INTEL XEON PLATINUM 8592+ testing with a Quanta Cloud S6Q-MB-MPS (3B05.TEL4P1 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 2312187-NE-NET50813920 net - Phoronix Test Suite net INTEL XEON PLATINUM 8592+ testing with a Quanta Cloud S6Q-MB-MPS (3B05.TEL4P1 BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2312187-NE-NET50813920&sor&grw .
net Processor Motherboard Chipset Memory Disk Graphics OS Kernel Desktop Display Server Compiler File-System Screen Resolution a b c INTEL XEON PLATINUM 8592+ @ 3.90GHz (64 Cores / 128 Threads) Quanta Cloud S6Q-MB-MPS (3B05.TEL4P1 BIOS) Intel Device 1bce 512GB 3201GB Micron_7450_MTFDKCC3T2TFS + 0GB Virtual HDisk0 + 0GB Virtual HDisk2 + 0GB Virtual HDisk1 + 0GB Virtual HDisk3 ASPEED Ubuntu 23.10 6.6.0-rc5-phx-patched (x86_64) GNOME Shell 45.0 X Server 1.21.1.7 GCC 13.2.0 ext4 1920x1200 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v Processor Details - Scaling Governor: intel_pstate performance (EPP: performance) - CPU Microcode: 0x21000161 Java Details - a: OpenJDK Runtime Environment (build 11.0.20+8-post-Ubuntu-1ubuntu1) 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: Not affected + 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 RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected
net xmrig: KawPow - 1M xmrig: Monero - 1M xmrig: Wownero - 1M xmrig: GhostRider - 1M xmrig: CryptoNight-Heavy - 1M xmrig: CryptoNight-Femto UPX2 - 1M lczero: BLAS lczero: Eigen 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 svt-av1: Preset 4 - Bosphorus 4K svt-av1: Preset 8 - Bosphorus 4K svt-av1: Preset 12 - Bosphorus 4K svt-av1: Preset 13 - Bosphorus 4K svt-av1: Preset 4 - Bosphorus 1080p svt-av1: Preset 8 - Bosphorus 1080p svt-av1: Preset 12 - Bosphorus 1080p svt-av1: Preset 13 - Bosphorus 1080p a b c 39936.2 40329.6 43088.3 6862.9 40394.9 40425.9 67 796 71.9864 442.3119 34.4749 29.0016 2323.9799 13.7504 210.9638 4.7354 934.6524 34.2126 286.8882 3.4825 5706.6964 5.5953 701.7915 1.4200 436.5226 73.2660 164.9393 6.0577 86.3024 370.7287 31.2246 32.0197 933.0074 34.2750 290.0133 3.4452 452.1951 70.7373 166.6567 5.9970 641.1047 49.8955 186.0257 5.3729 96.1343 332.8063 35.1023 28.4611 938.0661 34.0725 67.8694 14.7276 72.0462 442.2210 34.6092 28.8890 7.156 75.139 228.874 227.285 20.770 139.811 545.910 632.459 40344.7 40153.2 42998.7 6857.8 40282.2 40080.4 67 805 71.6759 443.3971 34.4826 28.9953 2324.7362 13.7462 210.8100 4.7386 928.4462 34.4463 290.2826 3.4417 5717.5185 5.5844 705.8268 1.4123 436.3286 73.2935 164.8968 6.0589 86.2914 370.7761 31.1465 32.0999 934.5224 34.2173 288.6849 3.4609 452.1641 70.7412 166.5123 6.0023 637.6092 50.1708 188.5376 5.3005 95.6329 334.3153 34.6174 28.8654 937.5775 34.0905 68.1760 14.6612 72.0875 441.4776 34.6250 28.8756 7.168 75.737 229.514 229.556 20.587 141.977 543.725 636.909 40242.5 40072.2 43080.4 6820.8 40286.6 40331.1 68 817 71.9685 442.7525 34.2377 29.2030 2322.5803 13.7597 209.6095 4.7654 939.5363 34.0380 287.3469 3.4767 5704.9530 5.5965 701.7061 1.4205 435.4932 73.4267 163.9718 6.0922 86.1709 371.2957 31.1875 32.0585 940.2198 34.0080 289.8081 3.4473 450.4918 71.0046 166.3050 6.0096 637.4175 50.1864 188.2324 5.3092 96.8521 330.3352 33.7246 29.6799 937.8630 34.0792 67.5802 14.7898 71.7827 443.1582 34.4526 29.0205 7.151 74.926 228.518 229.075 20.492 141.873 546.877 637.337 OpenBenchmarking.org
