adl feb

Intel Core i7-1280P testing with a MSI MS-14C6 (E14C6IMS.115 BIOS) and MSI Intel ADL GT2 15GB on Ubuntu 22.10 via the Phoronix Test Suite.

HTML result view exported from: https://openbenchmarking.org/result/2302026-NE-ADLFEB23315&gru&sor.

adl febProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLOpenCLVulkanCompilerFile-SystemScreen ResolutionancIntel Core i7-1280P @ 4.80GHz (14 Cores / 20 Threads)MSI MS-14C6 (E14C6IMS.115 BIOS)Intel Alder Lake PCH16GB1024GB Micron_3400_MTFDKBA1T0TFHMSI Intel ADL GT2 15GB (1450MHz)Realtek ALC274Intel Alder Lake-P PCH CNVi WiFiUbuntu 22.105.19.0-29-generic (x86_64)Xfce 4.16X Server 1.21.1.44.6 Mesa 22.2.1OpenCL 3.01.3.224GCC 12.2.0ext41920x1080OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler Details- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-U8K4Qv/gcc-12-12.2.0/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-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v Processor Details- Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0x421 - Thermald 2.5.1 Java Details- OpenJDK Runtime Environment (build 11.0.17+8-post-Ubuntu-1ubuntu2)Python Details- Python 3.10.7Security Details- 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 + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

adl febdeepsparse: 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-Streammemcached: 1:1memcached: 1:5memcached: 1:10memcached: 1:100deepsparse: 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 Timeanc4.51044.206467.191644.087819.780414.833128.030923.453667.194350.5343.453233.34976.30495.718819.019316.15594.50544.16441767830.1918690701742709.671665301.71534.4547237.725104.102222.6707351.501767.4054248.434142.6237103.928119.7839160.843229.97991102.4971174.8444365.113961.89111545.7642240.12612.93207.95187726311.9060983873.602.211.5833336011.354.12209.93318868111.9445243483.953.032.481.984.56207.48263443811.974.613.322.822.374.79206.58014273112.0034294455.173.5954258613.3491091112.7415.513832371207.55928209211.8402008828.0113.0714.08726257714.04840493216.492305717207.45298434211.878.9311.95058037114.4112.70311034215.926342675207.52356609411.909.0512.1813.44303278413.1016.768759819207.55456999911.859.2112.04100651414.3212.844.55194.240366.906844.311918.603514.718528.418923.187260.934143.660540.998533.13486.11995.689919.522716.2354.41354.17211767278.131781728.271739460.621686349.511508.5481235.821104.530522.5568374.063967.9297244.889443.1131114.780622.8974170.194930.17441137.8994175.7334357.479761.58941523.2204239.67983.03207.10759991911.903.652.251.571.324.155978363210.21254709812.103.743.062.321.934.39208.4912.024.753.392.872.244.99213.3512.705.293.603.502.8115.41208.17358193812.028.3911.7913.7113.1816.51207.75787340412.039.0212.1014.6013.5516.03069788207.46611507611.85400698710.4311.1114.4612.9816.69207.76285118811.749.1912.2614.4813.164.54754.188267.143944.241918.828214.866328.170323.203462.174243.451640.818433.21755.79345.727519.176616.1954.40614.1811767103.071823583.081750912.911662246.521520.5369238.7595104.0222.592367.848567.2541247.381343.0829112.44123.0076171.253130.09911169.8973174.5776361.725761.7411529.3919239.1683.17206.31982615811.993.722.261.601.364.24210.11070886112.043.893.282.401.954.36208.24405606911.874.583.362.812.224.96207.7317580611.895.073.653.492.7115.160105142208.6178367211.808.4811.6313.4112.5916.58209.01007723711.888.8812.53353725615.3314.3915.95207.5611.798.3312.0713.7713.5416.87208.24884779411.849.3412.2114.1513.29OpenBenchmarking.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-Streamnca1.02422.04843.07264.09685.1214.55194.54754.5104

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-Streamnac0.95411.90822.86233.81644.77054.24034.20644.1882

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-Streamacn153045607567.1967.1466.91

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-Streamnca102030405044.3144.2444.09

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-Streamacn51015202519.7818.8318.60

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-Streamcan4812162014.8714.8314.72

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-Streamnca71421283528.4228.1728.03

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-Streamacn61218243023.4523.2023.19

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-Streamacn153045607567.1962.1760.93

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-Streamanc112233445550.5343.6643.45

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-Streamanc102030405043.4541.0040.82

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-Streamacn81624324033.3533.2233.13

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-Streamanc2468106.30496.11995.7934

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-Streamcan1.28872.57743.86615.15486.44355.72755.71885.6899

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-Streamnca51015202519.5219.1819.02

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-Streamnca4812162016.2416.2016.16

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-Streamanc1.01372.02743.04114.05485.06854.50544.41354.4061

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-Streamcna0.94071.88142.82213.76284.70354.18104.17214.1644

Memcached

Set To Get Ratio: 1:1

OpenBenchmarking.orgOps/sec, More Is BetterMemcached 1.6.18Set To Get Ratio: 1:1anc400K800K1200K1600K2000K1767830.191767278.131767103.071. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Memcached

