8490h 1s

Intel Xeon Platinum 8490H testing with a Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS) and ASPEED on Ubuntu 22.04 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 2307296-NE-8490H1S1663
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a
July 28 2023
  1 Hour, 52 Minutes
b
July 28 2023
  2 Hours, 53 Minutes
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July 28 2023
  1 Hour, 26 Minutes
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July 28 2023
  1 Hour, 25 Minutes
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July 29 2023
  1 Hour, 25 Minutes
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8490h 1sOpenBenchmarking.orgPhoronix Test SuiteIntel Xeon Platinum 8490H @ 3.50GHz (60 Cores / 120 Threads)Quanta Cloud S6Q-MB-MPS (3A10.uh BIOS)Intel Device 1bce512GB3 x 3841GB Micron_9300_MTFDHAL3T8TDPASPEED4 x Intel E810-C for QSFPUbuntu 22.045.15.0-47-generic (x86_64)GNOME Shell 42.4X Server 1.21.1.31.2.204GCC 11.2.0ext41024x768ProcessorMotherboardChipsetMemoryDiskGraphicsNetworkOSKernelDesktopDisplay ServerVulkanCompilerFile-SystemScreen Resolution8490h 1s PerformanceSystem Logs- Transparent Huge Pages: madvise- --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,brig,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-targets=nvptx-none=/build/gcc-11-gBFGDP/gcc-11-11.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-gBFGDP/gcc-11-11.2.0/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 - Scaling Governor: intel_pstate performance (EPP: performance) - CPU Microcode: 0x2b0000c0 - OpenJDK Runtime Environment (build 11.0.16+8-post-Ubuntu-0ubuntu122.04)- Python 3.10.6- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling + srbds: Not affected + tsx_async_abort: Not affected

abcdeResult OverviewPhoronix Test Suite100%104%108%112%116%Apache CassandraRedis 7.0.12 + memtier_benchmarkDragonflydbBRL-CADNeural Magic DeepSparseBlender

