ddf

Tests for a future article. AMD EPYC 8534PN 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.

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January 07
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January 08
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ddf Tests for a future article. AMD EPYC 8534PN 64-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite. ,,"a","b" Processor,,AMD EPYC 8534PN 64-Core @ 2.00GHz (64 Cores / 128 Threads),AMD EPYC 8534PN 64-Core @ 2.00GHz (64 Cores / 128 Threads) Motherboard,,AMD Cinnabar (RCB1009C BIOS),AMD Cinnabar (RCB1009C BIOS) Chipset,,AMD Device 14a4,AMD Device 14a4 Memory,,192GB,192GB Disk,,3201GB Micron_7450_MTFDKCB3T2TFS,3201GB Micron_7450_MTFDKCB3T2TFS Graphics,,ASPEED,ASPEED Network,,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe OS,,Ubuntu 23.10,Ubuntu 23.10 Kernel,,6.5.0-5-generic (x86_64),6.5.0-5-generic (x86_64) Desktop,,GNOME Shell,GNOME Shell Display Server,,X Server 1.21.1.7,X Server 1.21.1.7 Compiler,,GCC 13.2.0,GCC 13.2.0 File-System,,ext4,ext4 Screen Resolution,,640x480,640x480 ,,"a","b" "WebP2 Image Encode - Encode Settings: Quality 100, Lossless Compression (MP/s)",HIB,0.06,0.06 "LeelaChessZero - Backend: Eigen (Nodes/s)",HIB,272,282 "LeelaChessZero - Backend: BLAS (Nodes/s)",HIB,315,354 "Speedb - Test: Sequential Fill (Op/s)",HIB,371857,369178 "OpenRadioss - Model: Chrysler Neon 1M (sec)",LIB,297.08,295.72 "Quicksilver - Input: CTS2 (Figure Of Merit)",HIB,16240000,16310000 "PyTorch - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,6.00,5.98 "PyTorch - Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l (batches/sec)",HIB,6.03,6.03 "PyTorch - Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l (batches/sec)",HIB,6.06,6.08 "Quicksilver - Input: CORAL2 P2 (Figure Of Merit)",HIB,16170000,16190000 "Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,239.83,240.12 "Xmrig - Variant: GhostRider - Hash Count: 1M (H/s)",HIB,4436.2,4442.9 "Timed Gem5 Compilation - Time To Compile (sec)",LIB,211.562,223.062 "FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,23.20,23.29 "FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,47.03,47.05 "FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,47.15,47.07 "OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,164.67,163.46 "PyTorch - Device: CPU - Batch Size: 32 - Model: ResNet-152 (batches/sec)",HIB,14.37,14.13 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,14.70,14.18 "OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,143.85,142.38 "PyTorch - Device: CPU - Batch Size: 64 - Model: ResNet-152 (batches/sec)",HIB,14.89,14.61 "Y-Cruncher - Pi Digits To Calculate: 10B (sec)",LIB,112.543,112.813 "PyTorch - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,9.53,9.61 "easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 (sec)",LIB,111.038,111.072 "rav1e - Speed: 1 (FPS)",HIB,0.85,0.85 "WebP2 Image Encode - Encode Settings: Quality 95, Compression Effort 7 (MP/s)",HIB,0.27,0.26 "OpenRadioss - Model: Bumper Beam (sec)",LIB,88.11,88.16 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,673.3343,674.9861 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,46.9635,46.8626 "Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,86.14,86.16 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream (ms/batch)",LIB,32.9699,33.1445 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream (items/sec)",HIB,30.3213,30.1617 "OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,76.78,76.1 "QuantLib - Configuration: Multi-Threaded (MFLOPS)",HIB,176928.1,170381.3 "PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,16.54,16.58 "Y-Cruncher - Pi Digits To Calculate: 5B (sec)",LIB,53.068,53.146 "Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,67.06,67.51 "FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,114.74,115.73 "Speedb - Test: Random Fill (Op/s)",HIB,369023,367684 "Speedb - Test: Random Fill Sync (Op/s)",HIB,239469,244535 "Speedb - Test: Update Random (Op/s)",HIB,350612,361192 "Speedb - Test: Read Random Write Random (Op/s)",HIB,2539184,2539687 "Speedb - Test: Read While Writing (Op/s)",HIB,15411684,15231425 "Speedb - Test: Random Read (Op/s)",HIB,303866048,304143127 "CloverLeaf - Input: clover_bm64_short (sec)",LIB,57.21,57.09 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,36.12,36.35 "PyTorch - Device: CPU - Batch Size: 32 - Model: ResNet-50 (batches/sec)",HIB,36.66,36.38 "PyTorch - Device: CPU - Batch Size: 64 - Model: ResNet-50 (batches/sec)",HIB,36.87,36.29 "rav1e - Speed: 5 (FPS)",HIB,3.584,3.596 "Quicksilver - Input: CORAL2 P1 (Figure Of Merit)",HIB,21350000,21280000 "TensorFlow - Device: CPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,35.21,35.14 "Xmrig - Variant: CryptoNight-Heavy - Hash Count: 1M (H/s)",HIB,20666.7,20071.9 "Xmrig - Variant: CryptoNight-Femto UPX2 - Hash Count: 1M (H/s)",HIB,20698.4,20683 "Xmrig - Variant: KawPow - Hash Count: 1M (H/s)",HIB,20682.1,20732.7 "Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,20714.7,20732.3 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,5.1074,5.217 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,195.6,191.4824 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,852.1762,853.3085 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,36.8118,37.0225 "rav1e - Speed: 10 (FPS)",HIB,12.32,12.36 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,854.1221,853.694 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,37.088,37.16 