dwq

AMD Ryzen 7 4700U testing with a LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS) and AMD Renoir 512MB on Ubuntu 22.04 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2302021-NE-DWQ81086357&gru&sro.

dwqProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLVulkanCompilerFile-SystemScreen ResolutionwbcAMD Ryzen 7 4700U @ 2.00GHz (8 Cores)LENOVO LNVNB161216 (DTCN18WWV1.04 BIOS)AMD Renoir/Cezanne16GB512GB SAMSUNG MZALQ512HALU-000L2AMD Renoir 512MB (1600/400MHz)AMD Renoir Radeon HD AudioIntel Wi-Fi 6 AX200Ubuntu 22.045.18.8-051808-generic (x86_64)GNOME Shell 42.2X Server + Wayland4.6 Mesa 22.0.5 (LLVM 13.0.1 DRM 3.46)1.3.204GCC 11.3.0ext41920x1080OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler 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,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-xKiWfi/gcc-11-11.3.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-xKiWfi/gcc-11-11.3.0/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: acpi-cpufreq schedutil (Boost: Enabled) - Platform Profile: balanced - CPU Microcode: 0x8600102 - ACPI Profile: balanced Java Details- OpenJDK Runtime Environment (build 11.0.16+8-post-Ubuntu-0ubuntu122.04) Python Details- Python 3.10.6Security Details- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: 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 Retpolines IBPB: conditional IBRS_FW STIBP: disabled RSB filling + srbds: Not affected + tsx_async_abort: Not affected

dwqdeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-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 - Synchronous Single-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: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-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 - Synchronous Single-Streamopenems: pyEMS Coupleropenems: openEMS MSL_NotchFilterrocksdb: Rand Fillrocksdb: Rand Readrocksdb: Update Randrocksdb: Seq Fillrocksdb: Rand Fill Syncrocksdb: Read While Writingrocksdb: Read Rand Write Randmemcached: 1:5memcached: 1:10memcached: 1:100clickhouse: 100M Rows Hits Dataset, First Run / Cold Cacheclickhouse: 100M Rows Hits Dataset, Second Runclickhouse: 100M Rows Hits Dataset, Third Runkeydb: GET - 50keydb: SET - 50keydb: GET - 100keydb: LPOP - 50keydb: SADD - 50keydb: SET - 100keydb: HMSET - 50keydb: LPOP - 100keydb: LPUSH - 50keydb: SADD - 100keydb: HMSET - 100keydb: LPUSH - 100pgbench: 1 - 1 - Read Onlypgbench: 1 - 1 - Read Writepgbench: 1 - 50 - Read Onlypgbench: 1 - 100 - Read Onlypgbench: 1 - 250 - Read Onlypgbench: 1 - 50 - Read Writepgbench: 1 - 500 - Read Onlypgbench: 1 - 800 - Read Onlypgbench: 100 - 1 - Read Onlypgbench: 1 - 100 - Read Writepgbench: 1 - 1000 - Read Onlypgbench: 1 - 250 - Read Writepgbench: 1 - 500 - Read Writepgbench: 1 - 800 - Read Writepgbench: 100 - 1 - Read Writepgbench: 100 - 50 - Read Onlypgbench: 1 - 1000 - Read Writepgbench: 100 - 100 - Read Onlypgbench: 100 - 250 - Read Onlypgbench: 100 - 50 - Read Writepgbench: 100 - 500 - Read Onlypgbench: 100 - 800 - Read Onlypgbench: 100 - 100 - Read Writepgbench: 100 - 1000 - Read Onlypgbench: 100 - 250 - Read Writepgbench: 100 - 500 - Read Writepgbench: 100 - 800 - Read Writepgbench: 100 - 1000 - Read Writepgbench: 1 - 1 - Read Only - Average Latencypgbench: 1 - 1 - Read Write - Average Latencypgbench: 1 - 50 - Read Only - Average Latencypgbench: 1 - 100 - Read Only - Average Latencypgbench: 1 - 250 - Read Only - Average Latencypgbench: 1 - 50 - Read Write - Average Latencypgbench: 1 - 500 - Read Only - Average Latencypgbench: 1 - 800 - Read Only - Average Latencypgbench: 100 - 1 - Read Only - Average Latencypgbench: 1 - 100 - Read Write - Average Latencypgbench: 1 - 1000 - Read Only - Average Latencypgbench: 1 - 250 - Read Write - Average Latencypgbench: 1 - 500 - Read Write - Average Latencypgbench: 1 - 800 - Read Write - Average Latencypgbench: 100 - 1 - Read Write - Average Latencypgbench: 100 - 50 - Read Only - Average Latencypgbench: 1 - 1000 - Read Write - Average Latencypgbench: 100 - 100 - Read Only - Average Latencypgbench: 100 - 250 - Read Only - Average Latencypgbench: 100 - 50 - Read Write - Average Latencypgbench: 100 - 500 - Read Only - Average Latencypgbench: 100 - 800 - Read Only - Average Latencypgbench: 100 - 100 - Read Write - Average Latencypgbench: 100 - 1000 - Read Only - Average Latencypgbench: 100 - 250 - Read Write - Average Latencypgbench: 100 - 500 - Read Write - Average Latencypgbench: 100 - 800 - Read Write - Average Latencypgbench: 100 - 1000 - Read Write - Average Latencydeepsparse: NLP Document Classification, oBERT base uncased on IMDB - Asynchronous Multi-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 - Synchronous Single-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: CV Detection, YOLOv5s COCO - Asynchronous Multi-Streamdeepsparse: CV Detection, YOLOv5s COCO - Synchronous Single-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Asynchronous Multi-Streamdeepsparse: CV Classification, ResNet-50 ImageNet - Synchronous Single-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Asynchronous Multi-Streamdeepsparse: NLP Text Classification, DistilBERT mnli - Synchronous Single-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Asynchronous Multi-Streamdeepsparse: CV Segmentation, 90% Pruned YOLACT Pruned - Synchronous Single-Streamdeepsparse: NLP Text Classification, BERT base uncased SST2 - Asynchronous Multi-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 - Synchronous Single-Streamspark: 1000000 - 100 - SHA-512 Benchmark Timespark: 1000000 - 100 - Calculate Pi Benchmarkspark: 1000000 - 100 - Calculate Pi Benchmark Using Dataframespark: 1000000 - 100 - Group By Test Timespark: 1000000 - 100 - Repartition Test Timespark: 1000000 - 100 - Inner Join Test Timespark: 1000000 - 100 - Broadcast Inner Join Test Timespark: 1000000 - 500 - SHA-512 Benchmark Timespark: 1000000 - 500 - Calculate Pi Benchmarkspark: 1000000 - 500 - Calculate Pi Benchmark Using Dataframespark: 1000000 - 500 - Group By Test Timespark: 1000000 - 500 - Repartition Test Timespark: 1000000 - 500 - Inner Join Test Timespark: 1000000 - 500 - Broadcast Inner Join Test Timespark: 1000000 - 1000 - SHA-512 Benchmark Timespark: 1000000 - 1000 - Calculate Pi Benchmarkspark: 1000000 - 1000 - Calculate Pi Benchmark Using Dataframespark: 1000000 - 1000 - Group By Test Timespark: 1000000 - 1000 - Repartition Test Timespark: 1000000 - 1000 - Inner Join Test Timespark: 1000000 - 1000 - Broadcast Inner Join Test Timespark: 1000000 - 2000 - SHA-512 Benchmark