ds AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) and NVIDIA NV174 8GB on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2312110-PTS-DS58174320&sor .
ds Processor Motherboard Chipset Memory Disk Graphics Audio Monitor Network OS Kernel Desktop Display Server Display Driver OpenGL Compiler File-System Screen Resolution a b c d AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads) ASUS ROG STRIX X670E-E GAMING WIFI (1416 BIOS) AMD Device 14d8 32GB 2000GB Samsung SSD 980 PRO 2TB + 4001GB Western Digital WD_BLACK SN850X 4000GB NVIDIA NV174 8GB NVIDIA GA104 HD Audio DELL U2723QE Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 Ubuntu 23.10 6.7.0-060700rc2daily20231127-generic (x86_64) GNOME Shell 45.1 X Server 1.21.1.7 + Wayland nouveau 4.3 Mesa 24.0~git2311260600.945288~oibaf~m (git-945288f 2023-11-26 mantic-oibaf-ppa) GCC 13.2.0 + LLVM 16.0.6 ext4 3840x2160 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Processor Details - Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0xa601203 Python Details - Python 3.11.6 Security Details - gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_rstack_overflow: Vulnerable: Safe RET no microcode + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced / Automatic IBRS IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
ds deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Stream deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Asynchronous Multi-Stream deepsparse: ResNet-50, Baseline - Synchronous Single-Stream deepsparse: ResNet-50, Baseline - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Stream deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream deepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream deepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream deepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream deepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream deepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream deepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream deepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream a b c d 22.7389 350.7492 19.5685 51.0955 983.3126 8.1243 299.9092 3.3312 296.0378 27.0091 197.0798 5.0670 2314.2272 3.4471 1295.8078 0.7695 127.7126 62.6288 101.8661 9.8076 29.3517 272.1665 21.1279 47.3214 296.0322 27.0107 198.8967 5.0217 133.5376 59.8641 103.1665 9.6870 203.9666 39.2065 116.3673 8.5884 38.9835 204.8572 32.3888 30.8613 462.4186 17.2878 110.6228 9.0307 22.7592 349.9757 19.5417 51.1656 22.6899 351.5559 19.5391 51.1690 988.2981 8.0835 301.5141 3.3138 295.5210 27.0574 198.4779 5.0320 2315.5240 3.4442 1295.2310 0.7698 127.2462 62.8602 101.7672 9.8180 29.3894 271.9143 21.1400 47.2956 295.7606 27.0344 198.4507 5.0331 133.1707 60.0283 103.1635 9.6883 203.4893 39.2941 116.5816 8.5729 38.8700 205.5998 32.4189 30.8326 462.6802 17.2779 110.0314 9.0802 22.7193 351.5076 19.5292 51.1975 22.7000 351.4011 19.5454 51.1551 986.6769 8.0963 301.1738 3.3173 295.7285 27.0386 198.2479 5.0382 2317.2555 3.4420 1308.7670 0.7620 127.4662 62.7323 101.8841 9.8068 29.3969 271.7780 21.1302 47.3165 295.2366 27.0809 198.7653 5.0250 132.0251 60.5733 103.3168 9.6736 203.9185 39.2164 116.7136 8.5631 39.0428 204.5755 32.4022 30.8484 461.5344 17.3189 110.0550 9.0770 22.6850 351.4431 19.5308 51.1932 22.6176 352.4834 19.5678 51.0971 987.4091 8.0908 301.6484 3.3119 295.3355 27.0742 198.3620 5.0356 2293.2480 3.4780 1299.0909 0.7672 128.0169 62.4691 101.4802 9.8453 29.3591 272.1527 21.2410 47.0684 295.5731 27.0539 198.9679 5.0198 132.5933 60.2946 103.2328 9.6809 203.6193 39.2783 117.2571 8.5234 39.1305 204.2205 32.4054 30.8462 462.4074 17.2882 110.4956 9.0414 22.7096 351.4079 19.5097 51.2514 OpenBenchmarking.org
Neural Magic DeepSparse Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream a c b d 5 10 15 20 25 SE +/- 0.03, N = 3 SE +/- 0.08, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 22.74 22.70 22.69 22.62
Neural Magic DeepSparse Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream a c b d 80 160 240 320 400 SE +/- 0.16, N = 3 SE +/- 0.75, N = 3 SE +/- 0.09, N = 3 SE +/- 0.20, N = 3 350.75 351.40 351.56 352.48
Neural Magic DeepSparse Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream a d c b 5 10 15 20 25 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 19.57 19.57 19.55 19.54
Neural Magic DeepSparse Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream a d c b 12 24 36 48 60 SE +/- 0.06, N = 3 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 51.10 51.10 51.16 51.17
