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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2401089-NE-DDF54911740
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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: Processor: AMD EPYC 8534PN 64-Core @ 2.00GHz (64 Cores / 128 Threads), Motherboard: AMD Cinnabar (RCB1009C BIOS), Chipset: AMD Device 14a4, Memory: 192GB, Disk: 3201GB Micron_7450_MTFDKCB3T2TFS, Graphics: ASPEED, Network: 2 x Broadcom NetXtreme BCM5720 PCIe OS: Ubuntu 23.10, Kernel: 6.5.0-5-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 640x480 b: Processor: AMD EPYC 8534PN 64-Core @ 2.00GHz (64 Cores / 128 Threads), Motherboard: AMD Cinnabar (RCB1009C BIOS), Chipset: AMD Device 14a4, Memory: 192GB, Disk: 3201GB Micron_7450_MTFDKCB3T2TFS, Graphics: ASPEED, Network: 2 x Broadcom NetXtreme BCM5720 PCIe OS: Ubuntu 23.10, Kernel: 6.5.0-5-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server 1.21.1.7, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 640x480 WebP2 Image Encode 20220823 Encode Settings: Quality 100, Lossless Compression MP/s > Higher Is Better a . 0.06 |===================================================================== b . 0.06 |===================================================================== LeelaChessZero 0.30 Backend: Eigen Nodes Per Second > Higher Is Better a . 272 |==================================================================== b . 282 |====================================================================== LeelaChessZero 0.30 Backend: BLAS Nodes Per Second > Higher Is Better a . 315 |============================================================== b . 354 |====================================================================== Speedb 2.7 Test: Sequential Fill Op/s > Higher Is Better a . 371857 |=================================================================== b . 369178 |=================================================================== OpenRadioss 2023.09.15 Model: Chrysler Neon 1M Seconds < Lower Is Better a . 297.08 |=================================================================== b . 295.72 |=================================================================== Quicksilver 20230818 Input: CTS2 Figure Of Merit > Higher Is Better a . 16240000 |================================================================= b . 16310000 |================================================================= PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.00 |===================================================================== b . 5.98 |===================================================================== PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.03 |===================================================================== b . 6.03 |===================================================================== PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 6.06 |===================================================================== b . 6.08 |===================================================================== Quicksilver 20230818 Input: CORAL2 P2 Figure Of Merit > Higher Is Better a . 16170000 |================================================================= b . 16190000 |================================================================= Blender 4.0 Blend File: Barbershop - Compute: CPU-Only Seconds < Lower Is Better a . 239.83 |=================================================================== b . 240.12 |=================================================================== Xmrig 6.21 Variant: GhostRider - Hash Count: 1M H/s > Higher Is Better a . 4436.2 |=================================================================== b . 4442.9 |=================================================================== Timed Gem5 Compilation 23.0.1 Time To Compile Seconds < Lower Is Better a . 211.56 |================================================================ b . 223.06 |=================================================================== FFmpeg 6.1 Encoder: libx265 - Scenario: Upload FPS > Higher Is Better a . 23.20 |==================================================================== b . 23.29 |==================================================================== FFmpeg 6.1 Encoder: libx265 - Scenario: Video On Demand FPS > Higher Is Better a . 47.03 |==================================================================== b . 47.05 |==================================================================== FFmpeg 6.1 Encoder: libx265 - Scenario: Platform FPS > Higher Is Better a . 47.15 |==================================================================== b . 47.07 |==================================================================== OpenRadioss 2023.09.15 Model: INIVOL and Fluid Structure Interaction Drop Container Seconds < Lower Is Better a . 164.67 |=================================================================== b . 163.46 |=================================================================== PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 batches/sec > Higher Is Better a . 14.37 |==================================================================== b . 14.13 |=================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better a . 14.70 |==================================================================== b . 14.18 |================================================================== OpenRadioss 2023.09.15 Model: Bird Strike on Windshield Seconds < Lower Is Better a . 143.85 |=================================================================== b . 142.38 |================================================================== PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 batches/sec > Higher Is Better a . 14.89 |==================================================================== b . 14.61 |=================================================================== Y-Cruncher 0.8.3 Pi Digits To Calculate: 10B Seconds < Lower Is Better a . 112.54 |=================================================================== b . 112.81 |=================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 9.53 |==================================================================== b . 9.61 |===================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 Seconds < Lower Is Better a . 111.04 |=================================================================== b . 111.07 |=================================================================== rav1e 0.7 Speed: 1 Frames Per Second > Higher Is Better a . 0.85 |===================================================================== b . 0.85 |===================================================================== WebP2 Image Encode 20220823 Encode Settings: Quality 95, Compression Effort 7 MP/s > Higher Is Better a . 0.27 |===================================================================== b . 0.26 |================================================================== OpenRadioss 2023.09.15 Model: Bumper Beam Seconds < Lower Is Better a . 88.11 |==================================================================== b . 88.16 |==================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 673.33 |=================================================================== b . 674.99 |=================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 46.96 |==================================================================== b . 