AI Daphne Candle

Intel Core i9-10980XE testing with a ASRock X299 Steel Legend (P1.30 BIOS) and NVIDIA NV132 11GB on Ubuntu 20.10 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 2008135-NE-AIDAPHNEC36
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Identifier
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Performance Per
Dollar
Date
Run
  Test
  Duration
Intel Core i9-10980XE - NVIDIA NV132 11GB - ASRock
August 13 2020
  1 Hour, 19 Minutes
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AI Daphne CandleOpenBenchmarking.orgPhoronix Test SuiteIntel Core i9-10980XE @ 4.80GHz (18 Cores / 36 Threads)ASRock X299 Steel Legend (P1.30 BIOS)Intel Sky Lake-E DMI3 Registers32GBSamsung SSD 970 PRO 512GBNVIDIA NV132 11GBRealtek ALC1220ASUS MG28UIntel I219-V + Intel I211Ubuntu 20.105.4.0-42-generic (x86_64)GNOME Shell 3.36.4X Server 1.20.8modesetting 1.20.84.3 Mesa 20.1.2GCC 10.2.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionAI Daphne Candle 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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-10-TMmQyZ/gcc-10-10.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-10-TMmQyZ/gcc-10-10.2.0/debian/tmp-gcn/usr,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 performance - CPU Microcode: 0x5002f01- Python 3.8.5- itlb_multihit: KVM: Mitigation of Split huge pages + 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: Not affected + tsx_async_abort: Mitigation of TSX disabled

AI Daphne Candledaphne: OpenMP - NDT Mappingdaphne: OpenMP - Points2Imagedaphne: OpenMP - Euclidean Clusterecp-candle: P1B2ecp-candle: P3B1ecp-candle: P3B2ai-benchmark: Device Inference Scoreai-benchmark: Device Training Scoreai-benchmark: Device AI ScoreIntel Core i9-10980XE - NVIDIA NV132 11GB - ASRock903.8424534.3977442451339.7432.06659.555575.081198816233611OpenBenchmarking.org

Darmstadt Automotive Parallel Heterogeneous Suite

DAPHNE is the Darmstadt Automotive Parallel HeterogeNEous Benchmark Suite with OpenCL / CUDA / OpenMP test cases for these automotive benchmarks for evaluating programming models in context to vehicle autonomous driving capabilities. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenMP - Kernel: NDT MappingIntel Core i9-10980XE - NVIDIA NV132 11GB - ASRock2004006008001000SE +/- 3.59, N = 3903.841. (CXX) g++ options: -O3 -std=c++11 -fopenmp

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenMP - Kernel: Points2ImageIntel Core i9-10980XE - NVIDIA NV132 11GB - ASRock5K10K15K20K25KSE +/- 409.49, N = 324534.401. (CXX) g++ options: -O3 -std=c++11 -fopenmp

OpenBenchmarking.orgTest Cases Per Minute, More Is BetterDarmstadt Automotive Parallel Heterogeneous SuiteBackend: OpenMP - Kernel: Euclidean ClusterIntel Core i9-10980XE - NVIDIA NV132 11GB - ASRock30060090012001500SE +/- 1.69, N = 31339.741. (CXX) g++ options: -O3 -std=c++11 -fopenmp

ECP-CANDLE

The CANDLE benchmark codes implement deep learning architectures relevant to problems in cancer. These architectures address problems at different biological scales, specifically problems at the molecular, cellular and population scales. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterECP-CANDLE 0.3Benchmark: P1B2Intel Core i9-10980XE - NVIDIA NV132 11GB - ASRock71421283532.06

OpenBenchmarking.orgSeconds, Fewer Is BetterECP-CANDLE 0.3Benchmark: P3B1Intel Core i9-10980XE - NVIDIA NV132 11GB - ASRock140280420560700659.56

OpenBenchmarking.orgSeconds, Fewer Is BetterECP-CANDLE 0.3Benchmark: P3B2Intel Core i9-10980XE - NVIDIA NV132 11GB - ASRock120240360480600575.08

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 ScoreIntel Core i9-10980XE - NVIDIA NV132 11GB - ASRock4008001200160020001988

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device Training ScoreIntel Core i9-10980XE - NVIDIA NV132 11GB - ASRock300600900120015001623

OpenBenchmarking.orgScore, More Is BetterAI Benchmark Alpha 0.1.2Device AI ScoreIntel Core i9-10980XE - NVIDIA NV132 11GB - ASRock80016002400320040003611

9 Results Shown

Darmstadt Automotive Parallel Heterogeneous Suite:
  OpenMP - NDT Mapping
  OpenMP - Points2Image
  OpenMP - Euclidean Cluster
ECP-CANDLE:
  P1B2
  P3B1
  P3B2
AI Benchmark Alpha:
  Device Inference Score
  Device Training Score
  Device AI Score