Timespark: 1000000 - 2000 - Calculate Pi Benchmarkspark: 1000000 - 2000 - Calculate Pi Benchmark Using Dataframespark: 1000000 - 2000 - Group By Test Timespark: 1000000 - 2000 - Repartition Test Timespark: 1000000 - 2000 - Inner Join Test Timespark: 1000000 - 2000 - Broadcast Inner Join Test Timespark: 10000000 - 100 - SHA-512 Benchmark Timespark: 10000000 - 100 - Calculate Pi Benchmarkspark: 10000000 - 100 - Calculate Pi Benchmark Using Dataframespark: 10000000 - 100 - Group By Test Timespark: 10000000 - 100 - Repartition Test Timespark: 10000000 - 100 - Inner Join Test Timespark: 10000000 - 100 - Broadcast Inner Join Test Timespark: 10000000 - 500 - SHA-512 Benchmark Timespark: 10000000 - 500 - Calculate Pi Benchmarkspark: 10000000 - 500 - Calculate Pi Benchmark Using Dataframespark: 10000000 - 500 - Group By Test Timespark: 10000000 - 500 - Repartition Test Timespark: 10000000 - 500 - Inner Join Test Timespark: 10000000 - 500 - Broadcast Inner Join Test Timespark: 10000000 - 1000 - SHA-512 Benchmark Timespark: 10000000 - 1000 - Calculate Pi Benchmarkspark: 10000000 - 1000 - Calculate Pi Benchmark Using Dataframespark: 10000000 - 1000 - Group By Test Timespark: 10000000 - 1000 - Repartition Test Timespark: 10000000 - 1000 - Inner Join Test Timespark: 10000000 - 1000 - Broadcast Inner Join Test Timespark: 10000000 - 2000 - SHA-512 Benchmark Timespark: 10000000 - 2000 - Calculate Pi Benchmarkspark: 10000000 - 2000 - Calculate Pi Benchmark Using Dataframespark: 10000000 - 2000 - Group By Test Timespark: 10000000 - 2000 - Repartition Test Timespark: 10000000 - 2000 - Inner Join Test Timespark: 10000000 - 2000 - Broadcast Inner Join Test Timewbc4.62294.72248.790436.571812.885812.834825.976421.887751.491646.410136.482432.28545.21655.319419.581217.2174.50154.575713.7541.6956984827294439306010738360757749177791426881038.49834672.86792731.8959.5869.5869.29369786.94342479.81307768.06364758.5360976.94292498.59243997.66310788.72322162.88303482.78197850.55289256.4417392316256079223266157226350153975124581164703461234733032642142832415622121957221392803343135920108957429410841645114217370638960.0573.1680.1950.4481.59142.6773.2476.4220.061288.6748.099825.9221890.7983731.8973.5390.2074714.5690.5111.79514.9593.6797.34223.2889.22455.422118.567215.87256.703857.1802211.763481.949227.3313309.738377.8999153.621545.671177.54521.5352109.537830.9639761.6333187.9712204.139658.0721880.8998218.53375.78301.77882232421.783533985.9168239454.563.422.856.09303.09615661621.7812264236.525.033.983.457.16303.1712290521.7702904966.805.534.663.987.74302.41835920621.7043115127.755.926.2303239695.0031.035995429302.65142856821.9414.28316038521.45661490624.2924.52118224927.86302.53790755321.7412.69793362420.7823.8721.54351978928.690433972301.8983047822.0013.3321.28016434423.93341763822.4728.976133511302.6798892121.7714.47343501321.90680120625.3923.1806459014.59194.717848.721236.83612.849713.051826.725721.957252.148446.034435.887131.74024.85835.24419.475517.28084.49054.417213.7541.8757172727131130304417731826766770192796507883520.2831515.24790452.4558.5472.5270.02360287.66343064.97298655.44328344.66355499.94301326.44241013.8290178.06322381303680195504.95275570.1619564337261198211074233976321135518130604175733401266523292822262972429362242052771494283110142097123277293310582638053744352235540.0512.970.1910.4741.068155.6233.696.1250.057293.8127.896758.7451774.0213547.2293.3680.2064466.6030.4871.67316.0783.5196.48934.0939.44965.697133.559227.176281.36864.2615211.952682.072627.1342310.588176.6036149.299645.526276.597521.7099111.257131.4949817.6718190.6732205.28157.8575879.9941226.37845.88302.6721.705.745.133.473.016.03302.8221.776.194.974.163.486.73302.46665870521.7864834276.825.464.754.047.59303.37681318821.617.576.056.335.0830.87302.47954138721.9113.9121.6024.2924.12405236228.47302.87564540221.7513.0921.9623.71398461121.96235256828.54302.3121.7213.7921.0724.3022.8929.63303.09437539921.8315.03279371521.3726.2623.6936681644.64674.694548.648337.185512.958912.697626.115421.607251.656646.247236.130332.64675.48345.30219.204616.72944.46824.474913.6941.6956091427452849303583728687767754802797910881419.05834811.61785762.3461.9068.5668.41357666.59343137.91309797.03329246.28360394.12284728.31242171.8286449.25322966.12301431.81196921.7227745119252330255387203493158024335142167122771166753311266333002752263022344352092012771399733015129129116684353812504236323195345532550.0523.0280.1960.4911.582149.0523.5176.5160.06302.1277.897833.6941820.513535.9963.3120.2134781.450.4971.78616.5843.8726.85628.2667.99768.838156.489231.516307.218856.2213213.005182.141126.8802307.602778.7417152.846846.264377.31321.6111110.658730.6209727.1519188.5856208.192159.7651884.0783223.45795.75298.3227610121.645.844.633.422.796.29297.89394211621.7252958196.404.914.093.336.93297.72109139521.756.925.474.794.087.65298.14835618721.837.976.006.064.7030.88297.5421.6214.2421.3923.6424.21974400328.701585388298.12487283121.8113.0020.6325.6321.8028.774771033303.27504277921.7113.6420.6723.7622.2229.83299.25125431321.8514.7921.4825.7722.98OpenBenchmarking.org