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream b d c a 200 400 600 800 1000 SE +/- 0.99, N = 3 SE +/- 1.44, N = 3 SE +/- 1.16, N = 3 SE +/- 0.48, N = 3 988.30 987.41 986.68 983.31
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream b d c a 2 4 6 8 10 SE +/- 0.0081, N = 3 SE +/- 0.0118, N = 3 SE +/- 0.0093, N = 3 SE +/- 0.0039, N = 3 8.0835 8.0908 8.0963 8.1243
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream d b c a 70 140 210 280 350 SE +/- 0.32, N = 3 SE +/- 0.53, N = 3 SE +/- 1.04, N = 3 SE +/- 0.35, N = 3 301.65 301.51 301.17 299.91
Neural Magic DeepSparse Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream d b c a 0.7495 1.499 2.2485 2.998 3.7475 SE +/- 0.0036, N = 3 SE +/- 0.0056, N = 3 SE +/- 0.0115, N = 3 SE +/- 0.0038, N = 3 3.3119 3.3138 3.3173 3.3312
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream a c b d 60 120 180 240 300 SE +/- 0.11, N = 3 SE +/- 0.15, N = 3 SE +/- 0.12, N = 3 SE +/- 0.10, N = 3 296.04 295.73 295.52 295.34
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream a c b d 6 12 18 24 30 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 27.01 27.04 27.06 27.07
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream b d c a 40 80 120 160 200 SE +/- 0.91, N = 3 SE +/- 0.35, N = 3 SE +/- 0.03, N = 3 SE +/- 0.82, N = 3 198.48 198.36 198.25 197.08
Neural Magic DeepSparse Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream b d c a 1.1401 2.2802 3.4203 4.5604 5.7005 SE +/- 0.0228, N = 3 SE +/- 0.0087, N = 3 SE +/- 0.0010, N = 3 SE +/- 0.0211, N = 3 5.0320 5.0356 5.0382 5.0670
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream c b a d 500 1000 1500 2000 2500 SE +/- 4.26, N = 3 SE +/- 6.99, N = 3 SE +/- 1.66, N = 3 SE +/- 8.04, N = 3 2317.26 2315.52 2314.23 2293.25
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream c b a d 0.7826 1.5652 2.3478 3.1304 3.913 SE +/- 0.0064, N = 3 SE +/- 0.0106, N = 3 SE +/- 0.0021, N = 3 SE +/- 0.0122, N = 3 3.4420 3.4442 3.4471 3.4780
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream c d a b 300 600 900 1200 1500 SE +/- 1.41, N = 3 SE +/- 0.19, N = 3 SE +/- 10.93, N = 3 SE +/- 7.10, N = 3 1308.77 1299.09 1295.81 1295.23
Neural Magic DeepSparse Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream c d a b 0.1732 0.3464 0.5196 0.6928 0.866 SE +/- 0.0008, N = 3 SE +/- 0.0001, N = 3 SE +/- 0.0065, N = 3 SE +/- 0.0041, N = 3 0.7620 0.7672 0.7695 0.7698
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream d a c b 30 60 90 120 150 SE +/- 0.24, N = 3 SE +/- 0.61, N = 3 SE +/- 0.72, N = 3 SE +/- 0.56, N = 3 128.02 127.71 127.47 127.25
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream d a c b 14 28 42 56 70 SE +/- 0.12, N = 3 SE +/- 0.30, N = 3 SE +/- 0.37, N = 3 SE +/- 0.28, N = 3 62.47 62.63 62.73 62.86
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream c a b d 20 40 60 80 100 SE +/- 0.04, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 SE +/- 0.19, N = 3 101.88 101.87 101.77 101.48
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream c a b d 3 6 9 12 15 SE +/- 0.0035, N = 3 SE +/- 0.0059, N = 3 SE +/- 0.0053, N = 3 SE +/- 0.0182, N = 3 9.8068 9.8076 9.8180 9.8453
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream c b d a 7 14 21 28 35 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 29.40 29.39 29.36 29.35
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream c b d a 60 120 180 240 300 SE +/- 0.09, N = 3 SE +/- 0.13, N = 3 SE +/- 0.09, N = 3 SE +/- 0.01, N = 3 271.78 271.91 272.15 272.17
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream d b c a 5 10 15 20 25 SE +/- 0.01, N = 3 SE +/- 0.04, N = 3 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 21.24 21.14 21.13 21.13
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Stream d b c a 11 22 33 44 55 SE +/- 0.01, N = 3 SE +/- 0.09, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 47.07 47.30 47.32 47.32
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream a b d c 60 120 180 240 300 SE +/- 0.22, N = 3 SE +/- 0.22, N = 3 SE +/- 0.38, N = 3 SE +/- 0.26, N = 3 296.03 295.76 295.57 295.24
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream a b d c 6 12 18 24 30 SE +/- 0.02, N = 3 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.02, N = 3 27.01 27.03 27.05 27.08
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream d a c b 40 80 120 160 200 SE +/- 0.45, N = 3 SE +/- 0.11, N = 3 SE +/- 0.17, N = 3 SE +/- 0.31, N = 3 198.97 198.90 198.77 198.45
