (MB/s)",HIB,9891.085916,9892.738544 "CacheBench - Test: Write (MB/s)",HIB,55386.26412,55484.050343 "CacheBench - Test: Read / Modify / Write (MB/s)",HIB,57602.719674,57618.902797 "LeelaChessZero - Backend: BLAS (Nodes/s)",HIB,130,133 "LeelaChessZero - Backend: Eigen (Nodes/s)",HIB,83,85 "Llama.cpp - Model: llama-2-7b.Q4_0.gguf (Tokens/sec)",HIB,11.32,12.67 "Llama.cpp - Model: llama-2-13b.Q4_0.gguf (Tokens/sec)",HIB,5.16,6.34 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,7.7676,7.7424 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,512.1858,515.2201 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,124.668,127.168 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,32.0561,31.4254 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,75.7554,74.4881 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,52.7328,53.6692 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,399.7162,396.2172 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,9.9773,10.0658 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,39.6374,39.4407 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,100.7805,101.3381 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,9.1492,9.2258 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,434.3769,433.0207 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,76.4568,76.7658 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,52.245,52.0753 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,40.1489,40.0737 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,99.5285,99.7263 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,59.0697,58.897 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,67.6345,67.8367 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,8.304,8.3172 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,480.2254,478.9249 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,56.1324,56.6743 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,71.2145,70.5121 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,7.866,7.8507 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,505.1583,509.3372 "PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,26.58,27.92 "PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,10.83,11.50 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,20.05,19.48 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,7.44,8.21 "PyTorch - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,5.91,6.11 "PyTorch - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,4.19,4.48 "Quicksilver - Input: CTS2 (Figure Of Merit)",HIB,5986000,5982000 "Quicksilver - Input: CORAL2 P1 (Figure Of Merit)",HIB,7364000,7308000 "Quicksilver - Input: CORAL2 P2 (Figure Of Merit)",HIB,7679000,7662000 "Speedb - Test: Random Fill (Op/s)",HIB,233324,239360 "Speedb - Test: Random Read (Op/s)",HIB,34248146,34244004 "Speedb - Test: Update Random (Op/s)",HIB,215940,216433 "Speedb - Test: Sequential Fill (Op/s)",HIB,275849,267223 "Speedb - Test: Random Fill Sync (Op/s)",HIB,3082,3026 "Speedb - Test: Read While Writing (Op/s)",HIB,2257890,2104380 "Speedb - Test: Read Random Write Random (Op/s)",HIB,1011750,978572 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,2.949,2.931 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,23.542,23.345 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,78.31,79.927 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,78.877,81.313 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,9.956,9.768 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,63.991,63.704 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,255.926,268.084 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,316.493,331.495 "TensorFlow - Device: CPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,2.59,2.13 "TensorFlow - Device: CPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,8.88,7.23 "TensorFlow - Device: CPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,4.69,4.23 "TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,59.35,51.44 "TensorFlow - Device: CPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,9.89,9.44 "TensorFlow - Device: CPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,6.38,6.47 "TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,35.56,33.16 "TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,11.52,10.04 "Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,47.648,47.2 "Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,22.303,22.048