Xmrig Variant: KawPow - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: KawPow - Hash Count: 1M b c a 9K 18K 27K 36K 45K SE +/- 97.76, N = 3 SE +/- 102.95, N = 3 SE +/- 185.86, N = 3 40344.7 40242.5 39936.2 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: Monero - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: Monero - Hash Count: 1M a b c 9K 18K 27K 36K 45K SE +/- 106.27, N = 3 SE +/- 234.97, N = 3 SE +/- 234.22, N = 3 40329.6 40153.2 40072.2 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: Wownero - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: Wownero - Hash Count: 1M a c b 9K 18K 27K 36K 45K SE +/- 76.66, N = 3 SE +/- 104.95, N = 3 SE +/- 81.91, N = 3 43088.3 43080.4 42998.7 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: GhostRider - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: GhostRider - Hash Count: 1M a b c 1500 3000 4500 6000 7500 SE +/- 5.37, N = 3 SE +/- 29.78, N = 3 SE +/- 18.86, N = 3 6862.9 6857.8 6820.8 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: CryptoNight-Heavy - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: CryptoNight-Heavy - Hash Count: 1M a c b 9K 18K 27K 36K 45K SE +/- 42.10, N = 3 SE +/- 169.87, N = 3 SE +/- 64.66, N = 3 40394.9 40286.6 40282.2 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
Xmrig Variant: CryptoNight-Femto UPX2 - Hash Count: 1M OpenBenchmarking.org H/s, More Is Better Xmrig 6.21 Variant: CryptoNight-Femto UPX2 - Hash Count: 1M a c b 9K 18K 27K 36K 45K SE +/- 55.21, N = 3 SE +/- 88.91, N = 3 SE +/- 72.11, N = 3 40425.9 40331.1 40080.4 1. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc
LeelaChessZero Backend: BLAS OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.30 Backend: BLAS c b a 15 30 45 60 75 SE +/- 0.58, N = 3 SE +/- 0.67, N = 3 SE +/- 0.67, N = 3 68 67 67 1. (CXX) g++ options: -flto -pthread
LeelaChessZero Backend: Eigen OpenBenchmarking.org Nodes Per Second, More Is Better LeelaChessZero 0.30 Backend: Eigen c b a 200 400 600 800 1000 SE +/- 32.94, N = 6 SE +/- 11.08, N = 9 SE +/- 21.82, N = 9 817 805 796 1. (CXX) g++ options: -flto -pthread
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 16 32 48 64 80 SE +/- 0.16, N = 3 SE +/- 0.20, N = 3 SE +/- 0.17, N = 3 71.99 71.97 71.68
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 100 200 300 400 500 SE +/- 0.57, N = 3 SE +/- 0.77, N = 3 SE +/- 0.20, N = 3 442.31 442.75 443.40
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 b a c 8 16 24 32 40 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 SE +/- 0.07, N = 3 34.48 34.47 34.24
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 b a c 7 14 21 28 35 SE +/- 0.05, N = 3 SE +/- 0.02, N = 3 SE +/- 0.06, N = 3 29.00 29.00 29.20
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 a c 500 1000 1500 2000 2500 SE +/- 2.92, N = 3 SE +/- 2.42, N = 3 SE +/- 0.54, N = 3 2324.74 2323.98 2322.58
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 a c 4 8 12 16 20 SE +/- 0.02, N = 3 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 13.75 13.75 13.76
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 a b c 50 100 150 200 250 SE +/- 1.74, N = 3 SE +/- 0.83, N = 3 SE +/- 0.49, N = 3 210.96 210.81 209.61
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 a b c 1.0722 2.1444 3.2166 4.2888 5.361 SE +/- 0.0394, N = 3 SE +/- 0.0188, N = 3 SE +/- 0.0109, N = 3 4.7354 4.7386 4.7654
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 c a b 200 400 600 800 1000 SE +/- 0.83, N = 3 SE +/- 3.60, N = 3 SE +/- 8.90, N = 3 939.54 934.65 928.45
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 c a b 8 16 24 32 40 SE +/- 0.03, N = 3 SE +/- 0.13, N = 3 SE +/- 0.33, N = 3 34.04 34.21 34.45
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 c a 60 120 180 240 300 SE +/- 0.65, N = 3 SE +/- 1.23, N = 3 SE +/- 0.98, N = 3 290.28 287.35 286.89
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 c a 0.7836 1.5672 2.3508 3.1344 3.918 SE +/- 0.0077, N = 3 SE +/- 0.0147, N = 3 SE +/- 0.0119, N = 3 3.4417 3.4767 3.4825
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 b a c 1200 2400 3600 4800 6000 SE +/- 10.52, N = 3 SE +/- 15.58, N = 3 SE +/- 16.89, N = 3 5717.52 5706.70 5704.95