46.86 |==================================================================== Blender 4.0 Blend File: Pabellon Barcelona - Compute: CPU-Only Seconds < Lower Is Better a . 86.14 |==================================================================== b . 86.16 |==================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 32.97 |==================================================================== b . 33.14 |==================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 30.32 |==================================================================== b . 30.16 |==================================================================== OpenRadioss 2023.09.15 Model: Rubber O-Ring Seal Installation Seconds < Lower Is Better a . 76.78 |==================================================================== b . 76.10 |=================================================================== QuantLib 1.32 Configuration: Multi-Threaded MFLOPS > Higher Is Better a . 176928.1 |================================================================= b . 170381.3 |=============================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better a . 16.54 |==================================================================== b . 16.58 |==================================================================== Y-Cruncher 0.8.3 Pi Digits To Calculate: 5B Seconds < Lower Is Better a . 53.07 |==================================================================== b . 53.15 |==================================================================== Blender 4.0 Blend File: Classroom - Compute: CPU-Only Seconds < Lower Is Better a . 67.06 |==================================================================== b . 67.51 |==================================================================== FFmpeg 6.1 Encoder: libx265 - Scenario: Live FPS > Higher Is Better a . 114.74 |================================================================== b . 115.73 |=================================================================== Speedb 2.7 Test: Random Fill Op/s > Higher Is Better a . 369023 |=================================================================== b . 367684 |=================================================================== Speedb 2.7 Test: Random Fill Sync Op/s > Higher Is Better a . 239469 |================================================================== b . 244535 |=================================================================== Speedb 2.7 Test: Update Random Op/s > Higher Is Better a . 350612 |================================================================= b . 361192 |=================================================================== Speedb 2.7 Test: Read Random Write Random Op/s > Higher Is Better a . 2539184 |================================================================== b . 2539687 |================================================================== Speedb 2.7 Test: Read While Writing Op/s > Higher Is Better a . 15411684 |================================================================= b . 15231425 |================================================================ Speedb 2.7 Test: Random Read Op/s > Higher Is Better a . 303866048 |================================================================ b . 304143127 |================================================================ CloverLeaf 1.3 Input: clover_bm64_short Seconds < Lower Is Better a . 57.21 |==================================================================== b . 57.09 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 batches/sec > Higher Is Better a . 36.12 |==================================================================== b . 36.35 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 batches/sec > Higher Is Better a . 36.66 |==================================================================== b . 36.38 |=================================================================== PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 batches/sec > Higher Is Better a . 36.87 |==================================================================== b . 36.29 |=================================================================== rav1e 0.7 Speed: 5 Frames Per Second > Higher Is Better a . 3.584 |==================================================================== b . 3.596 |==================================================================== Quicksilver 20230818 Input: CORAL2 P1 Figure Of Merit > Higher Is Better a . 21350000 |================================================================= b . 21280000 |================================================================= TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: VGG-16 images/sec > Higher Is Better a . 35.21 |==================================================================== b . 35.14 |==================================================================== Xmrig 6.21 Variant: CryptoNight-Heavy - Hash Count: 1M H/s > Higher Is Better a . 20666.7 |================================================================== b . 20071.9 |================================================================ Xmrig 6.21 Variant: CryptoNight-Femto UPX2 - Hash Count: 1M H/s > Higher Is Better a . 20698.4 |================================================================== b . 20683.0 |================================================================== Xmrig 6.21 Variant: KawPow - Hash Count: 1M H/s > Higher Is Better a . 20682.1 |================================================================== b . 20732.7 |================================================================== Xmrig 6.21 Variant: Monero - Hash Count: 1M H/s > Higher Is Better a . 20714.7 |================================================================== b . 20732.3 |================================================================== Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 5.1074 |================================================================== b . 5.2170 |=================================================================== Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 195.60 |=================================================================== b . 191.48 |================================================================== Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 852.18 |=================================================================== b . 853.31 |=================================================================== Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 36.81 |==================================================================== b . 37.02 |==================================================================== rav1e 0.7 Speed: 10 Frames Per Second > Higher Is Better a . 12.32 |==================================================================== b . 12.36 |==================================================================== Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 854.12 |=================================================================== b . 853.69 |=================================================================== Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 37.09 |==================================================================== b . 37.16 |==================================================================== 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 . 21.92 |==================================================================== b . 