Neural Magic DeepSparse

Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streambcw1.04552.0913.13654.1825.22754.59194.64674.6229

Neural Magic DeepSparse

Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streambcw1.06252.1253.18754.255.31254.71784.69454.7220

Neural Magic DeepSparse

Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Streambcw112233445548.7248.6548.79

Neural Magic DeepSparse

Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Streambcw91827364536.8437.1936.57

Neural Magic DeepSparse

Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Streambcw369121512.8512.9612.89

Neural Magic DeepSparse

Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Streambcw369121513.0512.7012.83

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streambcw61218243026.7326.1225.98

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streambcw51015202521.9621.6121.89

Neural Magic DeepSparse

Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streambcw122436486052.1551.6651.49

Neural Magic DeepSparse

Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streambcw112233445546.0346.2546.41

Neural Magic DeepSparse

Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streambcw81624324035.8936.1336.48

Neural Magic DeepSparse

Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streambcw81624324031.7432.6532.29

Neural Magic DeepSparse

Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streambcw1.23382.46763.70144.93526.1694.85835.48345.2165

Neural Magic DeepSparse

Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streambcw1.19692.39383.59074.78765.98455.24405.30205.3194

Neural Magic DeepSparse

Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Streambcw51015202519.4819.2019.58

Neural Magic DeepSparse

Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Streambcw4812162017.2816.7317.22

Neural Magic DeepSparse

Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streambcw1.01282.02563.03844.05125.0644.49054.46824.5015

Neural Magic DeepSparse

Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgitems/sec, More Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streambcw1.02952.0593.08854.1185.14754.41724.47494.5757

OpenEMS

Test: pyEMS Coupler

OpenBenchmarking.orgMCells/s, More Is BetterOpenEMS 0.0.35-86Test: pyEMS Couplerbcw4812162013.7513.6913.751. (CXX) g++ options: -O3 -rdynamic -ltinyxml -lcrypto -lcurl -lpthread -lsz -lz -ldl -lm -lexpat

OpenEMS

Test: openEMS MSL_NotchFilter

OpenBenchmarking.orgMCells/s, More Is BetterOpenEMS 0.0.35-86Test: openEMS MSL_NotchFilterbcw102030405041.8741.6941.691. (CXX) g++ options: -O3 -rdynamic -ltinyxml -lcrypto -lcurl -lpthread -lsz -lz -ldl -lm -lexpat

RocksDB

Test: Random Fill

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 7.9.2Test: Random Fillbcw120K240K360K480K600K5717275609145698481. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

RocksDB

Test: Random Read

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 7.9.2Test: Random Readbcw6M12M18M24M30M2713113027452849272944391. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

RocksDB

Test: Update Random

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 7.9.2Test: Update Randombcw70K140K210K280K350K3044173035833060101. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

RocksDB

Test: Sequential Fill

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 7.9.2Test: Sequential Fillbcw160K320K480K640K800K7318267286877383601. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

RocksDB

Test: Random Fill Sync

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 7.9.2Test: Random Fill Syncbcw1703405106808507667677571. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

RocksDB

Test: Read While Writing

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 7.9.2Test: Read While Writingbcw160K320K480K640K800K7701927548027491771. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

RocksDB

Test: Read Random Write Random

OpenBenchmarking.orgOp/s, More Is BetterRocksDB 7.9.2Test: Read Random Write Randombcw200K400K600K800K1000K7965077979107914261. (CXX) g++ options: -O3 -march=native -pthread -fno-builtin-memcmp -fno-rtti -lpthread