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 b a c 1.2592 2.5184 3.7776 5.0368 6.296 SE +/- 0.0102, N = 3 SE +/- 0.0153, N = 3 SE +/- 0.0160, N = 3 5.5844 5.5953 5.5965
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 b a c 150 300 450 600 750 SE +/- 2.96, N = 3 SE +/- 2.07, N = 3 SE +/- 0.26, N = 3 705.83 701.79 701.71
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 b a c 0.3196 0.6392 0.9588 1.2784 1.598 SE +/- 0.0057, N = 3 SE +/- 0.0038, N = 3 SE +/- 0.0007, N = 3 1.4123 1.4200 1.4205
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 a b c 90 180 270 360 450 SE +/- 0.33, N = 3 SE +/- 0.34, N = 3 SE +/- 0.19, N = 3 436.52 436.33 435.49
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 a b c 16 32 48 64 80 SE +/- 0.05, N = 3 SE +/- 0.05, N = 3 SE +/- 0.03, N = 3 73.27 73.29 73.43
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 a b c 40 80 120 160 200 SE +/- 0.67, N = 3 SE +/- 0.12, N = 3 SE +/- 0.23, N = 3 164.94 164.90 163.97
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 a b c 2 4 6 8 10 SE +/- 0.0247, N = 3 SE +/- 0.0043, N = 3 SE +/- 0.0081, N = 3 6.0577 6.0589 6.0922
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 a b c 20 40 60 80 100 SE +/- 0.14, N = 3 SE +/- 0.09, N = 3 SE +/- 0.05, N = 3 86.30 86.29 86.17
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 a b c 80 160 240 320 400 SE +/- 0.59, N = 3 SE +/- 0.36, N = 3 SE +/- 0.22, N = 3 370.73 370.78 371.30
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 a c b 7 14 21 28 35 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.03, N = 3 31.22 31.19 31.15
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 a c b 7 14 21 28 35 SE +/- 0.02, N = 3 SE +/- 0.08, N = 3 SE +/- 0.03, N = 3 32.02 32.06 32.10
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 c b a 200 400 600 800 1000 SE +/- 0.19, N = 3 SE +/- 4.66, N = 3 SE +/- 3.85, N = 3 940.22 934.52 933.01
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 c b a 8 16 24 32 40 SE +/- 0.01, N = 3 SE +/- 0.17, N = 3 SE +/- 0.14, N = 3 34.01 34.22 34.28
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 a c b 60 120 180 240 300 SE +/- 1.63, N = 3 SE +/- 0.98, N = 3 SE +/- 0.99, N = 3 290.01 289.81 288.68
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 a c b 0.7787 1.5574 2.3361 3.1148 3.8935 SE +/- 0.0193, N = 3 SE +/- 0.0117, N = 3 SE +/- 0.0119, N = 3 3.4452 3.4473 3.4609
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 c 100 200 300 400 500 SE +/- 0.30, N = 3 SE +/- 0.02, N = 3 SE +/- 0.54, N = 3 452.20 452.16 450.49
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 c 16 32 48 64 80 SE +/- 0.05, N = 3 SE +/- 0.00, N = 3 SE +/- 0.09, N = 3 70.74 70.74 71.00
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 a b c 40 80 120 160 200 SE +/- 0.33, N = 3 SE +/- 0.25, N = 3 SE +/- 0.19, N = 3 166.66 166.51 166.31
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 a b c 2 4 6 8 10 SE +/- 0.0119, N = 3 SE +/- 0.0087, N = 3 SE +/- 0.0069, N = 3 5.9970 6.0023 6.0096
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 b c 140 280 420 560 700 SE +/- 0.45, N = 3 SE +/- 1.94, N = 3 SE +/- 2.11, N = 3 641.10 637.61 637.42
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 b c 11 22 33 44 55 SE +/- 0.03, N = 3 SE +/- 0.15, N = 3 SE +/- 0.17, N = 3 49.90 50.17 50.19
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 b c a 40 80 120 160 200 SE +/- 0.69, N = 3 SE +/- 0.41, N = 3 SE +/- 1.59, N = 3 188.54 188.23 186.03
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 b c a 1.2089 2.4178 3.6267 4.8356 6.0445 SE +/- 0.0193, N = 3 SE +/- 0.0116, N = 3 SE +/- 0.0459, N = 3 5.3005 5.3092 5.3729