8490h 1scryptopp: All Algorithmscryptopp: Keyed Algorithmscryptopp: Unkeyed Algorithmsbrl-cad: VGR Performance Metricdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Streamdeepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Asynchronous Multi-Streamdeepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Asynchronous Multi-Streamdeepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Synchronous Single-Streamdeepsparse: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Synchronous Single-Streamdeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Streamdeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Streamdeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Synchronous Single-Streamdeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Synchronous Single-Streamdeepsparse: ResNet-50, Baseline - Asynchronous Multi-Streamdeepsparse: ResNet-50, Baseline - Asynchronous Multi-Streamdeepsparse: ResNet-50, Baseline - Synchronous Single-Streamdeepsparse: ResNet-50, Baseline - Synchronous Single-Streamdeepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Streamdeepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Synchronous Single-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Streamblender: BMW27 - CPU-Onlyblender: Classroom - CPU-Onlyblender: Fishy Cat - CPU-Onlyblender: Barbershop - CPU-Onlyblender: Pabellon Barcelona - CPU-Onlydragonflydb: 10 - 1:5dragonflydb: 10 - 1:10dragonflydb: 10 - 1:100memtier-benchmark: Redis - 50 - 1:1memtier-benchmark: Redis - 50 - 1:5memtier-benchmark: Redis - 100 - 1:1memtier-benchmark: Redis - 100 - 1:5memtier-benchmark: Redis - 50 - 1:10memtier-benchmark: Redis - 100 - 1:10cassandra: Writesabcde1663.920955595.365201452.34373482591756.1193534.501435.491128.17021905.980815.703208.95614.7834648.317546.2475180.1415.5454192.5033155.801386.9311.4928780.499638.4127272.79913.66085672.79935.268759.48471.3144346.938886.4291184.38675.418262.575479.12521.164747.2403780.398238.3944267.99433.7271348.530486.0393183.63325.4431475.718163.0065121.88648.198975.6034396.73439.942725.0015868.497534.4904117.22668.5248218.1115137.508461.647216.214557.076525.138535.76427.955225.7468.9335.75272.9188.7314247982.4514662941.4214338166.152462536.662613416.652503378.332627400.982646929.552929613.1713469482360257.7892517.163435.361328.27351891.056515.8316209.10214.7802644.049546.5440179.68165.5592191.9935156.210987.158211.4653782.040038.3371270.22953.69615678.51525.2627746.70731.3371347.655286.2508185.74535.378661.5956486.185121.161147.2504781.302438.3727270.85363.6871348.720685.9332183.92685.4340487.464661.5102123.67818.080475.8818395.209939.958324.9917869.470234.4634114.61478.7193224.1648133.77961.891316.150457.5702520.869535.719927.989725.6369.1635.26273.1488.514476834.1014292262.5214432034.212470315.912546591.862630752.032710324.972544897.582583878.2913493282041057.9253517.837535.622328.06591891.32715.8257208.42834.7956649.297746.1781178.71895.5886191.6104156.461586.78611.5118780.529438.4104268.1463.72485677.0355.2632758.33591.3167348.011786.1641184.19665.423961.4143488.245521.087147.4151780.331238.4054271.62293.677347.591786.2759183.8195.4372487.176461.546124.62248.01975.613396.682839.931825.0071870.756734.4193116.34838.5903220.4888135.998461.608816.224157.9918516.041835.855527.88425.6970.0335.03272.6488.8314235868.6114204640.2514307949.032377430.142516320.692460387.752554516.652508415.592611551.5912170881280658.2508511.418635.592528.09011890.570515.838209.65554.7675648.386446.2436180.43865.5358190.8181157.175687.340111.4418780.314138.422270.34813.69385665.46995.2743759.42531.3146346.560686.5253184.93195.40262.1748482.435421.061347.4732778.762938.4911271.77973.6743347.512886.2939184.0475.4307485.715461.6935123.45438.094575.5523396.993639.869825.0454871.205234.4017117.22358.5255229.4472130.515361.828316.166658.2129514.898235.756927.960725.7569.1635.16272.4188.1814750102.5214205235.7114571297.772383147.072452685.992493158.972549066.222487096.512593991.114093482297757.2121520.223935.094428.4881905.149115.7168205.24284.8699633.445547.3169177.01055.642191.4971156.556285.15911.7345783.19838.2796266.34443.74995679.78055.2615709.15491.4076347.760486.1663181.19935.513461.0696488.234720.73648.2186782.543938.312264.30623.7788348.139286.1261181.12895.5183488.249461.4194120.44098.297375.7124396.165139.736825.132870.666434.4226113.24198.8247217.7184137.761461.845816.161457.5236519.268635.881627.863725.7169.2535.5272.4488.0914392511.7914390358.9914492478.362414601.072444450.112474272.952541163.682540848.352755166.14137849OpenBenchmarking.org

Crypto++

Crypto++ is a C++ class library of cryptographic algorithms. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMiB/second, More Is BetterCrypto++ 8.8Test: All Algorithmsa4008001200160020001663.921. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe

OpenBenchmarking.orgMiB/second, More Is BetterCrypto++ 8.8Test: Keyed Algorithmsa130260390520650595.371. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe

OpenBenchmarking.orgMiB/second, More Is BetterCrypto++ 8.8Test: Unkeyed Algorithmsa100200300400500452.341. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe

BRL-CAD

BRL-CAD is a cross-platform, open-source solid modeling system with built-in benchmark mode. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgVGR Performance Metric, More Is BetterBRL-CAD 7.36VGR Performance Metricdceba200K400K600K800K1000K8128068204108229778236028259171. (CXX) g++ options: -std=c++14 -pipe -fvisibility=hidden -fno-strict-aliasing -fno-common -fexceptions -ftemplate-depth-128 -m64 -ggdb3 -O3 -fipa-pta -fstrength-reduce -finline-functions -flto -ltcl8.6 -lregex_brl -lz_brl -lnetpbm -ldl -lm -ltk8.6

Neural Magic DeepSparse

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streamaebcd1326395265SE +/- 0.18, N = 356.1257.2157.7957.9358.25

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streamaecbd120240360480600SE +/- 1.23, N = 3534.50520.22517.84517.16511.42

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streamebadc816243240SE +/- 0.07, N = 335.0935.3635.4935.5935.62

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streamebadc714212835SE +/- 0.05, N = 328.4928.2728.1728.0928.07

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Streamdbcea400800120016002000SE +/- 1.24, N = 31890.571891.061891.331905.151905.98

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Streamdbcea48121620SE +/- 0.01, N = 315.8415.8315.8315.7215.70

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Streamecabd50100150200250SE +/- 0.71, N = 3205.24208.43208.96209.10209.66

