dec

Tests for a future article. Intel Xeon Silver 4216 testing with a TYAN S7100AG2NR (V4.02 BIOS) and ASPEED on Debian 12 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 2312044-NE-DEC16393710
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December 04 2023
  3 Hours, 48 Minutes
b
December 04 2023
  3 Hours, 44 Minutes
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  3 Hours, 46 Minutes
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decOpenBenchmarking.orgPhoronix Test SuiteIntel Xeon Silver 4216 @ 3.20GHz (16 Cores / 32 Threads)TYAN S7100AG2NR (V4.02 BIOS)Intel Sky Lake-E DMI3 Registers46GB240GB Corsair Force MP500ASPEEDRealtek ALC8922 x Intel I350Debian 126.1.0-11-amd64 (x86_64)X ServerGCC 12.2.0ext41024x768ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDisplay ServerCompilerFile-SystemScreen ResolutionDec BenchmarksSystem Logs- Transparent Huge Pages: always- --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-bTRWOB/gcc-12-12.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-12-bTRWOB/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 - Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0x500002c - OpenJDK Runtime Environment (build 17.0.9+9-Debian-1deb12u1)- Python 3.11.2- gather_data_sampling: Vulnerable: No microcode + itlb_multihit: KVM: Mitigation of VMX disabled + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Vulnerable: Clear buffers attempted no microcode; SMT vulnerable + retbleed: Mitigation of Enhanced IBRS + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Mitigation of TSX disabled

a vs. b ComparisonPhoronix Test SuiteBaseline+7.1%+7.1%+14.2%+14.2%+21.3%+21.3%+28.4%+28.4%21.8%8.2%4.4%4.1%2.8%2.7%2.1%4.5%3.1%5.2%9.4%3.9%3.7%7.3%4.2%5.2%2.5%9.3%28.4%2.3%2.2%4%3.5%2.7%7.9%3.5%S.M.MQ.7.C.E.78.3%CPU - 32 - ResNet-5010 - G.M.O.A.QCompositeWrites2.9%CPU - 32 - Efficientnet_v2_l1 - G.M.O.A.Q2.7%Q.1.C.E.5CryptoNight-Heavy - 1M1 - Q025.8%1 - Q031 - Q043%1 - Q0520.9%1 - Q066.7%1 - Q071 - Q082.8%1 - Q091 - Q101 - Q118.2%1 - Q125.5%1 - Q1311%1 - Q155.9%1 - Q162.2%1 - Q177.6%1 - Q186.8%1 - Q216.6%1 - Q2210 - Q026.4%10 - Q0310 - Q042%10 - Q0610 - Q0710 - Q0810 - Q0910 - Q1010 - Q1110 - Q1210 - Q1410 - Q1510 - Q1710 - Q1810 - Q1910 - Q20Java SciMarkWebP2 Image EncodePyTorchApache Spark TPC-HJava SciMarkScyllaDBPyTorchApache Spark TPC-HWebP2 Image EncodeXmrigApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-HApache Spark TPC-Hab

