tg

Tests for a future article. Intel Core i7-1280P testing with a MSI MS-14C6 (E14C6IMS.115 BIOS) and MSI Intel ADL GT2 15GB on Ubuntu 23.10 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 2311250-NE-TG983149007
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November 25 2023
  1 Hour, 57 Minutes
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November 25 2023
  2 Hours, 23 Minutes
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tgOpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-1280P @ 4.70GHz (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 23.106.5.0-10-generic (x86_64)GNOME Shell 45.0X Server + Wayland4.6 Mesa 23.2.1-1ubuntu3OpenCL 3.0GCC 13.2.0ext41920x1080ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLOpenCLCompilerFile-SystemScreen ResolutionTg BenchmarksSystem Logs- Transparent Huge Pages: madvise- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --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-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-XYspKM/gcc-13-13.2.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-13-XYspKM/gcc-13-13.2.0/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-build-config=bootstrap-lto-lean --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: 0x42c - Thermald 2.5.4 - OpenJDK Runtime Environment (build 17.0.9-ea+6-Ubuntu-1)- Python 3.11.6- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + 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 / Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

a vs. b ComparisonPhoronix Test SuiteBaseline+67.9%+67.9%+135.8%+135.8%+203.7%+203.7%2.3%BLAS CPU FP32271.5%CPU - 32 - ResNet-15240.6%CPU - 16 - Efficientnet_v2_l34.5%BMW27 - CPU-Only31.9%CPU - 1 - ResNet-5029.5%CPU - 16 - ResNet-5028.1%CPU - 64 - ResNet-5028%CPU - 32 - ResNet-5027.9%CPU - 16 - ResNet-15227.4%CPU - 64 - ResNet-15227%CPU - 1 - ResNet-15225.4%CPU - 1 - Efficientnet_v2_l22.9%CPU - 32 - Efficientnet_v2_l16.4%Q.1.C.E.514.3%CPU - 64 - Efficientnet_v2_l8.8%C.G.CArrayFirePyTorchPyTorchBlenderPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchWebP2 Image EncodePyTorchArrayFireab

tgarrayfire: BLAS CPU FP16arrayfire: BLAS CPU FP32arrayfire: Conjugate Gradient CPUblender: BMW27 - CPU-Onlyembree: Pathtracer ISPC - Crownembree: Pathtracer ISPC - Asian Dragonjava-scimark2: Compositejava-scimark2: Monte Carlojava-scimark2: Fast Fourier Transformjava-scimark2: Sparse Matrix Multiplyjava-scimark2: Dense LU Matrix Factorizationjava-scimark2: Jacobi Successive Over-Relaxationpytorch: CPU - 1 - ResNet-50pytorch: CPU - 1 - ResNet-152pytorch: CPU - 16 - ResNet-50pytorch: CPU - 32 - ResNet-50pytorch: CPU - 64 - ResNet-50pytorch: CPU - 16 - ResNet-152pytorch: CPU - 32 - ResNet-152pytorch: CPU - 64 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lwebp2: Defaultwebp2: Quality 75, Compression Effort 7webp2: Quality 95, Compression Effort 7webp2: Quality 100, Compression Effort 5webp2: Quality 100, Lossless Compressionab64.539394.68613.42233.565.33667.1432908.791245.28719.933708.476529.952340.3520.049.1913.7713.7813.765.445.405.455.523.393.483.237.050.090.043.600.0164.2895106.23513.12308.055.33167.1112916.231246.36725.123733.826531.952343.9315.477.3310.7510.7710.754.273.844.294.492.522.992.977.040.090.043.150.01OpenBenchmarking.org

ArrayFire

ArrayFire is an GPU and CPU numeric processing library, this test uses the built-in CPU and OpenCL ArrayFire benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterArrayFire 3.9Test: BLAS CPU FP16ab142842567064.5464.291. (CXX) g++ options: -O3

OpenBenchmarking.orgGFLOPS, More Is BetterArrayFire 3.9Test: BLAS CPU FP32ab90180270360450394.69106.241. (CXX) g++ options: -O3

OpenBenchmarking.orgms, Fewer Is BetterArrayFire 3.9Test: Conjugate Gradient CPUba369121513.1213.421. (CXX) g++ options: -O3

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: BMW27 - Compute: CPU-Onlyab70140210280350233.56308.05

Embree

Intel Embree is a collection of high-performance ray-tracing kernels for execution on CPUs (and GPUs via SYCL) and supporting instruction sets such as SSE, AVX, AVX2, and AVX-512. Embree also supports making use of the Intel SPMD Program Compiler (ISPC). Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Crownab1.20072.40143.60214.80286.00355.33665.3316MIN: 5.2 / MAX: 5.49MIN: 5.2 / MAX: 5.49

OpenBenchmarking.orgFrames Per Second, More Is BetterEmbree 4.3Binary: Pathtracer ISPC - Model: Asian Dragonab2468107.1437.111MIN: 7.04 / MAX: 7.25MIN: 6.99 / MAX: 7.23

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: Compositeba60012001800240030002916.232908.79

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Monte Carloba300600900120015001246.361245.28

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Fast Fourier Transformba160320480640800725.12719.93

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Sparse Matrix Multiplyba80016002400320040003733.823708.47

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Dense LU Matrix Factorizationba140028004200560070006531.956529.95

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Jacobi Successive Over-Relaxationba50010001500200025002343.932340.35

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ab51015202520.0415.47MIN: 17.17 / MAX: 35.57MIN: 14.08 / MAX: 22.48

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152ab36912159.197.33MIN: 8.48 / MAX: 12.97MIN: 7.08 / MAX: 11.65

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ab4812162013.7710.75MIN: 12.94 / MAX: 18.53MIN: 10.17 / MAX: 15.41

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50ab4812162013.7810.77MIN: 13.15 / MAX: 18.24MIN: 10.43 / MAX: 14.76

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50ab4812162013.7610.75MIN: 13.09 / MAX: 18.12MIN: 10.57 / MAX: 15.02

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ab1.2242.4483.6724.8966.125.444.27MIN: 5.3 / MAX: 7.11MIN: 4.17 / MAX: 5.87

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ab1.2152.433.6454.866.0755.403.84MIN: 5.26 / MAX: 7.05MIN: 3.77 / MAX: 5.24

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152ab1.22632.45263.67894.90526.13155.454.29MIN: 5.17 / MAX: 7.1MIN: 4.22 / MAX: 5.81

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lab1.2422.4843.7264.9686.215.524.49MIN: 5.16 / MAX: 8.36MIN: 4.05 / MAX: 6.6

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lab0.76281.52562.28843.05123.8143.392.52MIN: 3.16 / MAX: 5.04MIN: 2.46 / MAX: 3.36

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lab0.7831.5662.3493.1323.9153.482.99MIN: 3.2 / MAX: 4.03MIN: 2.89 / MAX: 4.23

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lab0.72681.45362.18042.90723.6343.232.97MIN: 3.15 / MAX: 4.09MIN: 2.92 / MAX: 4.19

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: Defaultab2468107.057.041. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 75, Compression Effort 7ba0.02030.04060.06090.08120.10150.090.091. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 95, Compression Effort 7ba0.0090.0180.0270.0360.0450.040.041. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Compression Effort 5ab0.811.622.433.244.053.603.151. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 100, Lossless Compressionba0.00230.00460.00690.00920.01150.010.011. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl