Core i9 9900KS

Intel Core i9-9900KS testing with a ASUS PRIME Z390-A (1502 BIOS) and ASUS Intel UHD 630 3GB on Ubuntu 20.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2009063-FI-COREI999045
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Date
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  Test
  Duration
Core i9 9900KS
September 06 2020
  2 Hours, 35 Minutes
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Core i9 9900KSOpenBenchmarking.orgPhoronix Test SuiteIntel Core i9-9900KS @ 5.00GHz (8 Cores / 16 Threads)ASUS PRIME Z390-A (1502 BIOS)Intel Cannon Lake PCH32GB240GB Corsair Force MP510ASUS Intel UHD 630 3GB (1200MHz)Realtek ALC1220G237HLIntel I219-VUbuntu 20.045.9.0-050900rc1daily20200819-generic (x86_64) 20200818GNOME Shell 3.36.2X Server 1.20.8modesetting 1.20.84.6 Mesa 20.0.4GCC 9.3.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionCore I9 9900KS BenchmarksSystem Logs- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --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++,gm2 --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none,hsa --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 - CPU Microcode: 0xcc- Python 2.7.18rc1 + Python 3.8.2- itlb_multihit: KVM: Mitigation of VMX unsupported + l1tf: Not affected + mds: Not affected + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced IBRS IBPB: conditional RSB filling + srbds: Mitigation of TSX disabled + tsx_async_abort: Mitigation of TSX disabled

Core i9 9900KSlczero: BLASlczero: Eigenlczero: Randnamd: ATPase Simulation - 327,506 Atomscompress-zstd: 3compress-zstd: 19perf-bench: Epoll Waitperf-bench: Futex Hashperf-bench: Memcpy 1MBperf-bench: Memset 1MBperf-bench: Sched Pipeperf-bench: Futex Lock-Piperf-bench: Syscall Basictensorflow-lite: SqueezeNettensorflow-lite: Inception V4tensorflow-lite: NASNet Mobiletensorflow-lite: Mobilenet Floattensorflow-lite: Mobilenet Quanttensorflow-lite: Inception ResNet V2ai-benchmark: Device Inference Scoreai-benchmark: Device Training Scoreai-benchmark: Device AI ScoreCore i9 9900KS10739942690281.705033605.532.0153783608960234.20774356.2182942769425512155293820116428961531768171365861400692621277129412852579OpenBenchmarking.org

LeelaChessZero

LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.26Backend: BLASCore i9 9900KS2004006008001000SE +/- 6.36, N = 310731. (CXX) g++ options: -flto -pthread

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.26Backend: EigenCore i9 9900KS2004006008001000SE +/- 10.91, N = 39941. (CXX) g++ options: -flto -pthread

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.26Backend: RandomCore i9 9900KS60K120K180K240K300KSE +/- 1133.22, N = 32690281. (CXX) g++ options: -flto -pthread

NAMD

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgdays/ns, Fewer Is BetterNAMD 2.14ATPase Simulation - 327,506 AtomsCore i9 9900KS0.38360.76721.15081.53441.918SE +/- 0.00361, N = 31.70503

Zstd Compression

This test measures the time needed to compress a sample file (an Ubuntu ISO) using Zstd compression. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.4.5Compression Level: 3Core i9 9900KS8001600240032004000SE +/- 0.58, N = 33605.51. (CC) gcc options: -O3 -pthread -lz -llzma

OpenBenchmarking.orgMB/s, More Is BetterZstd Compression 1.4.5Compression Level: 19Core i9 9900KS714212835SE +/- 0.03, N = 332.01. (CC) gcc options: -O3 -pthread -lz -llzma

perf-bench

OpenBenchmarking.orgops/sec, More Is Betterperf-benchBenchmark: Epoll WaitCore i9 9900KS30K60K90K120K150KSE +/- 2511.08, N = 31537831. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -Xlinker -export-dynamic -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lpython2.7 -lutil -lz -llzma -lnuma

OpenBenchmarking.orgops/sec, More Is Betterperf-benchBenchmark: Futex HashCore i9 9900KS1.3M2.6M3.9M5.2M6.5MSE +/- 5040.28, N = 360896021. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -Xlinker -export-dynamic -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lpython2.7 -lutil -lz -llzma -lnuma

OpenBenchmarking.orgGB/sec, More Is Betterperf-benchBenchmark: Memcpy 1MBCore i9 9900KS816243240SE +/- 0.00, N = 334.211. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -Xlinker -export-dynamic -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lpython2.7 -lutil -lz -llzma -lnuma

OpenBenchmarking.orgGB/sec, More Is Betterperf-benchBenchmark: Memset 1MBCore i9 9900KS1326395265SE +/- 0.93, N = 356.221. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -Xlinker -export-dynamic -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lpython2.7 -lutil -lz -llzma -lnuma

OpenBenchmarking.orgops/sec, More Is Betterperf-benchBenchmark: Sched PipeCore i9 9900KS60K120K180K240K300KSE +/- 2066.94, N = 32769421. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -Xlinker -export-dynamic -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lpython2.7 -lutil -lz -llzma -lnuma

OpenBenchmarking.orgops/sec, More Is Betterperf-benchBenchmark: Futex Lock-PiCore i9 9900KS120240360480600SE +/- 5.17, N = 35511. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -Xlinker -export-dynamic -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lpython2.7 -lutil -lz -llzma -lnuma

OpenBenchmarking.orgops/sec, More Is Betterperf-benchBenchmark: Syscall BasicCore i9 9900KS5M10M15M20M25MSE +/- 4479.61, N = 3215529381. (CC) gcc options: -O6 -ggdb3 -funwind-tables -std=gnu99 -Xlinker -export-dynamic -lpthread -lrt -lm -ldl -lelf -lcrypto -lslang -lpython2.7 -lutil -lz -llzma -lnuma

TensorFlow Lite

This is a benchmark of the TensorFlow Lite implementation. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: SqueezeNetCore i9 9900KS40K80K120K160K200KSE +/- 260.35, N = 3201164

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception V4Core i9 9900KS600K1200K1800K2400K3000KSE +/- 781.71, N = 32896153

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: NASNet MobileCore i9 9900KS40K80K120K160K200KSE +/- 287.53, N = 3176817

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet FloatCore i9 9900KS30K60K90K120K150KSE +/- 24.10, N = 3136586

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet QuantCore i9 9900KS30K60K90K120K150KSE +/- 156.47, N = 3140069

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception ResNet V2Core i9 9900KS600K1200K1800K2400K3000KSE +/- 663.96, N = 32621277

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device Inference ScoreCore i9 9900KS300600900120015001294

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device Training ScoreCore i9 9900KS300600900120015001285

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device AI ScoreCore i9 9900KS60012001800240030002579

22 Results Shown

LeelaChessZero:
  BLAS
  Eigen
  Rand
NAMD
Zstd Compression:
  3
  19
perf-bench:
  Epoll Wait
  Futex Hash
  Memcpy 1MB
  Memset 1MB
  Sched Pipe
  Futex Lock-Pi
  Syscall Basic
TensorFlow Lite:
  SqueezeNet
  Inception V4
  NASNet Mobile
  Mobilenet Float
  Mobilenet Quant
  Inception ResNet V2
AI Benchmark Alpha:
  Device Inference Score
  Device Training Score
  Device AI Score