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
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
PyTorch 2.1
Device: CPU - Batch Size: 1 - Model: ResNet-50
batches/sec > Higher Is Better
a . 45.19 |====================================================================
b . 45.42 |====================================================================
PyTorch 2.1
Device: CPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
a . 16.54 |====================================================================
b . 16.58 |====================================================================
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 |===================================================================
PyTorch 2.1
Device: CPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better
a . 14.70 |====================================================================
b . 14.18 |==================================================================
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: 64 - Model: ResNet-152
batches/sec > Higher Is Better
a . 14.89 |====================================================================
b . 14.61 |===================================================================
PyTorch 2.1
Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 9.53 |====================================================================
b . 9.61 |=====================================================================
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: 32 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 6.06 |=====================================================================
b . 6.08 |=====================================================================
PyTorch 2.1
Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
a . 6.03 |=====================================================================
b . 6.03 |=====================================================================
Quicksilver 20230818
Input: CTS2
Figure Of Merit > Higher Is Better
a . 16240000 |=================================================================
b . 16310000 |=================================================================
Quicksilver 20230818
Input: CORAL2 P1
Figure Of Merit > Higher Is Better
a . 21350000 |=================================================================
b . 21280000 |=================================================================
Quicksilver 20230818
Input: CORAL2 P2
Figure Of Merit > Higher Is Better
a . 16170000 |=================================================================
b . 16190000 |=================================================================
FFmpeg 6.1
Encoder: libx265 - Scenario: Live
FPS > Higher Is Better
a . 114.74 |==================================================================
b . 115.73 |===================================================================
FFmpeg 6.1
Encoder: libx265 - Scenario: Upload
FPS > Higher Is Better
a . 23.20 |====================================================================
b . 23.29 |====================================================================
FFmpeg 6.1
Encoder: libx265 - Scenario: Platform
FPS > Higher Is Better
a . 47.15 |====================================================================
b . 47.07 |====================================================================
FFmpeg 6.1
Encoder: libx265 - Scenario: Video On Demand
FPS > Higher Is Better
a . 47.03 |====================================================================
b . 47.05 |====================================================================
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 |====================================================================
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
Frames Per Second > Higher Is Better
a . 83.88 |====================================================================
b . 83.58 |====================================================================
Embree 4.3
Binary: Pathtracer ISPC - Model: Asian Dragon Obj
Frames Per Second > Higher Is Better
a . 71.49 |====================================================================
b . 71.44 |====================================================================
rav1e 0.7
Speed: 1
Frames Per Second > Higher Is Better
a . 0.85 |=====================================================================
b . 0.85 |=====================================================================
rav1e 0.7
Speed: 5
Frames Per Second > Higher Is Better
a . 3.584 |====================================================================
b . 3.596 |====================================================================
rav1e 0.7
Speed: 6
Frames Per Second > Higher Is Better
a . 4.851 |===================================================================
b . 4.891 |====================================================================
rav1e 0.7
Speed: 10
Frames Per Second > Higher Is Better
a . 12.32 |====================================================================
b . 12.36 |====================================================================
SVT-AV1 1.8
Encoder Mode: Preset 4 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 6.628 |===================================================================
b . 6.750 |====================================================================
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 12 - Input: Bosphorus 4K
Frames Per Second > Higher Is Better
a . 190.95 |==================================================================
b . 194.49 |===================================================================
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 4 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 17.08 |==================================================================
b . 17.47 |====================================================================
SVT-AV1 1.8
Encoder Mode: Preset 8 - Input: Bosphorus 1080p
Frames Per Second > Higher Is Better
a . 131.90 |===================================================================
b . 129.18 |==================================================================
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 |===================================================================
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 |==================================================================
Xmrig 6.21
Variant: Wownero - Hash Count: 1M
H/s > Higher Is Better
a . 40330.7 |==================================================================
b . 40146.1 |==================================================================
Xmrig 6.21
Variant: GhostRider - Hash Count: 1M
H/s > Higher Is Better
a . 4436.2 |===================================================================
b . 4442.9 |===================================================================
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 |==================================================================
TensorFlow 2.12
Device: CPU - Batch Size: 1 - Model: VGG-16
images/sec > Higher Is Better
a . 9.87 |=====================================================================
b . 9.87 |=====================================================================
TensorFlow 2.12
Device: CPU - Batch Size: 1 - Model: AlexNet
images/sec > Higher Is Better
a . 30.46 |====================================================================
b . 30.45 |====================================================================
TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: VGG-16
images/sec > Higher Is Better
a . 35.21 |====================================================================
b . 35.14 |====================================================================
TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: AlexNet
images/sec > Higher Is Better
a . 299.15 |===================================================================
b . 297.84 |===================================================================
TensorFlow 2.12
Device: CPU - Batch Size: 1 - Model: GoogLeNet
images/sec > Higher Is Better
a . 17 |=======================================================================
b . 17 |=======================================================================
TensorFlow 2.12
Device: CPU - Batch Size: 1 - Model: ResNet-50
images/sec > Higher Is Better
a . 5.97 |=====================================================================
b . 5.97 |=====================================================================
TensorFlow 2.12
Device: CPU - Batch Size: 16 - Model: GoogLeNet
images/sec > Higher Is Better
a . 155.77 |===================================================================
b . 155.78 |===================================================================
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: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 36.81 |====================================================================
b . 37.02 |====================================================================
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 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: 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: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 486.60 |===================================================================
b . 485.73 |===================================================================
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: 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, Sparse INT8 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 800.59 |===================================================================
b . 799.96 |===================================================================
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 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 145.62 |===================================================================
b . 145.15 |===================================================================
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 |====================================================================
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 |====================================================================
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: 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 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: 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: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream
items/sec > Higher Is Better
a . 323.07 |===================================================================
b . 322.92 |===================================================================
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 |===================================================================
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
items/sec > Higher Is Better
a . 41.01 |====================================================================
b . 40.99 |====================================================================
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: 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: 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 Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream
items/sec > Higher Is Better
a . 27.50 |====================================================================
b . 27.53 |====================================================================
QuantLib 1.32
Configuration: Multi-Threaded
MFLOPS > Higher Is Better
a . 176928.1 |=================================================================
b . 170381.3 |===============================================================
QuantLib 1.32
Configuration: Single-Threaded
MFLOPS > Higher Is Better
a . 2634.4 |===================================================================
b . 2633.8 |===================================================================
WebP2 Image Encode 20220823
Encode Settings: Default
MP/s > Higher Is Better
a . 7.44 |=====================================================================
b . 7.49 |=====================================================================
WebP2 Image Encode 20220823
Encode Settings: Quality 75, Compression Effort 7
MP/s > Higher Is Better
a . 0.54 |=====================================================================
b . 0.51 |=================================================================
WebP2 Image Encode 20220823
Encode Settings: Quality 95, Compression Effort 7
MP/s > Higher Is Better
a . 0.27 |=====================================================================
b . 0.26 |==================================================================
WebP2 Image Encode 20220823
Encode Settings: Quality 100, Compression Effort 5
MP/s > Higher Is Better
a . 11.63 |====================================================================
b . 11.68 |====================================================================
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: BLAS
Nodes Per Second > Higher Is Better
a . 315 |==============================================================
b . 354 |======================================================================
LeelaChessZero 0.30
Backend: Eigen
Nodes Per Second > Higher Is Better
a . 272 |====================================================================
b . 282 |======================================================================
Speedb 2.7
Test: Random Fill
Op/s > Higher Is Better
a . 369023 |===================================================================
b . 367684 |===================================================================
Speedb 2.7
Test: Random Read
Op/s > Higher Is Better
a . 303866048 |================================================================
b . 304143127 |================================================================
Speedb 2.7
Test: Update Random
Op/s > Higher Is Better
a . 350612 |=================================================================
b . 361192 |===================================================================
Speedb 2.7
Test: Sequential Fill
Op/s > Higher Is Better
a . 371857 |===================================================================
b . 369178 |===================================================================
Speedb 2.7
Test: Random Fill Sync
Op/s > Higher Is Better
a . 239469 |==================================================================
b . 244535 |===================================================================
Speedb 2.7
Test: Read While Writing
Op/s > Higher Is Better
a . 15411684 |=================================================================
b . 15231425 |================================================================
Speedb 2.7
Test: Read Random Write Random
Op/s > Higher Is Better
a . 2539184 |==================================================================