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,21.9243,21.9623 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1458.049,1454.9899 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,45.7574,45.9477 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,698.3574,695.3481 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,36.2588,36.3016 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,27.5732,27.5404 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,36.3487,36.316 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,27.5048,27.5295 "WebP2 Image Encode - Encode Settings: Quality 75, Compression Effort 7 (MP/s)",HIB,0.54,0.51 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,15.7849,15.77 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,63.2873,63.3431 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,496.3373,497.6216 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,64.0666,63.9058 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (ms/batch)",LIB,24.3612,24.3739 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream (items/sec)",HIB,41.0087,40.9888 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,98.8186,98.8586 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,323.0662,322.9189 "easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 (sec)",LIB,39.643,39.484 "rav1e - Speed: 6 (FPS)",HIB,4.851,4.891 "OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,31.94,31.84 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,7.6305,7.5994 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,130.9206,131.4576 "TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,51.06,50.8 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,6.8554,6.8775 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,145.6232,145.1485 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,145.021,144.9123 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,220.0706,220.1545 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,6.7843,6.7891 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,147.2472,147.1485 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,65.6643,65.7823 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,486.6043,485.7323 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,143.5315,143.8442 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,222.2492,221.7174 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,8.3709,8.399 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,3813.6379,3800.6772 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (ms/batch)",LIB,5.3901,5.3631 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream (items/sec)",HIB,185.3007,186.2351 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,5.3704,5.4136 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,185.9864,184.5078 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,65.6917,65.7405 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,485.9989,485.8785 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,1.2456,1.2465 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream (items/sec)",HIB,800.5916,799.9581 "Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,35.54,35.33 "QuantLib - Configuration: Single-Threaded (MFLOPS)",HIB,2634.4,2633.8 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,6.628,6.75 "PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,45.19,45.42 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,26.71,26.75 "Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,40330.7,40146.1 "TensorFlow - Device: CPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,5.97,5.97 "Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,69.0867,68.5948 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,71.4939,71.4428 "Timed FFmpeg Compilation - Time To Compile (sec)",LIB,18.145,18.042 "TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,155.77,155.78 "Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,10.245,10.202 "CloverLeaf - Input: clover_bm (sec)",LIB,13.67,13.93 "TensorFlow - Device: CPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,9.87,9.87 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,67.98,68.523 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,17.075,17.467 "Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,67.9313,67.1138 "Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,69.2031,68.5827 "Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,77.2581,77.103 "TensorFlow - Device: CPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,17,17 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,83.8771,83.5831 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,187.077,194.587 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,190.949,194.49 "TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,299.15,297.84 "Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,5.11,5.106 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,131.9,129.181 "TensorFlow - Device: CPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,30.46,30.45 "WebP2 Image Encode - Encode Settings: Default (MP/s)",HIB,7.44,7.49 "easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 (sec)",LIB,1.947,1.958 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,511.853,503.618 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,597.058,601.573 "WebP2 Image Encode - Encode Settings: Quality 100, Compression Effort 5 (MP/s)",HIB,11.63,11.68