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Streamecabd1.09572.19143.28714.38285.4785SE +/- 0.0162, N = 34.86994.79564.78344.78024.7675

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Streamebadc140280420560700SE +/- 5.86, N = 3633.45644.05648.32648.39649.30

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Streamebadc1122334455SE +/- 0.41, N = 347.3246.5446.2546.2446.18

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Streamecbad4080120160200SE +/- 0.21, N = 3177.01178.72179.68180.14180.44

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Streamecbad1.26952.5393.80855.0786.3475SE +/- 0.0064, N = 35.64205.58865.55925.54545.5358

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Streamdecba4080120160200SE +/- 0.10, N = 3190.82191.50191.61191.99192.50

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Streamdecba306090120150SE +/- 0.08, N = 3157.18156.56156.46156.21155.80

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Streamecabd20406080100SE +/- 0.09, N = 385.1686.7986.9387.1687.34

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Streamecabd3691215SE +/- 0.01, N = 311.7311.5111.4911.4711.44

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Streamdacbe2004006008001000SE +/- 0.80, N = 3780.31780.50780.53782.04783.20

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Streamdacbe918273645SE +/- 0.04, N = 338.4238.4138.4138.3438.28

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: ResNet-50, Baseline - Scenario: Synchronous Single-Streamecbda60120180240300SE +/- 0.64, N = 3266.34268.15270.23270.35272.80

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: ResNet-50, Baseline - Scenario: Synchronous Single-Streamecbda0.84371.68742.53113.37484.2185SE +/- 0.0089, N = 33.74993.72483.69613.69383.6608

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Streamdacbe12002400360048006000SE +/- 3.30, N = 35665.475672.805677.045678.525679.78

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Streamdacbe1.18672.37343.56014.74685.9335SE +/- 0.0032, N = 35.27435.26805.26325.26275.2615

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Streamebcda160320480640800SE +/- 0.65, N = 3709.15746.71758.34759.43759.48

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Streamebcda0.31670.63340.95011.26681.5835SE +/- 0.0011, N = 31.40761.33711.31671.31461.3144

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streamdabec80160240320400SE +/- 0.33, N = 3346.56346.94347.66347.76348.01

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streamdabec20406080100SE +/- 0.08, N = 386.5386.4386.2586.1786.16

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streamecadb4080120160200SE +/- 0.69, N = 3181.20184.20184.39184.93185.75

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streamecadb1.24052.4813.72154.9626.2025SE +/- 0.0199, N = 35.51345.42395.41825.40205.3786

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Streamecbda1428425670SE +/- 0.44, N = 361.0761.4161.6062.1762.58

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Streamcebda110220330440550SE +/- 2.68, N = 3488.25488.23486.19482.44479.13

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Streamedcba510152025SE +/- 0.07, N = 320.7421.0621.0921.1621.16

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: BERT-Large, NLP Question Answering - Scenario: Synchronous Single-Streamedcba1122334455SE +/- 0.16, N = 348.2247.4747.4247.2547.24

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streamdcabe2004006008001000SE +/- 0.42, N = 3778.76780.33780.40781.30782.54

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streamdcabe918273645SE +/- 0.02, N = 338.4938.4138.3938.3738.31

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streameabcd60120180240300SE +/- 0.45, N = 3264.31267.99270.85271.62271.78

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streameabcd0.85021.70042.55063.40084.251SE +/- 0.0060, N = 33.77883.72713.68713.67703.6743

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Streamdceab80160240320400SE +/- 0.57, N = 3347.51347.59348.14348.53348.72

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Streamdceab20406080100SE +/- 0.14, N = 386.2986.2886.1386.0485.93

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Streameacbd4080120160200SE +/- 0.31, N = 3181.13183.63183.82183.93184.05

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Streameacbd1.24162.48323.72484.96646.208SE +/- 0.0092, N = 35.51835.44315.43725.43405.4307

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streamadcbe110220330440550SE +/- 0.85, N = 3475.72485.72487.18487.46488.25

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streamadcbe1428425670SE +/- 0.11, N = 363.0161.6961.5561.5161.42

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streameadbc306090120150SE +/- 0.43, N = 3120.44121.89123.45123.68124.62

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streameadbc246810SE +/- 0.0280, N = 38.29738.19898.09458.08048.0190