b . 2539687 |==================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 36.26 |====================================================================
b . 36.30 |====================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 5.1074 |==================================================================
b . 5.2170 |===================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 5.3901 |===================================================================
b . 5.3631 |===================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 1.2456 |===================================================================
b . 1.2465 |===================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 6.8554 |===================================================================
b . 6.8775 |===================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 32.97 |====================================================================
b . 33.14 |====================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 5.3704 |==================================================================
b . 5.4136 |===================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 6.7843 |===================================================================
b . 6.7891 |===================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 7.6305 |===================================================================
b . 7.5994 |===================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 24.36 |====================================================================
b . 24.37 |====================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 15.78 |====================================================================
b . 15.77 |====================================================================
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: Synchronous Single-Stream
ms/batch < Lower Is Better
a . 36.35 |====================================================================
b . 36.32 |====================================================================
CloverLeaf 1.3
Input: clover_bm
Seconds < Lower Is Better
a . 13.67 |===================================================================
b . 13.93 |====================================================================
CloverLeaf 1.3
Input: clover_bm64_short
Seconds < Lower Is Better
a . 57.21 |====================================================================
b . 57.09 |====================================================================
OpenRadioss 2023.09.15
Model: Bumper Beam
Seconds < Lower Is Better
a . 88.11 |====================================================================
b . 88.16 |====================================================================
OpenRadioss 2023.09.15
Model: Chrysler Neon 1M
Seconds < Lower Is Better
a . 297.08 |===================================================================
b . 295.72 |===================================================================
OpenRadioss 2023.09.15
Model: Cell Phone Drop Test
Seconds < Lower Is Better
a . 31.94 |====================================================================
b . 31.84 |====================================================================
OpenRadioss 2023.09.15
Model: Bird Strike on Windshield
Seconds < Lower Is Better
a . 143.85 |===================================================================
b . 142.38 |==================================================================
OpenRadioss 2023.09.15
Model: Rubber O-Ring Seal Installation
Seconds < Lower Is Better
a . 76.78 |====================================================================
b . 76.10 |===================================================================
OpenRadioss 2023.09.15
Model: INIVOL and Fluid Structure Interaction Drop Container
Seconds < Lower Is Better
a . 164.67 |===================================================================
b . 163.46 |===================================================================
easyWave r34
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240
Seconds < Lower Is Better
a . 1.947 |====================================================================
b . 1.958 |====================================================================
easyWave r34
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200
Seconds < Lower Is Better
a . 39.64 |====================================================================
b . 39.48 |====================================================================
easyWave r34
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400
Seconds < Lower Is Better
a . 111.04 |===================================================================
b . 111.07 |===================================================================
Timed FFmpeg Compilation 6.1
Time To Compile
Seconds < Lower Is Better
a . 18.15 |====================================================================
b . 18.04 |====================================================================
Timed Gem5 Compilation 23.0.1
Time To Compile
Seconds < Lower Is Better
a . 211.56 |================================================================
b . 223.06 |===================================================================
Y-Cruncher 0.8.3
Pi Digits To Calculate: 1B
Seconds < Lower Is Better
a . 10.25 |====================================================================
b . 10.20 |====================================================================
Y-Cruncher 0.8.3
Pi Digits To Calculate: 5B
Seconds < Lower Is Better
a . 53.07 |====================================================================
b . 53.15 |====================================================================
Y-Cruncher 0.8.3
Pi Digits To Calculate: 10B
Seconds < Lower Is Better
a . 112.54 |===================================================================
b . 112.81 |===================================================================
Y-Cruncher 0.8.3
Pi Digits To Calculate: 500M
Seconds < Lower Is Better
a . 5.110 |====================================================================
b . 5.106 |====================================================================
Blender 4.0
Blend File: BMW27 - Compute: CPU-Only
Seconds < Lower Is Better
a . 26.71 |====================================================================
b . 26.75 |====================================================================
Blender 4.0
Blend File: Classroom - Compute: CPU-Only
Seconds < Lower Is Better
a . 67.06 |====================================================================
b . 67.51 |====================================================================
Blender 4.0
Blend File: Fishy Cat - Compute: CPU-Only
Seconds < Lower Is Better
a . 35.54 |====================================================================
b . 35.33 |====================================================================
Blender 4.0
Blend File: Barbershop - Compute: CPU-Only
Seconds < Lower Is Better
a . 239.83 |===================================================================
b . 240.12 |===================================================================
Blender 4.0
Blend File: Pabellon Barcelona - Compute: CPU-Only
Seconds < Lower Is Better
a . 86.14 |====================================================================
b . 86.16 |====================================================================