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
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results
Show Result Confidence Charts

Limit displaying results to tests within:

CPU Massive 2 Tests
Creator Workloads 2 Tests
Database Test Suite 3 Tests
Multi-Core 2 Tests
Server 3 Tests
Common Workstation Benchmarks 2 Tests

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Geometric Means Per-Suite/Category
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
a
July 28 2023
  1 Hour, 52 Minutes
b
July 28 2023
  2 Hours, 53 Minutes
c
July 28 2023
  1 Hour, 26 Minutes
d
July 28 2023
  1 Hour, 25 Minutes
e
July 29 2023
  1 Hour, 25 Minutes
Invert Hiding All Results Option
  1 Hour, 48 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


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 1sbrl-cad: VGR Performance Metriccryptopp: All Algorithmscryptopp: Keyed Algorithmsblender: Barbershop - CPU-Onlycryptopp: Unkeyed Algorithmsdeepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering - Asynchronous Multi-Streamcassandra: Writesdeepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Streamdeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Synchronous Single-Streamdragonflydb: 10 - 1:5dragonflydb: 10 - 1:100dragonflydb: 10 - 1:10blender: Pabellon Barcelona - CPU-Onlydeepsparse: BERT-Large, NLP Question Answering, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: BERT-Large, NLP Question Answering, 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: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-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 Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-Streammemtier-benchmark: Redis - 100 - 1:10memtier-benchmark: Redis - 100 - 1:5memtier-benchmark: Redis - 100 - 1:1blender: Classroom - CPU-Onlydeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Streamdeepsparse: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Asynchronous Multi-Streammemtier-benchmark: Redis - 50 - 1:5memtier-benchmark: Redis - 50 - 1:10memtier-benchmark: Redis - 50 - 1:1deepsparse: NLP Document Classification, oBERT base uncased on IMDB - Synchronous Single-Streamdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - 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: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-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: 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 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 Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: ResNet-50, Sparse INT8 - Synchronous Single-Streamdeepsparse: ResNet-50, Sparse INT8 - 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: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Asynchronous Multi-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: 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: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: ResNet-50, Sparse INT8 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Asynchronous Multi-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - 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 - Synchronous Single-Streamdeepsparse: NLP Token Classification, BERT base uncased conll2003 - Synchronous Single-Streamblender: Fishy Cat - CPU-Onlyblender: BMW27 - CPU-Onlydragonflydb: 20 - 1:100abcde8259171663.920955595.365201272.91452.343734479.12562.57513469447.240321.16478.5248117.226614247982.4514338166.1514662941.4288.7334.4904868.49754.7834208.9561396.73475.603415.7031905.9808534.501456.11932929613.172627400.982503378.3368.93155.8013192.50332613416.652646929.552462536.6628.170235.491146.2475648.317525.001539.942711.492886.935.5454180.14163.0065475.71818.1989121.88645.4182184.38671.3144759.484738.4127780.49963.6608272.799186.4291346.938886.0393348.53045.4431183.633238.3944780.39823.7271267.99435.2685672.7993137.5084218.1115525.138557.07616.214561.647227.955235.76435.7525.74823602273.14486.185161.595613493247.250421.16118.7193114.614714476834.1014432034.2114292262.5288.534.4634869.47024.7802209.1021395.209975.881815.83161891.0565517.163457.78922583878.292710324.972630752.0369.16156.2109191.99352546591.862544897.582470315.9128.273535.361346.5440644.049524.991739.958311.465387.15825.5592179.681661.5102487.46468.0804123.67815.3786185.74531.3371746.707338.3371782.04003.6961270.229586.2508347.655285.9332348.72065.4340183.926838.3727781.30243.6871270.85365.26275678.5152133.779224.1648520.869557.570216.150461.891327.989735.719935.2625.63820410272.64488.245561.414312170847.415121.08718.5903116.348314235868.6114307949.0314204640.2588.8334.4193870.75674.7956208.4283396.682875.61315.82571891.327517.837557.92532611551.592554516.652460387.7570.03156.4615191.61042516320.692508415.592377430.1428.065935.622346.1781649.297725.007139.931811.511886.7865.5886178.718961.546487.17648.019124.62245.4239184.19661.3167758.335938.4104780.52943.7248268.14686.1641348.011786.2759347.59175.4372183.81938.4054780.33123.677271.62295.26325677.035135.9984220.4888516.041857.991816.224161.608827.88435.855535.0325.69812806272.41482.435462.174814093447.473221.06138.5255117.223514750102.5214571297.7714205235.7188.1834.4017871.20524.7675209.6555396.993675.552315.8381890.5705511.418658.25082593991.12549066.222493158.9769.16157.1756190.81812452685.992487096.512383147.0728.090135.592546.2436648.386425.045439.869811.441887.34015.5358180.438661.6935485.71548.0945123.45435.402184.93191.3146759.425338.422780.31413.6938270.348186.5253346.560686.2939347.51285.4307184.04738.4911778.76293.6743271.77975.27435665.4699130.5153229.4472514.898258.212916.166661.828327.960735.756935.1625.75822977272.44488.234761.069613784948.218620.7368.8247113.241914392511.7914492478.3614390358.9988.0934.4226870.66644.8699205.2428396.165175.712415.71681905.1491520.223957.21212755166.142541163.682474272.9569.25156.5562191.49712444450.112540848.352414601.0728.48835.094447.3169633.445525.13239.736811.734585.1595.642177.010561.4194488.24948.2973120.44095.5134181.19931.4076709.154938.2796783.1983.7499266.344486.1663347.760486.1261348.13925.5183181.128938.312782.54393.7788264.30625.26155679.7805137.7614217.7184519.268657.523616.161461.845827.863735.881635.525.71OpenBenchmarking.org

