xeon jan

Intel Xeon Silver 4216 testing with a TYAN S7100AG2NR (V4.02 BIOS) and ASPEED on Debian 12 via the Phoronix Test Suite.

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xeon jan Intel Xeon Silver 4216 testing with a TYAN S7100AG2NR (V4.02 BIOS) and ASPEED on Debian 12 via the Phoronix Test Suite. a: Processor: Intel Xeon Silver 4216 @ 3.20GHz (16 Cores / 32 Threads), Motherboard: TYAN S7100AG2NR (V4.02 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 6 x 8 GB DDR4-2400MT/s, Disk: 240GB Corsair Force MP500, Graphics: ASPEED, Audio: Realtek ALC892, Network: 2 x Intel I350 OS: Debian 12, Kernel: 6.1.0-11-amd64 (x86_64), Display Server: X Server, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1024x768 b: Processor: Intel Xeon Silver 4216 @ 3.20GHz (16 Cores / 32 Threads), Motherboard: TYAN S7100AG2NR (V4.02 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 6 x 8 GB DDR4-2400MT/s, Disk: 240GB Corsair Force MP500, Graphics: ASPEED, Audio: Realtek ALC892, Network: 2 x Intel I350 OS: Debian 12, Kernel: 6.1.0-11-amd64 (x86_64), Display Server: X Server, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1024x768 c: Processor: Intel Xeon Silver 4216 @ 3.20GHz (16 Cores / 32 Threads), Motherboard: TYAN S7100AG2NR (V4.02 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 6 x 8 GB DDR4-2400MT/s, Disk: 240GB Corsair Force MP500, Graphics: ASPEED, Audio: Realtek ALC892, Network: 2 x Intel I350 OS: Debian 12, Kernel: 6.1.0-11-amd64 (x86_64), Display Server: X Server, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1024x768 Quicksilver 20230818 Input: CTS2 Figure Of Merit > Higher Is Better a . 8446000 |================================================================= b . 8497000 |================================================================= c . 8607000 |================================================================== Quicksilver 20230818 Input: CORAL2 P2 Figure Of Merit > Higher Is Better a . 9287000 |================================================================== b . 9354000 |================================================================== c . 9308000 |================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 4.72 |==================================================================== b . 4.76 |===================================================================== c . 4.70 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 4.79 |===================================================================== b . 4.75 |==================================================================== c . 4.75 |==================================================================== LeelaChessZero 0.30 Backend: BLAS Nodes Per Second > Higher Is Better a . 37 |===================================================================== b . 38 |======================================================================= c . 37 |===================================================================== LeelaChessZero 0.30 Backend: Eigen Nodes Per Second > Higher Is Better a . 33 |======================================================================= b . 33 |======================================================================= c . 32 |===================================================================== Llama.cpp b1808 Model: llama-2-70b-chat.Q5_0.gguf Tokens Per Second > Higher Is Better a . 1.50 |===================================================================== b . 1.51 |===================================================================== c . 1.50 |===================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: VGG-16 images/sec > Higher Is Better a . 5.96 |===================================================================== b . 5.96 |===================================================================== c . 5.96 |===================================================================== PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 batches/sec > Higher Is Better a . 8.18 |===================================================================== b . 8.09 |==================================================================== c . 8.08 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better a . 8.14 |==================================================================== b . 8.13 |==================================================================== c . 8.22 |===================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.91 |===================================================================== b . 6.90 |===================================================================== c . 6.95 |===================================================================== CacheBench Test: Read / Modify / Write MB/s > Higher Is Better a . 61680.56 |================================================================= b . 59877.34 |=============================================================== c . 60843.70 |================================================================ CacheBench Test: Write MB/s > Higher Is Better a . 23161.61 |================================================================= b . 23134.97 |================================================================= c . 23165.59 |================================================================= CacheBench Test: Read MB/s > Higher Is Better a . 6062.37 |================================================================== b . 6058.74 |================================================================== c . 6057.99 |================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: ResNet-50 images/sec > Higher Is Better a . 16.22 |==================================================================== b . 16.25 |==================================================================== c . 16.21 |==================================================================== Quicksilver 20230818 Input: CORAL2 P1 Figure Of Merit > Higher Is Better a . 10170000 |================================================================= b . 10110000 |================================================================= c . 10150000 |================================================================= PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better a . 11.11 |==================================================================== b . 11.17 |==================================================================== c . 11.07 |=================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 845.95 |=================================================================== b . 846.00 |=================================================================== c . 845.20 |=================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 9.4169 |=================================================================== b . 9.4557 |=================================================================== c . 9.4646 |=================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 batches/sec > Higher Is Better a . 21.57 |=================================================================== b . 21.27 |=================================================================== c . 21.73 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 batches/sec > Higher Is Better a . 21.56 |=================================================================== b . 21.64 |==================================================================== c . 21.74 |==================================================================== Llama.cpp b1808 Model: llama-2-13b.Q4_0.gguf Tokens Per Second > Higher Is Better a . 8.70 |===================================================================== b . 8.73 |===================================================================== c . 8.62 |==================================================================== SVT-AV1 1.8 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 2.462 |==================================================================== b . 2.423 |=================================================================== c . 2.421 |=================================================================== Speedb 2.7 Test: Random Fill Sync Op/s > Higher Is Better a . 8962 |============================================= b . 13397 |==================================================================== c . 10150 |==================================================== Speedb 2.7 Test: Random Fill Op/s > Higher Is Better a . 379730 |=================================================================== b . 298026 |===================================================== c . 377206 |=================================================================== Speedb 2.7 Test: Update Random Op/s > Higher Is Better a . 172891 |=================================================================== b . 163726 |=============================================================== c . 151137 |=========================================================== Speedb 2.7 Test: Read While Writing Op/s > Higher Is Better a . 3897119 |================================================================ b . 3867484 |================================================================ c . 4014397 |================================================================== Speedb 2.7 Test: Read Random Write Random Op/s > Higher Is Better a . 1640953 |================================================================= b . 1658156 |================================================================== c . 1656172 |================================================================== Speedb 2.7 Test: Random Read Op/s > Higher Is Better a . 53271554 |================================================================= b . 52915603 |================================================================= c . 52443533 |================================================================ Speedb 2.7 Test: Sequential Fill Op/s > Higher Is Better a . 565169 |=================================================================== b . 558662 |================================================================== c . 549382 |================================================================= Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 28.14 |==================================================================== b . 27.85 |=================================================================== c . 27.95 |==================================================================== Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 283.96 |================================================================== b . 286.91 |=================================================================== c . 285.94 |=================================================================== Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 1061.89 |================================================================= b . 1073.13 |================================================================== c . 1060.60 |================================================================= Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 7.5161 |=================================================================== b . 7.2935 |================================================================= c . 7.5416 |=================================================================== Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 1071.41 |================================================================== b . 1063.84 |================================================================= c . 1072.98 |================================================================== Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 7.3201 |================================================================= b . 7.5195 |=================================================================== c . 7.2847 |================================================================= Y-Cruncher 0.8.3 Pi Digits To Calculate: 1B Seconds < Lower Is Better a . 46.09 |==================================================================== b . 45.45 |=================================================================== c . 45.93 |==================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 63.48 |==================================================================== b . 63.39 |==================================================================== c . 63.53 |==================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 125.96 |=================================================================== b . 126.10 |=================================================================== c . 125.77 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 552.53 |=================================================================== b . 549.40 |=================================================================== c . 553.47 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 14.38 |=================================================================== b . 14.50 |==================================================================== c . 14.30 |=================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better a . 29.51 |==================================================================== b . 29.64 |==================================================================== c . 28.89 |================================================================== Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 123.22 |=================================================================== b . 123.89 |=================================================================== c . 123.78 |=================================================================== Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 64.91 |==================================================================== b . 64.54 |==================================================================== c . 64.62 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: GoogLeNet images/sec > Higher Is Better a . 47.63 |==================================================================== b . 47.51 |==================================================================== c . 47.36 |==================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 68.77 |==================================================================== b . 68.91 |==================================================================== c . 68.89 |==================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 116.28 |=================================================================== b . 116.04 |=================================================================== c . 116.08 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 164.63 |=================================================================== b . 164.59 |=================================================================== c . 164.08 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 48.57 |==================================================================== b . 48.60 |==================================================================== c . 48.65 |==================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 165.97 |=================================================================== b . 165.69 |=================================================================== c . 165.88 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 48.19 |==================================================================== b . 48.27 |==================================================================== c . 48.22 |==================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 10.90 |==================================================================== b . 10.84 |==================================================================== c . 10.87 |==================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 732.36 |=================================================================== b . 736.87 |=================================================================== c . 734.42 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 68.76 |==================================================================== b . 68.95 |==================================================================== c . 68.68 |==================================================================== Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 116.18 |=================================================================== b . 115.88 |=================================================================== c . 116.40 |=================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: VGG-16 images/sec > Higher Is Better a . 3.27 |===================================================================== b . 3.24 |==================================================================== c . 3.26 |===================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: ResNet-50 images/sec > Higher Is Better a . 4.81 |==================================================================== b . 4.87 |===================================================================== c . 4.88 |===================================================================== SVT-AV1 1.8 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 24.38 |==================================================================== b . 23.99 |=================================================================== c . 24.07 |=================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: AlexNet images/sec > Higher Is Better a . 83.17 |==================================================================== b . 82.83 |==================================================================== c . 83.33 |==================================================================== SVT-AV1 1.8 Encoder Mode: Preset 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 7.326 |==================================================================== b . 7.379 |==================================================================== c . 7.251 |=================================================================== Y-Cruncher 0.8.3 Pi Digits To Calculate: 500M Seconds < Lower Is Better a . 20.62 |==================================================================== b . 20.68 |==================================================================== c . 20.58 |==================================================================== Llama.cpp b1808 Model: llama-2-7b.Q4_0.gguf Tokens Per Second > Higher Is Better a . 16.95 |==================================================================== b . 15.89 |================================================================ c . 16.55 |================================================================== SVT-AV1 1.8 Encoder Mode: Preset 8 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 45.63 |================================================================== b . 46.69 |==================================================================== c . 45.94 |=================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: GoogLeNet images/sec > Higher Is Better a . 17.26 |==================================================================== b . 15.86 |============================================================== c . 16.19 |================================================================ SVT-AV1 1.8 Encoder Mode: Preset 12 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 82.81 |==================================================================== b . 78.54 |================================================================ c . 82.22 |==================================================================== SVT-AV1 1.8 Encoder Mode: Preset 13 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 82.39 |=================================================================== b . 82.62 |=================================================================== c . 83.27 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: AlexNet images/sec > Higher Is Better a . 18.21 |=================================================================== b . 18.25 |==================================================================== c . 18.35 |==================================================================== SVT-AV1 1.8 Encoder Mode: Preset 12 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 165.27 |================================================================= b . 170.98 |=================================================================== c . 168.01 |================================================================== SVT-AV1 1.8 Encoder Mode: Preset 13 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 188.99 |=================================================================== b . 184.72 |================================================================= c . 187.02 |==================================================================