decxmrig: KawPow - 1Mxmrig: Monero - 1Mxmrig: Wownero - 1Mxmrig: GhostRider - 1Mxmrig: CryptoNight-Heavy - 1Mxmrig: CryptoNight-Femto UPX2 - 1Mjava-scimark2: Compositejava-scimark2: Monte Carlojava-scimark2: Fast Fourier Transformjava-scimark2: Sparse Matrix Multiplyjava-scimark2: Dense LU Matrix Factorizationjava-scimark2: Jacobi Successive Over-Relaxationwebp2: Defaultwebp2: Quality 75, Compression Effort 7webp2: Quality 95, Compression Effort 7webp2: Quality 100, Compression Effort 5webp2: Quality 100, Lossless Compressionspark-tpch: 1 - Geometric Mean Of All Queriesspark-tpch: 1 - Q01spark-tpch: 1 - Q02spark-tpch: 1 - Q03spark-tpch: 1 - Q04spark-tpch: 1 - Q05spark-tpch: 1 - Q06spark-tpch: 1 - Q07spark-tpch: 1 - Q08spark-tpch: 1 - Q09spark-tpch: 1 - Q10spark-tpch: 1 - Q11spark-tpch: 1 - Q12spark-tpch: 1 - Q13spark-tpch: 1 - Q14spark-tpch: 1 - Q15spark-tpch: 1 - Q16spark-tpch: 1 - Q17spark-tpch: 1 - Q18spark-tpch: 1 - Q19spark-tpch: 1 - Q20spark-tpch: 1 - Q21spark-tpch: 1 - Q22spark-tpch: 10 - Geometric Mean Of All Queriesspark-tpch: 10 - Q01spark-tpch: 10 - Q02spark-tpch: 10 - Q03spark-tpch: 10 - Q04spark-tpch: 10 - Q05spark-tpch: 10 - Q06spark-tpch: 10 - Q07spark-tpch: 10 - Q08spark-tpch: 10 - Q09spark-tpch: 10 - Q10spark-tpch: 10 - Q11spark-tpch: 10 - Q12spark-tpch: 10 - Q13spark-tpch: 10 - Q14spark-tpch: 10 - Q15spark-tpch: 10 - Q16spark-tpch: 10 - Q17spark-tpch: 10 - Q18spark-tpch: 10 - Q19spark-tpch: 10 - Q20spark-tpch: 10 - Q21spark-tpch: 10 - Q22pytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 32 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lscylladb: Writesscylladb: Mixed 1:1scylladb: Mixed 1:3ab5867.45893.19157.4963.75837.85928.61707.42781.47454.761626.694515.951158.245.910.130.063.350.012.183214824.092722422.563711883.227153062.517598872.909869910.78977183.122417932.439898734.226441382.855340481.564065811.852846261.717790371.29490281.600293871.759385592.448478223.112349751.221323252.18017847.133046151.577602749.281896569.975249294.4833350211.710604679.7635631613.332208636.0984549510.6867628111.9213647815.7125701910.970542913.864919198.486800195.404675487.460264687.126156815.1335697218.4600257919.150533687.295358669.3641672135.336891173.8539769629.6011.1321.6019.778.108.266.934.784.681069901026461048775855.95825.59271.5977.95962.45850.61777.58785.76450.811980.664515.951154.756.000.120.063.440.012.242331434.138847352.713507183.087904932.593739993.518117670.842409913.029561042.50900344.01695492.610700851.691650631.954094531.907204511.311342721.695010541.797543412.634629253.325278041.241607432.189243327.604266641.517878778.888747259.87204174.7720260611.288640029.9577627213.225991255.6845226310.2541732811.3349437715.3219118110.033387183.00896128.292750365.47891767.302735336.854080685.1590461717.8347663918.638505946.761696829.0461807335.113098143.8899650629.3711.1421.4721.398.168.136.924.714.81103971102265104038OpenBenchmarking.org

Xmrig

Xmrig is an open-source cross-platform CPU/GPU miner for RandomX, KawPow, CryptoNight and AstroBWT. This test profile is setup to measure the Xmrig CPU mining performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: KawPow - Hash Count: 1Mab130026003900520065005867.45855.91. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: Monero - Hash Count: 1Mab130026003900520065005893.15825.51. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: Wownero - Hash Count: 1Mab2K4K6K8K10K9157.49271.51. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: GhostRider - Hash Count: 1Mab2004006008001000963.7977.91. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: CryptoNight-Heavy - Hash Count: 1Mab130026003900520065005837.85962.41. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

OpenBenchmarking.orgH/s, More Is BetterXmrig 6.21Variant: CryptoNight-Femto UPX2 - Hash Count: 1Mab130026003900520065005928.65850.61. (CXX) g++ options: -fexceptions -fno-rtti -maes -O3 -Ofast -static-libgcc -static-libstdc++ -rdynamic -lssl -lcrypto -luv -lpthread -lrt -ldl -lhwloc