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

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

Blender

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

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: Unkeyed Algorithmsa100200300400500452.341. (CXX) g++ options: -g2 -O3 -fPIC -pthread -pipe

Neural Magic DeepSparse

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: Asynchronous Multi-Streamecbda1428425670SE +/- 0.44, N = 361.0761.4161.6062.1762.58

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

Neural Magic DeepSparse

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: 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, Sparse INT8 - Scenario: Synchronous Single-Streamebcda2468108.82478.71938.59038.52558.5248

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

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

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

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

Blender

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

Neural Magic DeepSparse

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: Asynchronous Multi-Streamabecd2004006008001000SE +/- 0.53, N = 3868.50869.47870.67870.76871.21

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 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: 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: Asynchronous Multi-Streamdaceb20406080100SE +/- 0.23, N = 375.5575.6075.6175.7175.88

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: Asynchronous Multi-Streamdbcea400800120016002000SE +/- 1.24, N = 31890.571891.061891.331905.151905.98

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: Asynchronous Multi-Streamaebcd1326395265SE +/- 0.18, N = 356.1257.2157.7957.9358.25

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: 100 - Set To Get Ratio: 1:10bdcea600K1200K1800K2400K3000K2583878.292593991.102611551.592755166.142929613.171. (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: 100 - Set To Get Ratio: 1:1cedab600K1200K1800K2400K3000K2460387.752474272.952493158.972503378.332630752.031. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Blender

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

Neural Magic DeepSparse

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: Asynchronous Multi-Streamdecba4080120160200SE +/- 0.10, N = 3190.82191.50191.61191.99192.50

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: 1:5edcba600K1200K1800K2400K3000K2444450.112452685.992516320.692546591.862613416.651. (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: 50 - Set To Get Ratio: 1:10dceba600K1200K1800K2400K3000K2487096.512508415.592540848.352544897.582646929.551. (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: 1:1cdeab500K1000K1500K2000K2500K2377430.142383147.072414601.072462536.662470315.911. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Neural Magic DeepSparse

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 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 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: Asynchronous Multi-Streamebadc140280420560700SE +/- 5.86, N = 3633.45644.05648.32648.39649.30

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: 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: 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: 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 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 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 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: 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: Synchronous Single-Streameadbc246810SE +/- 0.0280, N = 38.29738.19898.09458.08048.0190

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: 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: 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: 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: 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, 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: 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: 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, Baseline - Scenario: Synchronous Single-Streamecbda60120180240300SE +/- 0.64, N = 3266.34268.15270.23270.35272.80

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: 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, 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: 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: 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: 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 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: 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: 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 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: 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: Asynchronous Multi-Streamdacbe12002400360048006000SE +/- 3.30, N = 35665.475672.805677.045678.525679.78

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: Asynchronous Multi-Streameacbd50100150200250217.72218.11220.49224.16229.45

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: Asynchronous Multi-Streamaebcd132639526557.0857.5257.5757.9958.21

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 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 Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streambdace71421283527.9927.9627.9627.8827.86

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

Blender

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: BMW27 - Compute: CPU-Onlydaecb61218243025.7525.7425.7125.6925.63

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.

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.

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: 1:10

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.

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.

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

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

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

79 Results Shown

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