tg

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.

HTML result view exported from: https://openbenchmarking.org/result/2311253-NE-TG843149007&rdt&grt.

tgProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLOpenCLCompilerFile-SystemScreen ResolutionabIntel 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 13.2.0ext41920x1080OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseCompiler Details- --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 Processor Details- Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0x42c - Thermald 2.5.4 Java Details- OpenJDK Runtime Environment (build 17.0.9-ea+6-Ubuntu-1)Python Details- Python 3.11.6Security Details- 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

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

Test: BLAS CPU FP16

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

ArrayFire

Test: BLAS CPU FP32

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

ArrayFire

Test: Conjugate Gradient CPU

OpenBenchmarking.orgms, Fewer Is BetterArrayFire 3.9Test: Conjugate Gradient CPUab369121513.4213.121. (CXX) g++ options: -O3

Blender

Blend File: BMW27 - Compute: CPU-Only

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

Embree

Binary: Pathtracer ISPC - Model: Crown

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

Embree

Binary: Pathtracer ISPC - Model: Asian Dragon

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

Computational Test: Composite

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Compositeab60012001800240030002908.792916.23

Java SciMark

Computational Test: Monte Carlo

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Monte Carloab300600900120015001245.281246.36

Java SciMark

Computational Test: Fast Fourier Transform

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Fast Fourier Transformab160320480640800719.93725.12

Java SciMark

Computational Test: Sparse Matrix Multiply

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Sparse Matrix Multiplyab80016002400320040003708.473733.82

Java SciMark

Computational Test: Dense LU Matrix Factorization

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Dense LU Matrix Factorizationab140028004200560070006529.956531.95

Java SciMark

Computational Test: Jacobi Successive Over-Relaxation

OpenBenchmarking.orgMflops, More Is BetterJava SciMark 2.2Computational Test: Jacobi Successive Over-Relaxationab50010001500200025002340.352343.93

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-50

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

PyTorch

Device: CPU - Batch Size: 1 - Model: ResNet-152

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

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-50

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

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-50

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

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-50

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

PyTorch

Device: CPU - Batch Size: 16 - Model: ResNet-152

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

PyTorch

Device: CPU - Batch Size: 32 - Model: ResNet-152

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

PyTorch

Device: CPU - Batch Size: 64 - Model: ResNet-152

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

PyTorch

Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l

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

PyTorch

Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l

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

PyTorch

Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l

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

PyTorch

Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l

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

Encode Settings: Default

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Defaultab2468107.057.041. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

WebP2 Image Encode

Encode Settings: Quality 75, Compression Effort 7

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 75, Compression Effort 7ab0.02030.04060.06090.08120.10150.090.091. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

WebP2 Image Encode

Encode Settings: Quality 95, Compression Effort 7

OpenBenchmarking.orgMP/s, More Is BetterWebP2 Image Encode 20220823Encode Settings: Quality 95, Compression Effort 7ab0.0090.0180.0270.0360.0450.040.041. (CXX) g++ options: -msse4.2 -fno-rtti -O3 -ldl

WebP2 Image Encode

Encode Settings: Quality 100, Compression Effort 5

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

WebP2 Image Encode

Encode Settings: Quality 100, Lossless Compression

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

Phoronix Test Suite v10.8.5