Set To Get Ratio: 1:5

OpenBenchmarking.orgOps/sec, More Is BetterMemcached 1.6.18Set To Get Ratio: 1:5acn400K800K1200K1600K2000K1869070.001823583.081781728.271. (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: 1:10can400K800K1200K1600K2000K1750912.911742709.671739460.621. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

Memcached

Set To Get Ratio: 1:100

OpenBenchmarking.orgOps/sec, More Is BetterMemcached 1.6.18Set To Get Ratio: 1:100nac400K800K1200K1600K2000K1686349.511665301.701662246.521. (CXX) g++ options: -O2 -levent_openssl -levent -lcrypto -lssl -lpthread -lz -lpcre

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-Streamnca300600900120015001508.551520.541534.45

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-Streamnac50100150200250235.82237.73238.76

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-Streamcan20406080100104.02104.10104.53

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-Streamnca51015202522.5622.5922.67

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-Streamacn80160240320400351.50367.85374.06

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-Streamcan153045607567.2567.4167.93

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-Streamnca50100150200250244.89247.38248.43

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-Streamacn102030405042.6243.0843.11

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-Streamacn306090120150103.93112.44114.78

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-Streamanc61218243019.7822.9023.01

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-Streamanc4080120160200160.84170.19171.25

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-Streamacn71421283529.9830.1030.17

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-Streamanc300600900120015001102.501137.901169.90

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-Streamcan4080120160200174.58174.84175.73

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-Streamnca80160240320400357.48361.73365.11

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-Streamnca142842567061.5961.7461.89

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-Streamnca300600900120015001523.221529.391545.76

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-Streamcna50100150200250239.17239.68240.13

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 Timeanc0.71331.42662.13992.85323.56652.933.033.17

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Calculate Pi Benchmarkcna50100150200250206.32207.11207.95

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 Dataframenac369121511.9011.9111.99

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 Timeanc0.8371.6742.5113.3484.1853.603.653.72

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 100 - Repartition Test Timeanc0.50851.0171.52552.0342.54252.212.252.26

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 Timenac0.360.721.081.441.81.5700000001.5833336011.600000000

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 Timenac0.3060.6120.9181.2241.531.321.351.36

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 Timeanc0.9541.9082.8623.8164.774.1200000004.1559783634.240000000

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Calculate Pi Benchmarkacn50100150200250209.93210.11210.21

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 Dataframeacn369121511.9412.0412.10

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 Timenca0.88881.77762.66643.55524.4443.743.893.95

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 500 - Repartition Test Timeanc0.7381.4762.2142.9523.693.033.063.28

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 Timenca0.5581.1161.6742.2322.792.322.402.48

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 Timenca0.44550.8911.33651.7822.22751.931.951.98

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 Timecna1.0262.0523.0784.1045.134.364.394.56

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Calculate Pi Benchmarkacn50100150200250207.48208.24208.49

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 Dataframecan369121511.8711.9712.02

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 Timecan1.06882.13763.20644.27525.3444.584.614.75

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 1000 - Repartition Test Timeacn0.76281.52562.28843.05123.8143.323.363.39

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 Timecan0.64581.29161.93742.58323.2292.812.822.87

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 Timecna0.53331.06661.59992.13322.66652.222.242.37

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 Timeacn1.12282.24563.36844.49125.6144.794.964.99

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Calculate Pi Benchmarkacn50100150200250206.58207.73213.35

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 Dataframecan369121511.8912.0012.70

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 Timecan1.19032.38063.57094.76125.95155.075.175.29

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 1000000 - Partitions: 2000 - Repartition Test Timeanc0.82131.64262.46393.28524.10653.5954258613.6000000003.650000000

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 Timeacn0.78751.5752.36253.153.93753.3491091113.4900000003.500000000

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 Timecan0.63231.26461.89692.52923.16152.712.742.81

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 Timecna4812162015.1615.4115.51

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Calculate Pi Benchmarkanc50100150200250207.56208.17208.62

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 Dataframecan369121511.8011.8412.02

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 Timeanc2468108.018.398.48

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 100 - Repartition Test Timecna369121511.6311.7913.07

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 Timecna4812162013.4113.7114.09

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 Timecna4812162012.5913.1814.05

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 Timeanc4812162016.4916.5116.58

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Calculate Pi Benchmarkanc50100150200250207.45207.76209.01

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 Dataframeacn369121511.8711.8812.03

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 Timecan36912158.888.939.02

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 500 - Repartition Test Timeanc369121511.9512.1012.53

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 Timeanc4812162014.4114.6015.33

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 Timeanc4812162012.7013.5514.39

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 Timeacn4812162015.9315.9516.03

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Calculate Pi Benchmarknac50100150200250207.47207.52207.56

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 Dataframecna369121511.7911.8511.90

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 Timecan36912158.339.0510.43

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 1000 - Repartition Test Timenca369121511.1112.0712.18

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 Timeacn4812162013.4413.7714.46

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 Timenac369121512.9813.1013.54

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 Timenac4812162016.6916.7716.87

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Calculate Pi Benchmarkanc50100150200250207.55207.76208.25

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 Dataframenca369121511.7411.8411.85

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 Timenac36912159.199.219.34

Apache Spark

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

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark 3.3Row Count: 10000000 - Partitions: 2000 - Repartition Test Timeacn369121512.0412.2112.26

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 Timecan4812162014.1514.3214.48

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 Timeanc369121512.8413.1613.29

Phoronix Test Suite v10.8.4