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streamdaceb20406080100SE +/- 0.23, N = 375.5575.6075.6175.7175.88

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streamdaceb90180270360450SE +/- 1.22, N = 3396.99396.73396.68396.17395.21

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streamedcab918273645SE +/- 0.01, N = 339.7439.8739.9339.9439.96

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streamedcab612182430SE +/- 0.00, N = 325.1325.0525.0125.0024.99

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Streamabecd2004006008001000SE +/- 0.53, N = 3868.50869.47870.67870.76871.21

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Streamabecd816243240SE +/- 0.02, N = 334.4934.4634.4234.4234.40

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Streamebcda306090120150113.24114.61116.35117.22117.23

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Streamebcda2468108.82478.71938.59038.52558.5248

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Streameacbd50100150200250217.72218.11220.49224.16229.45

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Streameacbd306090120150137.76137.51136.00133.78130.52

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Streamcadeb142842567061.6161.6561.8361.8561.89

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Streamcadeb4812162016.2216.2116.1716.1616.15

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streamaebcd132639526557.0857.5257.5757.9958.21

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streamabecd110220330440550525.14520.87519.27516.04514.90

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.5Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streambdace81624324035.7235.7635.7635.8635.88

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.5Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streambdace71421283527.9927.9627.9627.8827.86

Blender

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: BMW27 - Compute: CPU-Onlydaecb61218243025.7525.7425.7125.6925.63

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Classroom - Compute: CPU-Onlycedba163248648070.0369.2569.1669.1668.93

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Fishy Cat - Compute: CPU-Onlyaebdc81624324035.7535.5035.2635.1635.03

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Barbershop - Compute: CPU-Onlybaced60120180240300273.14272.91272.64272.44272.41

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.6Blend File: Pabellon Barcelona - Compute: CPU-Onlycabde2040608010088.8388.7388.5088.1888.09

Dragonflydb

Dragonfly is an open-source database server that is a "modern Redis replacement" that aims to be the fastest memory store while being compliant with the Redis and Memcached protocols. For benchmarking Dragonfly, Memtier_benchmark is used as a NoSQL Redis/Memcache traffic generation plus benchmarking tool developed by Redis Labs. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgOps/sec, More Is BetterDragonflydb 1.6.2Clients Per Thread: 10 - Set To Get Ratio: 1:5caebd3M6M9M12M15MSE +/- 71046.49, N = 314235868.6114247982.4514392511.7914476834.1014750102.521. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Clients Per Thread: 20 - Set To Get Ratio: 1:5

a: The test run did not produce a result. E: Connection error: Connection reset by peer

b: The test run did not produce a result. E: Connection error: Connection reset by peer

c: The test run did not produce a result. E: Connection error: Connection reset by peer

d: The test run did not produce a result. E: Connection error: Connection reset by peer

e: The test run did not produce a result. E: Connection error: Connection reset by peer

OpenBenchmarking.orgOps/sec, More Is BetterDragonflydb 1.6.2Clients Per Thread: 10 - Set To Get Ratio: 1:10cdbea3M6M9M12M15MSE +/- 31999.75, N = 314204640.2514205235.7114292262.5214390358.9914662941.421. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Clients Per Thread: 20 - Set To Get Ratio: 1:10

a: The test run did not produce a result. E: Connection error: Connection reset by peer

b: The test run did not produce a result. E: Connection error: Connection reset by peer

c: The test run did not produce a result. E: Connection error: Connection reset by peer

d: The test run did not produce a result. E: Connection error: Connection refused

e: The test run did not produce a result. E: Connection error: Connection reset by peer

OpenBenchmarking.orgOps/sec, More Is BetterDragonflydb 1.6.2Clients Per Thread: 10 - Set To Get Ratio: 1:100cabed3M6M9M12M15MSE +/- 145332.09, N = 314307949.0314338166.1514432034.2114492478.3614571297.771. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Clients Per Thread: 20 - Set To Get Ratio: 1:100

a: The test run did not produce a result. E: Connection error: Connection refused

b: The test run did not produce a result. E: Connection error: Connection reset by peer

c: The test run did not produce a result. E: Connection error: Connection reset by peer

d: The test run did not produce a result. E: Connection error: Connection refused

e: The test run did not produce a result. E: Connection error: Connection reset by peer