Memcached

Set To Get Ratio: 1:5

OpenBenchmarking.orgOps/sec, More Is BetterMemcached 1.6.18Set To Get Ratio: 1:5bcw200K400K600K800K1000K883520.20881419.05881038.491. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Memcached

Set To Get Ratio: 1:10

OpenBenchmarking.orgOps/sec, More Is BetterMemcached 1.6.18Set To Get Ratio: 1:10bcw200K400K600K800K1000K831515.24834811.61834672.861. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Memcached

Set To Get Ratio: 1:100

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ClickHouse

100M Rows Hits Dataset, First Run / Cold Cache

OpenBenchmarking.orgQueries Per Minute, Geo Mean, More Is BetterClickHouse 22.12.3.5100M Rows Hits Dataset, First Run / Cold Cachebcw142842567058.5461.9059.58MIN: 3.81 / MAX: 2000MIN: 3.88 / MAX: 3000MIN: 3.78 / MAX: 2857.14

ClickHouse

100M Rows Hits Dataset, Second Run

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ClickHouse

100M Rows Hits Dataset, Third Run

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KeyDB

Test: GET - Parallel Connections: 50

OpenBenchmarking.orgRequests Per Second, More Is BetterKeyDB 6.3.2Test: GET - Parallel Connections: 50bcw80K160K240K320K400K360287.66357666.59369786.941. (CXX) g++ options: -ggdb -rdynamic -lm -lz -lcrypto -lbz2 -lzstd -llz4 -lsnappy -latomic -ldl -pthread -lrt -luuid -lcurl -lssl -std=c++14 -pedantic -fno-rtti -O2 -flto -MMD

KeyDB

Test: SET - Parallel Connections: 50

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KeyDB

Test: GET - Parallel Connections: 100

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KeyDB

Test: LPOP - Parallel Connections: 50

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KeyDB

Test: SADD - Parallel Connections: 50

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KeyDB

Test: SET - Parallel Connections: 100

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KeyDB

Test: HMSET - Parallel Connections: 50

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KeyDB

Test: LPOP - Parallel Connections: 100

OpenBenchmarking.orgRequests Per Second, More Is BetterKeyDB 6.3.2Test: LPOP - Parallel Connections: 100bcw70K140K210K280K350K290178.06286449.25310788.721. (CXX) g++ options: -ggdb -rdynamic -lm -lz -lcrypto -lbz2 -lzstd -llz4 -lsnappy -latomic -ldl -pthread -lrt -luuid -lcurl -lssl -std=c++14 -pedantic -fno-rtti -O2 -flto -MMD

