mlaug2

Intel Core i7-10700K testing with a ASUS ROG STRIX Z490-F GAMING (0403 BIOS) and NVIDIA GeForce RTX 3060 Ti 8GB on Ubuntu 20.04 via the Phoronix Test Suite.

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NVIDIA GeForce RTX 3060 Ti
August 03 2021
  2 Hours
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NVIDIA GeForce RTX 3060 Ti

Processor: Intel Core i7-10700K @ 5.10GHz (8 Cores / 16 Threads), Motherboard: ASUS ROG STRIX Z490-F GAMING (0403 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: 1024GB Viper M.2 VPN100 + Sabrent Rocket 4.0 500GB, Graphics: NVIDIA GeForce RTX 3060 Ti 8GB, Audio: Realtek ALC1220, Monitor: S24H85x, Network: Intel Device 15f3 + Intel Wi-Fi 6 AX200

OS: Ubuntu 20.04, Kernel: 5.8.0-63-generic (x86_64), Desktop: GNOME Shell 3.36.7, Display Server: X Server 1.20.9, Display Driver: NVIDIA 470.57.02, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 11.4.94, Vulkan: 1.2.175, Compiler: GCC 9.3.0 + CUDA 11.2, File-System: ext4, Screen Resolution: 5120x1440

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --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=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/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
Processor Notes: Scaling Governor: intel_pstate powersave - CPU Microcode: 0xec - Thermald 1.9.1
OpenCL Notes: GPU Compute Cores: 4864
Python Notes: Python 3.8.5
Security Notes: itlb_multihit: KVM: Mitigation of VMX disabled + 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: Not affected

mlaug2OpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-10700K @ 5.10GHz (8 Cores / 16 Threads)ASUS ROG STRIX Z490-F GAMING (0403 BIOS)Intel Comet Lake PCH32GB1024GB Viper M.2 VPN100 + Sabrent Rocket 4.0 500GBNVIDIA GeForce RTX 3060 Ti 8GBRealtek ALC1220S24H85xIntel Device 15f3 + Intel Wi-Fi 6 AX200Ubuntu 20.045.8.0-63-generic (x86_64)GNOME Shell 3.36.7X Server 1.20.9NVIDIA 470.57.024.6.0OpenCL 3.0 CUDA 11.4.941.2.175GCC 9.3.0 + CUDA 11.2ext45120x1440ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerDisplay DriverOpenGLOpenCLVulkanCompilerFile-SystemScreen ResolutionMlaug2 BenchmarksSystem Logs- Transparent Huge Pages: madvise- --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=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/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 powersave - CPU Microcode: 0xec - Thermald 1.9.1 - GPU Compute Cores: 4864- Python 3.8.5- itlb_multihit: KVM: Mitigation of VMX disabled + 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: Not affected

mlaug2numpy: deepspeech: CPUtensorflow-lite: SqueezeNettensorflow-lite: Inception V4tensorflow-lite: NASNet Mobiletensorflow-lite: Mobilenet Floattensorflow-lite: Mobilenet Quanttensorflow-lite: Inception ResNet V2plaidml: No - Inference - VGG16 - CPUplaidml: No - Inference - ResNet 50 - CPUecp-candle: P1B2ecp-candle: P3B1numenta-nab: EXPoSEnumenta-nab: Relative Entropynumenta-nab: Windowed Gaussiannumenta-nab: Earthgecko Skylinenumenta-nab: Bayesian Changepointmlpack: scikit_icamlpack: scikit_qdamlpack: scikit_svmmlpack: scikit_linearridgeregressionscikit-learn: NVIDIA GeForce RTX 3060 Ti426.5169.054851939532781937159375129642131842251722716.356.55357.87343.081331.98219.8119.414128.74840.91032.26123.6721.622.007.415OpenBenchmarking.org

Numpy Benchmark

This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterNumpy BenchmarkNVIDIA GeForce RTX 3060 Ti90180270360450SE +/- 0.66, N = 3426.51

DeepSpeech

Mozilla DeepSpeech is a speech-to-text engine powered by TensorFlow for machine learning and derived from Baidu's Deep Speech research paper. This test profile times the speech-to-text process for a roughly three minute audio recording. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDeepSpeech 0.6Acceleration: CPUNVIDIA GeForce RTX 3060 Ti1530456075SE +/- 0.04, N = 369.05

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: SqueezeNetNVIDIA GeForce RTX 3060 Ti40K80K120K160K200KSE +/- 402.02, N = 3193953