Neural Magic DeepSparse Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream d a c b 1.1324 2.2648 3.3972 4.5296 5.662 SE +/- 0.0116, N = 3 SE +/- 0.0028, N = 3 SE +/- 0.0044, N = 3 SE +/- 0.0078, N = 3 5.0198 5.0217 5.0250 5.0331
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b d c 30 60 90 120 150 SE +/- 0.30, N = 3 SE +/- 0.59, N = 3 SE +/- 0.43, N = 3 SE +/- 0.45, N = 3 133.54 133.17 132.59 132.03
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream a b d c 14 28 42 56 70 SE +/- 0.13, N = 3 SE +/- 0.27, N = 3 SE +/- 0.21, N = 3 SE +/- 0.21, N = 3 59.86 60.03 60.29 60.57
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream c d a b 20 40 60 80 100 SE +/- 0.00, N = 3 SE +/- 0.14, N = 3 SE +/- 0.06, N = 3 SE +/- 0.06, N = 3 103.32 103.23 103.17 103.16
Neural Magic DeepSparse Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream c d a b 3 6 9 12 15 SE +/- 0.0004, N = 3 SE +/- 0.0125, N = 3 SE +/- 0.0055, N = 3 SE +/- 0.0056, N = 3 9.6736 9.6809 9.6870 9.6883
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream a c d b 40 80 120 160 200 SE +/- 0.15, N = 3 SE +/- 0.24, N = 3 SE +/- 0.23, N = 3 SE +/- 0.06, N = 3 203.97 203.92 203.62 203.49
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream a c d b 9 18 27 36 45 SE +/- 0.03, N = 3 SE +/- 0.04, N = 3 SE +/- 0.05, N = 3 SE +/- 0.01, N = 3 39.21 39.22 39.28 39.29
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream d c b a 30 60 90 120 150 SE +/- 0.43, N = 3 SE +/- 0.84, N = 3 SE +/- 0.80, N = 3 SE +/- 0.35, N = 3 117.26 116.71 116.58 116.37
Neural Magic DeepSparse Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream d c b a 2 4 6 8 10 SE +/- 0.0316, N = 3 SE +/- 0.0624, N = 3 SE +/- 0.0593, N = 3 SE +/- 0.0256, N = 3 8.5234 8.5631 8.5729 8.5884
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream d c a b 9 18 27 36 45 SE +/- 0.13, N = 3 SE +/- 0.07, N = 3 SE +/- 0.08, N = 3 SE +/- 0.36, N = 3 39.13 39.04 38.98 38.87
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream d c a b 50 100 150 200 250 SE +/- 0.62, N = 3 SE +/- 0.32, N = 3 SE +/- 0.47, N = 3 SE +/- 1.77, N = 3 204.22 204.58 204.86 205.60
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream b d c a 8 16 24 32 40 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 32.42 32.41 32.40 32.39
Neural Magic DeepSparse Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream b d c a 7 14 21 28 35 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.01, N = 3 SE +/- 0.05, N = 3 30.83 30.85 30.85 30.86
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream b a d c 100 200 300 400 500 SE +/- 0.43, N = 3 SE +/- 0.23, N = 3 SE +/- 0.35, N = 3 SE +/- 0.34, N = 3 462.68 462.42 462.41 461.53
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream b a d c 4 8 12 16 20 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 SE +/- 0.01, N = 3 17.28 17.29 17.29 17.32
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream a d c b 20 40 60 80 100 SE +/- 0.42, N = 3 SE +/- 0.78, N = 3 SE +/- 0.22, N = 3 SE +/- 0.94, N = 3 110.62 110.50 110.06 110.03
Neural Magic DeepSparse Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream a d c b 3 6 9 12 15 SE +/- 0.0337, N = 3 SE +/- 0.0640, N = 3 SE +/- 0.0179, N = 3 SE +/- 0.0759, N = 3 9.0307 9.0414 9.0770 9.0802
Neural Magic DeepSparse Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream a b d c 5 10 15 20 25 SE +/- 0.07, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.02, N = 3 22.76 22.72 22.71 22.69
Neural Magic DeepSparse Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream a d c b 80 160 240 320 400 SE +/- 1.12, N = 3 SE +/- 0.17, N = 3 SE +/- 0.11, N = 3 SE +/- 0.23, N = 3 349.98 351.41 351.44 351.51
Neural Magic DeepSparse Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream OpenBenchmarking.org items/sec, More Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream a c b d 5 10 15 20 25 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 SE +/- 0.01, N = 3 SE +/- 0.03, N = 3 19.54 19.53 19.53 19.51
Neural Magic DeepSparse Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream OpenBenchmarking.org ms/batch, Fewer Is Better Neural Magic DeepSparse 1.6 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream a c b d 12 24 36 48 60 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 SE +/- 0.03, N = 3 SE +/- 0.08, N = 3 51.17 51.19 51.20 51.25
Phoronix Test Suite v10.8.4