KeyDB

Test: LPUSH - Parallel Connections: 50

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KeyDB

Test: SADD - Parallel Connections: 100

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KeyDB

Test: HMSET - Parallel Connections: 100

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KeyDB

Test: LPUSH - Parallel Connections: 100

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PostgreSQL

Scaling Factor: 1 - Clients: 1 - Mode: Read Only

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PostgreSQL

Scaling Factor: 1 - Clients: 1 - Mode: Read Write

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PostgreSQL

Scaling Factor: 1 - Clients: 50 - Mode: Read Only

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PostgreSQL

Scaling Factor: 1 - Clients: 100 - Mode: Read Only

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PostgreSQL

Scaling Factor: 1 - Clients: 250 - Mode: Read Only

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PostgreSQL

Scaling Factor: 1 - Clients: 50 - Mode: Read Write

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PostgreSQL

Scaling Factor: 1 - Clients: 500 - Mode: Read Only

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PostgreSQL

Scaling Factor: 1 - Clients: 800 - Mode: Read Only

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PostgreSQL

Scaling Factor: 100 - Clients: 1 - Mode: Read Only

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PostgreSQL

Scaling Factor: 1 - Clients: 100 - Mode: Read Write

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PostgreSQL

Scaling Factor: 1 - Clients: 1000 - Mode: Read Only

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PostgreSQL

Scaling Factor: 1 - Clients: 250 - Mode: Read Write

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PostgreSQL

Scaling Factor: 1 - Clients: 500 - Mode: Read Write

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PostgreSQL

Scaling Factor: 1 - Clients: 800 - Mode: Read Write

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PostgreSQL

Scaling Factor: 100 - Clients: 1 - Mode: Read Write

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PostgreSQL

Scaling Factor: 100 - Clients: 50 - Mode: Read Only

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PostgreSQL

Scaling Factor: 1 - Clients: 1000 - Mode: Read Write

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PostgreSQL

Scaling Factor: 100 - Clients: 100 - Mode: Read Only

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PostgreSQL

Scaling Factor: 100 - Clients: 250 - Mode: Read Only

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PostgreSQL

Scaling Factor: 100 - Clients: 50 - Mode: Read Write

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PostgreSQL

Scaling Factor: 100 - Clients: 500 - Mode: Read Only

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PostgreSQL

Scaling Factor: 100 - Clients: 800 - Mode: Read Only

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PostgreSQL

Scaling Factor: 100 - Clients: 100 - Mode: Read Write

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PostgreSQL

Scaling Factor: 100 - Clients: 1000 - Mode: Read Only

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PostgreSQL

Scaling Factor: 100 - Clients: 250 - Mode: Read Write

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PostgreSQL

Scaling Factor: 100 - Clients: 500 - Mode: Read Write

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PostgreSQL

Scaling Factor: 100 - Clients: 800 - Mode: Read Write

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PostgreSQL

Scaling Factor: 100 - Clients: 1000 - Mode: Read Write

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PostgreSQL

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PostgreSQL

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PostgreSQL

Scaling Factor: 1 - Clients: 50 - Mode: Read Only - Average Latency

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PostgreSQL

Scaling Factor: 1 - Clients: 100 - Mode: Read Only - Average Latency

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PostgreSQL

Scaling Factor: 1 - Clients: 250 - Mode: Read Only - Average Latency

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PostgreSQL

Scaling Factor: 1 - Clients: 50 - Mode: Read Write - Average Latency

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PostgreSQL

Scaling Factor: 1 - Clients: 500 - Mode: Read Only - Average Latency

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PostgreSQL

Scaling Factor: 1 - Clients: 800 - Mode: Read Only - Average Latency

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PostgreSQL

Scaling Factor: 100 - Clients: 1 - Mode: Read Only - Average Latency

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PostgreSQL

Scaling Factor: 1 - Clients: 100 - Mode: Read Write - Average Latency

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PostgreSQL

Scaling Factor: 1 - Clients: 1000 - Mode: Read Only - Average Latency

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PostgreSQL

Scaling Factor: 1 - Clients: 250 - Mode: Read Write - Average Latency

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PostgreSQL

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PostgreSQL

Scaling Factor: 1 - Clients: 800 - Mode: Read Write - Average Latency

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PostgreSQL

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PostgreSQL

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PostgreSQL

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PostgreSQL

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PostgreSQL

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PostgreSQL

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PostgreSQL

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PostgreSQL

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PostgreSQL

Scaling Factor: 100 - Clients: 100 - Mode: Read Write - Average Latency

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PostgreSQL

Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency

OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 15Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latencybcw36912159.4497.9979.2241. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

PostgreSQL

Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latency

OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 15Scaling Factor: 100 - Clients: 250 - Mode: Read Write - Average Latencybcw153045607565.7068.8455.421. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

PostgreSQL

Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latency

OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 15Scaling Factor: 100 - Clients: 500 - Mode: Read Write - Average Latencybcw306090120150133.56156.49118.571. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

PostgreSQL

Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency

OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 15Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latencybcw50100150200250227.18231.52215.871. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

PostgreSQL

Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency

OpenBenchmarking.orgms, Fewer Is BetterPostgreSQL 15Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latencybcw70140210280350281.36307.22256.701. (CC) gcc options: -fno-strict-aliasing -fwrapv -O2 -lpgcommon -lpgport -lpq -lm

Neural Magic DeepSparse

Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Streambcw2004006008001000864.26856.22857.18

Neural Magic DeepSparse

Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Streambcw50100150200250211.95213.01211.76

Neural Magic DeepSparse

Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Streambcw2040608010082.0782.1481.95

Neural Magic DeepSparse

Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Synchronous Single-Streambcw61218243027.1326.8827.33

Neural Magic DeepSparse

Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Streambcw70140210280350310.59307.60309.74