Redis 7.0.12 + memtier_benchmark

Memtier_benchmark is a NoSQL Redis/Memcache traffic generation plus benchmarking tool developed by Redis Labs. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgOps/sec, More Is BetterRedis 7.0.12 + memtier_benchmark 2.0Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:1cdeab500K1000K1500K2000K2500K2377430.142383147.072414601.072462536.662470315.911. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

OpenBenchmarking.orgOps/sec, More Is BetterRedis 7.0.12 + memtier_benchmark 2.0Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5edcba600K1200K1800K2400K3000K2444450.112452685.992516320.692546591.862613416.651. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

OpenBenchmarking.orgOps/sec, More Is BetterRedis 7.0.12 + memtier_benchmark 2.0Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:1cedab600K1200K1800K2400K3000K2460387.752474272.952493158.972503378.332630752.031. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

OpenBenchmarking.orgOps/sec, More Is BetterRedis 7.0.12 + memtier_benchmark 2.0Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5edcab600K1200K1800K2400K3000K2541163.682549066.222554516.652627400.982710324.971. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

OpenBenchmarking.orgOps/sec, More Is BetterRedis 7.0.12 + memtier_benchmark 2.0Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10dceba600K1200K1800K2400K3000K2487096.512508415.592540848.352544897.582646929.551. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:1

a: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

b: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

c: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

d: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

e: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:5

a: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

b: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

c: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

d: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

e: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

OpenBenchmarking.orgOps/sec, More Is BetterRedis 7.0.12 + memtier_benchmark 2.0Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10bdcea600K1200K1800K2400K3000K2583878.292593991.102611551.592755166.142929613.171. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10

a: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

b: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

c: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

d: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

e: The test run did not produce a result. E: error: failed to prepare thread 56 for test.

Apache Cassandra

This is a benchmark of the Apache Cassandra NoSQL database management system making use of cassandra-stress. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgOp/s, More Is BetterApache Cassandra 4.1.3Test: Writescabed30K60K90K120K150K121708134694134932137849140934

79 Results Shown

Crypto++:
  All Algorithms
  Keyed Algorithms
  Unkeyed Algorithms
BRL-CAD
Neural Magic DeepSparse:
  NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Stream:
    items/sec
    ms/batch
  NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Synchronous Single-Stream:
    items/sec
    ms/batch
  NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Synchronous Single-Stream:
    items/sec
    ms/batch
  NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Synchronous Single-Stream:
    items/sec
    ms/batch
  ResNet-50, Baseline - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  ResNet-50, Baseline - Synchronous Single-Stream:
    items/sec
    ms/batch
  ResNet-50, Sparse INT8 - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  ResNet-50, Sparse INT8 - Synchronous Single-Stream:
    items/sec
    ms/batch
  CV Detection, YOLOv5s COCO - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  CV Detection, YOLOv5s COCO - Synchronous Single-Stream:
    items/sec
    ms/batch
  BERT-Large, NLP Question Answering - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  BERT-Large, NLP Question Answering - Synchronous Single-Stream:
    items/sec
    ms/batch
  CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  CV Classification, ResNet-50 ImageNet - Synchronous Single-Stream:
    items/sec
    ms/batch
  CV Detection, YOLOv5s COCO, Sparse INT8 - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  CV Detection, YOLOv5s COCO, Sparse INT8 - Synchronous Single-Stream:
    items/sec
    ms/batch
  NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  NLP Text Classification, DistilBERT mnli - Synchronous Single-Stream:
    items/sec
    ms/batch
  CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Stream:
    items/sec
    ms/batch
  BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Stream:
    items/sec
    ms/batch
  NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  NLP Text Classification, BERT base uncased SST2 - Synchronous Single-Stream:
    items/sec
    ms/batch
  NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Stream:
    items/sec
    ms/batch
  NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Stream:
    items/sec
    ms/batch
Blender:
  BMW27 - CPU-Only
  Classroom - CPU-Only
  Fishy Cat - CPU-Only
  Barbershop - CPU-Only
  Pabellon Barcelona - CPU-Only
Dragonflydb:
  10 - 1:5
  10 - 1:10
  10 - 1:100
Redis 7.0.12 + memtier_benchmark:
  Redis - 50 - 1:1
  Redis - 50 - 1:5
  Redis - 100 - 1:1
  Redis - 100 - 1:5
  Redis - 50 - 1:10
  Redis - 100 - 1:10
Apache Cassandra