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 c a b 20 40 60 80 100 SE +/- 0.08, N = 3 SE +/- 0.29, N = 3 SE +/- 0.27, N = 3 96.85 96.13 95.63
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 c a b 70 140 210 280 350 SE +/- 0.28, N = 3 SE +/- 1.00, N = 3 SE +/- 0.71, N = 3 330.34 332.81 334.32
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 a b c 8 16 24 32 40 SE +/- 0.16, N = 3 SE +/- 0.35, N = 3 SE +/- 0.38, N = 15 35.10 34.62 33.72
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 a b c 7 14 21 28 35 SE +/- 0.12, N = 3 SE +/- 0.29, N = 3 SE +/- 0.34, N = 15 28.46 28.87 29.68
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 a c b 200 400 600 800 1000 SE +/- 0.34, N = 3 SE +/- 0.07, N = 3 SE +/- 0.09, N = 3 938.07 937.86 937.58
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 a c b 8 16 24 32 40 SE +/- 0.01, N = 3 SE +/- 0.00, N = 3 SE +/- 0.00, N = 3 34.07 34.08 34.09
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 b a c 15 30 45 60 75 SE +/- 0.12, N = 3 SE +/- 0.27, N = 3 SE +/- 0.11, N = 3 68.18 67.87 67.58
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 b a c 4 8 12 16 20 SE +/- 0.03, N = 3 SE +/- 0.06, N = 3 SE +/- 0.02, N = 3 14.66 14.73 14.79
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 b a c 16 32 48 64 80 SE +/- 0.04, N = 3 SE +/- 0.17, N = 3 SE +/- 0.07, N = 3 72.09 72.05 71.78
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 b a c 100 200 300 400 500 SE +/- 0.59, N = 3 SE +/- 0.73, N = 3 SE +/- 0.25, N = 3 441.48 442.22 443.16
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 b a c 8 16 24 32 40 SE +/- 0.02, N = 3 SE +/- 0.04, N = 3 SE +/- 0.03, N = 3 34.63 34.61 34.45
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 b a c 7 14 21 28 35 SE +/- 0.02, N = 3 SE +/- 0.03, N = 3 SE +/- 0.03, N = 3 28.88 28.89 29.02
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 4 - Input: Bosphorus 4K b a c 2 4 6 8 10 SE +/- 0.025, N = 3 SE +/- 0.022, N = 3 SE +/- 0.071, N = 3 7.168 7.156 7.151 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 8 - Input: Bosphorus 4K b a c 20 40 60 80 100 SE +/- 0.27, N = 3 SE +/- 0.38, N = 3 SE +/- 0.15, N = 3 75.74 75.14 74.93 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 12 - Input: Bosphorus 4K b a c 50 100 150 200 250 SE +/- 1.07, N = 3 SE +/- 0.42, N = 3 SE +/- 1.46, N = 3 229.51 228.87 228.52 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 4K OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 13 - Input: Bosphorus 4K b c a 50 100 150 200 250 SE +/- 0.75, N = 3 SE +/- 0.19, N = 3 SE +/- 2.23, N = 3 229.56 229.08 227.29 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 4 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 4 - Input: Bosphorus 1080p a b c 5 10 15 20 25 SE +/- 0.08, N = 3 SE +/- 0.01, N = 3 SE +/- 0.25, N = 3 20.77 20.59 20.49 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 8 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 8 - Input: Bosphorus 1080p b c a 30 60 90 120 150 SE +/- 1.29, N = 7 SE +/- 1.86, N = 3 SE +/- 0.16, N = 3 141.98 141.87 139.81 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 12 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 12 - Input: Bosphorus 1080p c a b 120 240 360 480 600 SE +/- 4.85, N = 3 SE +/- 4.95, N = 3 SE +/- 3.52, N = 3 546.88 545.91 543.73 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
SVT-AV1 Encoder Mode: Preset 13 - Input: Bosphorus 1080p OpenBenchmarking.org Frames Per Second, More Is Better SVT-AV1 1.8 Encoder Mode: Preset 13 - Input: Bosphorus 1080p c b a 140 280 420 560 700 SE +/- 4.46, N = 3 SE +/- 4.83, N = 3 SE +/- 3.46, N = 3 637.34 636.91 632.46 1. (CXX) g++ options: -march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq
Phoronix Test Suite v10.8.4