Neural Magic DeepSparse

Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Streambcw2040608010076.6078.7477.90

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Streambcw306090120150149.30152.85153.62

Neural Magic DeepSparse

Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: CV Detection, YOLOv5s COCO - Scenario: Synchronous Single-Streambcw102030405045.5346.2645.67

Neural Magic DeepSparse

Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Streambcw2040608010076.6077.3177.55

Neural Magic DeepSparse

Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Streambcw51015202521.7121.6121.54

Neural Magic DeepSparse

Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Streambcw20406080100111.26110.66109.54

Neural Magic DeepSparse

Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Streambcw71421283531.4930.6230.96

Neural Magic DeepSparse

Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Streambcw2004006008001000817.67727.15761.63

Neural Magic DeepSparse

Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Streambcw4080120160200190.67188.59187.97

Neural Magic DeepSparse

Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Streambcw50100150200250205.28208.19204.14

Neural Magic DeepSparse

Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Streambcw132639526557.8659.7758.07

Neural Magic DeepSparse

Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Streambcw2004006008001000879.99884.08880.90

Neural Magic DeepSparse

Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream

OpenBenchmarking.orgms/batch, Fewer Is BetterNeural Magic DeepSparse 1.3.2Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Streambcw50100150200250226.38223.46218.53

Apache Spark

Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - SHA-512 Benchmark Timebcw1.3232.6463.9695.2926.6155.885.755.78

Apache Spark

Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmarkbcw70140210280350302.67298.32301.78

Apache Spark

Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframebcw51015202521.7021.6421.78

Apache Spark

Row Count: 1000000 - Partitions: 100 - Group By Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Group By Test Timebcw1.33132.66263.99395.32526.65655.7400000005.8400000005.916823945

Apache Spark

Row Count: 1000000 - Partitions: 100 - Repartition Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Repartition Test Timebcw1.15432.30863.46294.61725.77155.134.634.56

Apache Spark

Row Count: 1000000 - Partitions: 100 - Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Inner Join Test Timebcw0.78081.56162.34243.12323.9043.473.423.42

Apache Spark

Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Broadcast Inner Join Test Timebcw0.67731.35462.03192.70923.38653.012.792.85

Apache Spark

Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - SHA-512 Benchmark Timebcw2468106.036.296.09

Apache Spark

Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmarkbcw70140210280350302.82297.89303.10

Apache Spark

Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframebcw51015202521.7721.7321.78

Apache Spark

Row Count: 1000000 - Partitions: 500 - Group By Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Group By Test Timebcw2468106.196.406.52

Apache Spark

Row Count: 1000000 - Partitions: 500 - Repartition Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Repartition Test Timebcw1.13182.26363.39544.52725.6594.974.915.03

Apache Spark

Row Count: 1000000 - Partitions: 500 - Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Inner Join Test Timebcw0.9361.8722.8083.7444.684.164.093.98

Apache Spark

Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Broadcast Inner Join Test Timebcw0.7831.5662.3493.1323.9153.483.333.45

Apache Spark

Row Count: 1000000 - Partitions: 1000 - SHA-512 Benchmark Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - SHA-512 Benchmark Timebcw2468106.736.937.16

Apache Spark

Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmarkbcw70140210280350302.47297.72303.17

Apache Spark

Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframebcw51015202521.7921.7521.77

Apache Spark

Row Count: 1000000 - Partitions: 1000 - Group By Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Group By Test Timebcw2468106.826.926.80

Apache Spark

Row Count: 1000000 - Partitions: 1000 - Repartition Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Repartition Test Timebcw1.24432.48863.73294.97726.22155.465.475.53

Apache Spark

Row Count: 1000000 - Partitions: 1000 - Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Inner Join Test Timebcw1.07782.15563.23344.31125.3894.754.794.66

Apache Spark

Row Count: 1000000 - Partitions: 1000 - Broadcast Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Broadcast Inner Join Test Timebcw0.9181.8362.7543.6724.594.044.083.98

Apache Spark

Row Count: 1000000 - Partitions: 2000 - SHA-512 Benchmark Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - SHA-512 Benchmark Timebcw2468107.597.657.74

Apache Spark

Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmarkbcw70140210280350303.38298.15302.42

Apache Spark

Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframebcw51015202521.6121.8321.70

Apache Spark

Row Count: 1000000 - Partitions: 2000 - Group By Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Group By Test Timebcw2468107.577.977.75

Apache Spark

Row Count: 1000000 - Partitions: 2000 - Repartition Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Repartition Test Timebcw2468106.056.005.92

Apache Spark

Row Count: 1000000 - Partitions: 2000 - Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Inner Join Test Timebcw2468106.3300000006.0600000006.230323969

Apache Spark

Row Count: 1000000 - Partitions: 2000 - Broadcast Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Broadcast Inner Join Test Timebcw1.1432.2863.4294.5725.7155.084.705.00

Apache Spark

Row Count: 10000000 - Partitions: 100 - SHA-512 Benchmark Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - SHA-512 Benchmark Timebcw71421283530.8730.8831.04

Apache Spark

Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmarkbcw70140210280350302.48297.54302.65

Apache Spark

Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframe

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmark Using Dataframebcw51015202521.9121.6221.94

Apache Spark

Row Count: 10000000 - Partitions: 100 - Group By Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Group By Test Timebcw4812162013.9114.2414.28

Apache Spark

Row Count: 10000000 - Partitions: 100 - Repartition Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Repartition Test Timebcw51015202521.6021.3921.46

Apache Spark

Row Count: 10000000 - Partitions: 100 - Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Inner Join Test Timebcw61218243024.2923.6424.29

Apache Spark

Row Count: 10000000 - Partitions: 100 - Broadcast Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Broadcast Inner Join Test Timebcw61218243024.1224.2224.52

Apache Spark

Row Count: 10000000 - Partitions: 500 - SHA-512 Benchmark Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - SHA-512 Benchmark Timebcw71421283528.4728.7027.86

Apache Spark

Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmarkbcw70140210280350302.88298.12302.54

Apache Spark

Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframe

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmark Using Dataframebcw51015202521.7521.8121.74

Apache Spark

Row Count: 10000000 - Partitions: 500 - Group By Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Group By Test Timebcw369121513.0913.0012.70

Apache Spark

Row Count: 10000000 - Partitions: 500 - Repartition Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Repartition Test Timebcw51015202521.9620.6320.78

Apache Spark

Row Count: 10000000 - Partitions: 500 - Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Inner Join Test Timebcw61218243023.7125.6323.87

Apache Spark

Row Count: 10000000 - Partitions: 500 - Broadcast Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Broadcast Inner Join Test Timebcw51015202521.9621.8021.54

Apache Spark

Row Count: 10000000 - Partitions: 1000 - SHA-512 Benchmark Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - SHA-512 Benchmark Timebcw71421283528.5428.7728.69

Apache Spark

Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmarkbcw70140210280350302.31303.28301.90

Apache Spark

Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframe

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmark Using Dataframebcw51015202521.7221.7122.00

Apache Spark

Row Count: 10000000 - Partitions: 1000 - Group By Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Group By Test Timebcw4812162013.7913.6413.33

Apache Spark

Row Count: 10000000 - Partitions: 1000 - Repartition Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Repartition Test Timebcw51015202521.0720.6721.28

Apache Spark

Row Count: 10000000 - Partitions: 1000 - Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Inner Join Test Timebcw61218243024.3023.7623.93

Apache Spark

Row Count: 10000000 - Partitions: 1000 - Broadcast Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Broadcast Inner Join Test Timebcw51015202522.8922.2222.47

Apache Spark

Row Count: 10000000 - Partitions: 2000 - SHA-512 Benchmark Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - SHA-512 Benchmark Timebcw71421283529.6329.8328.98

Apache Spark

Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmarkbcw70140210280350303.09299.25302.68

Apache Spark

Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframe

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmark Using Dataframebcw51015202521.8321.8521.77

Apache Spark

Row Count: 10000000 - Partitions: 2000 - Group By Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Group By Test Timebcw4812162015.0314.7914.47

Apache Spark

Row Count: 10000000 - Partitions: 2000 - Repartition Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Repartition Test Timebcw51015202521.3721.4821.91

Apache Spark

Row Count: 10000000 - Partitions: 2000 - Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Inner Join Test Timebcw61218243026.2625.7725.39

Apache Spark

Row Count: 10000000 - Partitions: 2000 - Broadcast Inner Join Test Time

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Broadcast Inner Join Test Timebcw61218243023.6922.9823.18

Phoronix Test Suite v10.8.4