21.96 |==================================================================== 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 . 1458.05 |================================================================== b . 1454.99 |================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 45.76 |==================================================================== b . 45.95 |==================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 698.36 |=================================================================== b . 695.35 |=================================================================== Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 36.26 |==================================================================== b . 36.30 |==================================================================== Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 27.57 |==================================================================== b . 27.54 |==================================================================== Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 36.35 |==================================================================== b . 36.32 |==================================================================== Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 27.50 |==================================================================== b . 27.53 |==================================================================== WebP2 Image Encode 20220823 Encode Settings: Quality 75, Compression Effort 7 MP/s > Higher Is Better a . 0.54 |===================================================================== b . 0.51 |================================================================= Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 15.78 |==================================================================== b . 15.77 |==================================================================== Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 63.29 |==================================================================== b . 63.34 |==================================================================== Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 496.34 |=================================================================== b . 497.62 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 64.07 |==================================================================== b . 63.91 |==================================================================== Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 24.36 |==================================================================== b . 24.37 |==================================================================== Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 41.01 |==================================================================== b . 40.99 |==================================================================== Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 98.82 |==================================================================== b . 98.86 |==================================================================== Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 323.07 |=================================================================== b . 322.92 |=================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 Seconds < Lower Is Better a . 39.64 |==================================================================== b . 39.48 |==================================================================== rav1e 0.7 Speed: 6 Frames Per Second > Higher Is Better a . 4.851 |=================================================================== b . 4.891 |==================================================================== OpenRadioss 2023.09.15 Model: Cell Phone Drop Test Seconds < Lower Is Better a . 31.94 |==================================================================== b . 31.84 |==================================================================== Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 7.6305 |=================================================================== b . 7.5994 |=================================================================== Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 130.92 |=================================================================== b . 131.46 |=================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: ResNet-50 images/sec > Higher Is Better a . 51.06 |==================================================================== b . 50.80 |==================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 6.8554 |=================================================================== b . 6.8775 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 145.62 |=================================================================== b . 145.15 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 145.02 |=================================================================== b . 144.91 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 220.07 |=================================================================== b . 220.15 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 6.7843 |=================================================================== b . 6.7891 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 147.25 |=================================================================== b . 147.15 |=================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 65.66 |==================================================================== b . 65.78 |==================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 486.60 |=================================================================== b . 485.73 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 143.53 |=================================================================== b . 143.84 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 222.25 |=================================================================== b . 221.72 |=================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 8.3709 |=================================================================== b . 8.3990 |=================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 3813.64 |================================================================== b . 3800.68 |================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 5.3901 |=================================================================== b . 5.3631 |=================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 185.30 |=================================================================== b . 186.24 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 5.3704 |================================================================== b . 5.4136 |=================================================================== Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 185.99 |=================================================================== b . 184.51 |================================================================== Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 65.69 |==================================================================== b . 65.74 |==================================================================== Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 486.00 |=================================================================== b . 