Java SciMark

This test runs the Java version of SciMark 2, which is a benchmark for scientific and numerical computing developed by programmers at the National Institute of Standards and Technology. This benchmark is made up of Fast Foruier Transform, Jacobi Successive Over-relaxation, Monte Carlo, Sparse Matrix Multiply, and dense LU matrix factorization benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Compositeab4008001200160020001707.421777.58

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Monte Carloab2004006008001000781.47785.76

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Fast Fourier Transformab100200300400500454.76450.81

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Sparse Matrix Multiplyab4008001200160020001626.691980.66

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Dense LU Matrix Factorizationab100020003000400050004515.954515.95

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Jacobi Successive Over-Relaxationab20040060080010001158.241154.75

WebP2 Image Encode

This is a test of Google's libwebp2 library with the WebP2 image encode utility and using a sample 6000x4000 pixel JPEG image as the input, similar to the WebP/libwebp test profile. WebP2 is currently experimental and under heavy development as ultimately the successor to WebP. WebP2 supports 10-bit HDR, more efficienct lossy compression, improved lossless compression, animation support, and full multi-threading support compared to WebP. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Defaultab2468105.916.001. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 75, Compression Effort 7ab0.02930.05860.08790.11720.14650.130.121. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 95, Compression Effort 7ab0.01350.0270.04050.0540.06750.060.061. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Compression Effort 5ab0.7741.5482.3223.0963.873.353.441. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Lossless Compressionab0.00230.00460.00690.00920.01150.010.011. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

Apache Spark TPC-H

This is a benchmark of Apache Spark using TPC-H data-set. Apache Spark is an open-source unified analytics engine for large-scale data processing and dealing with big data. This test profile benchmarks the Apache Spark in a single-system configuration using spark-submit. The test makes use of https://github.com/ssavvides/tpch-spark/ for facilitating the TPC-H benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 1 - Geometric Mean Of All Queriesab0.50451.0091.51352.0182.52252.183214822.24233143MIN: 1.22 / MAX: 7.13MIN: 1.24 / MAX: 7.6

OpenBenchmarking.orgSeconds, Fewer Is BetterApache Spark TPC-H 3.5Scale Factor: 10 - Geometric Mean Of All Queriesab36912159.281896568.88874725MIN: 3.85 / MAX: 35.34MIN: 3.01 / MAX: 35.11

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ab71421283529.6029.37MIN: 25.83 / MAX: 29.8MIN: 22.42 / MAX: 29.58

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152ab369121511.1311.14MIN: 8.56 / MAX: 11.2MIN: 9.31 / MAX: 11.2

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ab51015202521.6021.47MIN: 17.62 / MAX: 21.74MIN: 14.81 / MAX: 21.69

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50ab51015202519.7721.39MIN: 13.79 / MAX: 21.46MIN: 17.11 / MAX: 21.58

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ab2468108.108.16MIN: 7.24 / MAX: 8.17MIN: 6.81 / MAX: 8.25

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ab2468108.268.13MIN: 7.3 / MAX: 8.35MIN: 7.22 / MAX: 8.33

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lab2468106.936.92MIN: 5.15 / MAX: 7.03MIN: 5.17 / MAX: 7.06

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lab1.07552.1513.22654.3025.37754.784.71MIN: 3.36 / MAX: 4.96MIN: 3.35 / MAX: 4.86

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lab1.08232.16463.24694.32925.41154.684.81MIN: 3.34 / MAX: 4.83MIN: 3.38 / MAX: 4.93

ScyllaDB

This is a benchmark of ScyllaDB and is making use of Apache Cassandra's cassandra-stress for conducting the benchmark. ScyllaDB is an open-source distributed NoSQL data store that is compatible with Apache Cassandra while focusing on higher throughput and lower latency. ScyllaDB uses a sharded design on each node. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgOp/s, More Is BetterScyllaDB 5.2.9Test: Writesab20K40K60K80K100K106990103971

OpenBenchmarking.orgOp/s, More Is BetterScyllaDB 5.2.9Test: Mixed 1:1ab20K40K60K80K100K102646102265

OpenBenchmarking.orgOp/s, More Is BetterScyllaDB 5.2.9Test: Mixed 1:3ab20K40K60K80K100K104877104038