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception V4NVIDIA GeForce RTX 3060 Ti600K1200K1800K2400K3000KSE +/- 1651.79, N = 32781937

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: NASNet MobileNVIDIA GeForce RTX 3060 Ti30K60K90K120K150KSE +/- 314.90, N = 3159375

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet FloatNVIDIA GeForce RTX 3060 Ti30K60K90K120K150KSE +/- 49.96, N = 3129642

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Mobilenet QuantNVIDIA GeForce RTX 3060 Ti30K60K90K120K150KSE +/- 8.09, N = 3131842

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2020-08-23Model: Inception ResNet V2NVIDIA GeForce RTX 3060 Ti500K1000K1500K2000K2500KSE +/- 4334.31, N = 32517227

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: CPUNVIDIA GeForce RTX 3060 Ti48121620SE +/- 0.10, N = 316.35

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: ResNet 50 - Device: CPUNVIDIA GeForce RTX 3060 Ti246810SE +/- 0.02, N = 36.55

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 0.4Benchmark: P1B2NVIDIA GeForce RTX 3060 Ti80160240320400357.87

OpenBenchmarking.orgSeconds, Fewer Is BetterECP-CANDLE 0.4Benchmark: P3B1NVIDIA GeForce RTX 3060 Ti70140210280350343.08

Numenta Anomaly Benchmark

Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial timeseries data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: EXPoSENVIDIA GeForce RTX 3060 Ti70140210280350SE +/- 3.94, N = 3331.98

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Relative EntropyNVIDIA GeForce RTX 3060 Ti510152025SE +/- 0.07, N = 319.81

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Windowed GaussianNVIDIA GeForce RTX 3060 Ti3691215SE +/- 0.009, N = 39.414

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Earthgecko SkylineNVIDIA GeForce RTX 3060 Ti306090120150SE +/- 0.84, N = 3128.75

OpenBenchmarking.orgSeconds, Fewer Is BetterNumenta Anomaly Benchmark 1.1Detector: Bayesian ChangepointNVIDIA GeForce RTX 3060 Ti918273645SE +/- 0.07, N = 340.91

Mlpack Benchmark

Mlpack benchmark scripts for machine learning libraries Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_icaNVIDIA GeForce RTX 3060 Ti714212835SE +/- 0.03, N = 332.26

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_qdaNVIDIA GeForce RTX 3060 Ti306090120150SE +/- 0.19, N = 3123.67

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_svmNVIDIA GeForce RTX 3060 Ti510152025SE +/- 0.01, N = 321.62

OpenBenchmarking.orgSeconds, Fewer Is BetterMlpack BenchmarkBenchmark: scikit_linearridgeregressionNVIDIA GeForce RTX 3060 Ti0.450.91.351.82.25SE +/- 0.00, N = 32.00

Scikit-Learn

Scikit-learn is a Python module for machine learning Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterScikit-Learn 0.22.1NVIDIA GeForce RTX 3060 Ti246810SE +/- 0.005, N = 37.415

NVIDIA GeForce RTX 3060 Ti

Processor: Intel Core i7-10700K @ 5.10GHz (8 Cores / 16 Threads), Motherboard: ASUS ROG STRIX Z490-F GAMING (0403 BIOS), Chipset: Intel Comet Lake PCH, Memory: 32GB, Disk: 1024GB Viper M.2 VPN100 + Sabrent Rocket 4.0 500GB, Graphics: NVIDIA GeForce RTX 3060 Ti 8GB, Audio: Realtek ALC1220, Monitor: S24H85x, Network: Intel Device 15f3 + Intel Wi-Fi 6 AX200

OS: Ubuntu 20.04, Kernel: 5.8.0-63-generic (x86_64), Desktop: GNOME Shell 3.36.7, Display Server: X Server 1.20.9, Display Driver: NVIDIA 470.57.02, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 11.4.94, Vulkan: 1.2.175, Compiler: GCC 9.3.0 + CUDA 11.2, File-System: ext4, Screen Resolution: 5120x1440

Kernel Notes: Transparent Huge Pages: madvise
Compiler Notes: --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=/build/gcc-9-HskZEa/gcc-9-9.3.0/debian/tmp-nvptx/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
Processor Notes: Scaling Governor: intel_pstate powersave - CPU Microcode: 0xec - Thermald 1.9.1
OpenCL Notes: GPU Compute Cores: 4864
Python Notes: Python 3.8.5
Security Notes: itlb_multihit: KVM: Mitigation of VMX disabled + 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: Not affected

Testing initiated at 3 August 2021 06:48 by user bharath.