485.88 |=================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream ms/batch < Lower Is Better a . 1.2456 |=================================================================== b . 1.2465 |=================================================================== Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream items/sec > Higher Is Better a . 800.59 |=================================================================== b . 799.96 |=================================================================== Blender 4.0 Blend File: Fishy Cat - Compute: CPU-Only Seconds < Lower Is Better a . 35.54 |==================================================================== b . 35.33 |==================================================================== QuantLib 1.32 Configuration: Single-Threaded MFLOPS > Higher Is Better a . 2634.4 |=================================================================== b . 2633.8 |=================================================================== SVT-AV1 1.8 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 6.628 |=================================================================== b . 6.750 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better a . 45.19 |==================================================================== b . 45.42 |==================================================================== Blender 4.0 Blend File: BMW27 - Compute: CPU-Only Seconds < Lower Is Better a . 26.71 |==================================================================== b . 26.75 |==================================================================== Xmrig 6.21 Variant: Wownero - Hash Count: 1M H/s > Higher Is Better a . 40330.7 |================================================================== b . 40146.1 |================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: ResNet-50 images/sec > Higher Is Better a . 5.97 |===================================================================== b . 5.97 |===================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 69.09 |==================================================================== b . 68.59 |==================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 71.49 |==================================================================== b . 71.44 |==================================================================== Timed FFmpeg Compilation 6.1 Time To Compile Seconds < Lower Is Better a . 18.15 |==================================================================== b . 18.04 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: GoogLeNet images/sec > Higher Is Better a . 155.77 |=================================================================== b . 155.78 |=================================================================== Y-Cruncher 0.8.3 Pi Digits To Calculate: 1B Seconds < Lower Is Better a . 10.25 |==================================================================== b . 10.20 |==================================================================== CloverLeaf 1.3 Input: clover_bm Seconds < Lower Is Better a . 13.67 |=================================================================== b . 13.93 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: VGG-16 images/sec > Higher Is Better a . 9.87 |===================================================================== b . 9.87 |===================================================================== SVT-AV1 1.8 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 67.98 |=================================================================== b . 68.52 |==================================================================== SVT-AV1 1.8 Encoder Mode: Preset 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 17.08 |================================================================== b . 17.47 |==================================================================== Embree 4.3 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 67.93 |==================================================================== b . 67.11 |=================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 69.20 |==================================================================== b . 68.58 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 77.26 |==================================================================== b . 77.10 |==================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: GoogLeNet images/sec > Higher Is Better a . 17 |======================================================================= b . 17 |======================================================================= Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 83.88 |==================================================================== b . 83.58 |==================================================================== SVT-AV1 1.8 Encoder Mode: Preset 13 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 187.08 |================================================================ b . 194.59 |=================================================================== SVT-AV1 1.8 Encoder Mode: Preset 12 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 190.95 |================================================================== b . 194.49 |=================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 16 - Model: AlexNet images/sec > Higher Is Better a . 299.15 |=================================================================== b . 297.84 |=================================================================== Y-Cruncher 0.8.3 Pi Digits To Calculate: 500M Seconds < Lower Is Better a . 5.110 |==================================================================== b . 5.106 |==================================================================== SVT-AV1 1.8 Encoder Mode: Preset 8 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 131.90 |=================================================================== b . 129.18 |================================================================== TensorFlow 2.12 Device: CPU - Batch Size: 1 - Model: AlexNet images/sec > Higher Is Better a . 30.46 |==================================================================== b . 30.45 |==================================================================== WebP2 Image Encode 20220823 Encode Settings: Default MP/s > Higher Is Better a . 7.44 |===================================================================== b . 7.49 |===================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 Seconds < Lower Is Better a . 1.947 |==================================================================== b . 1.958 |==================================================================== SVT-AV1 1.8 Encoder Mode: Preset 12 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 511.85 |=================================================================== b . 503.62 |================================================================== SVT-AV1 1.8 Encoder Mode: Preset 13 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 597.06 |================================================================== b . 601.57 |=================================================================== WebP2 Image Encode 20220823 Encode Settings: Quality 100, Compression Effort 5 MP/s > Higher Is Better a . 11.63 |==================================================================== b . 11.68 |====================================================================