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Intel Core Ultra 7 155H testing with a MTL Swift SFG14-72T Coral_MTH (V1.01 BIOS) and Intel Arc MTL 8GB 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 2403279-NE-LDLD8328551
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March 27
  2 Hours, 27 Minutes
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March 27
  2 Hours, 26 Minutes
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ldldOpenBenchmarking.orgPhoronix Test SuiteIntel Core Ultra 7 155H @ 4.80GHz (16 Cores / 22 Threads)MTL Swift SFG14-72T Coral_MTH (V1.01 BIOS)Intel Device 7e7f8 x 2GB DRAM-6400MT/s Micron MT62F1G32D2DS-0261024GB Micron_2550_MTFDKBA1T0TGEIntel Arc MTL 8GB (2250MHz)Intel Meteor Lake-P HD AudioIntel Device 7e40Ubuntu 23.106.8.0-060800rc1daily20240126-generic (x86_64)GNOME Shell 45.2X Server 1.21.1.7 + Wayland4.6 Mesa 24.1~git2401200600.ebcab1~oibaf~m (git-ebcab14 2024-01-20 mantic-oibaf-ppa)GCC 13.2.0ext41920x1200ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLCompilerFile-SystemScreen ResolutionLdld 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: 0x13 - Thermald 2.5.4- 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: Not affected + srbds: Not affected + tsx_async_abort: Not affected

a vs. b ComparisonPhoronix Test SuiteBaseline+5%+5%+10%+10%+15%+15%19.9%19%16.1%6.9%3.2%2.9%2.2%2.2%CPU - 16 - Efficientnet_v2_lCPU - 1 - ResNet-50CPU - 16 - ResNet-152CPU - 256 - ResNet-5015.6%CPU - 1 - ResNet-15212.3%Classroom - CPU-Only8.7%Time To CompileCPU - 64 - ResNet-505.4%CPU - 64 - ResNet-1524.8%CPU - 256 - Efficientnet_v2_l4.3%CPU - 1 - ResNet-504.2%CPU - 1 - GoogLeNet4.2%CPU - 32 - ResNet-152CPU - 32 - Efficientnet_v2_lCPU - 64 - AlexNetCPU - 256 - ResNet-152PyTorchTensorFlowPyTorchPyTorchPyTorchBlenderTimed Mesa CompilationPyTorchPyTorchPyTorchPyTorchTensorFlowPyTorchPyTorchTensorFlowPyTorchab

ldldbuild-mesa: Time To Compilepytorch: 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 - 256 - ResNet-50pytorch: CPU - 32 - ResNet-152pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 1 - Efficientnet_v2_lpytorch: CPU - 16 - Efficientnet_v2_lpytorch: CPU - 32 - Efficientnet_v2_lpytorch: CPU - 64 - Efficientnet_v2_lpytorch: CPU - 256 - Efficientnet_v2_ltensorflow: CPU - 1 - AlexNettensorflow: CPU - 16 - AlexNettensorflow: CPU - 32 - AlexNettensorflow: CPU - 64 - AlexNettensorflow: CPU - 1 - GoogLeNettensorflow: CPU - 1 - ResNet-50tensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - ResNet-50tensorflow: CPU - 32 - GoogLeNettensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 64 - GoogLeNettensorflow: CPU - 64 - ResNet-50blender: BMW27 - CPU-Onlyblender: Junkshop - CPU-Onlyblender: Fishy Cat - CPU-Onlyblender: Barbershop - CPU-Onlyblender: Pabellon Barcelona - CPU-Onlyblender: Classroom - CPU-Onlyab34.88929.4910.3416.0316.1315.934.6715.865.935.866.026.603.073.493.783.8515.7192.7101.75104.1830.897.9148.0514.3347.2514.7746.5115.35163.16249.71234.471770.95572.7405.3832.62228.309.2115.9315.9815.125.4213.726.125.596.156.503.683.593.773.6915.7191.49101.38106.529.659.4147.9314.3647.4514.7546.4115.37161.09249.42230.591757.8578.85440.58OpenBenchmarking.org

Timed Mesa Compilation

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Mesa Compilation 24.0Time To Compileab81624324034.8932.62

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-50ab71421283529.4928.30MIN: 21.36 / MAX: 33.16MIN: 19.22 / MAX: 33.62

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: ResNet-152ab369121510.349.21MIN: 8.48 / MAX: 12.31MIN: 5.28 / MAX: 12.19

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-50ab4812162016.0315.93MIN: 10.94 / MAX: 18.23MIN: 8.32 / MAX: 18.45

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-50ab4812162016.1315.98MIN: 14.64 / MAX: 18.27MIN: 14.51 / MAX: 17.51

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-50ab4812162015.9315.12MIN: 14.58 / MAX: 17.56MIN: 11.4 / MAX: 18.4

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: ResNet-152ab1.21952.4393.65854.8786.09754.675.42MIN: 3.7 / MAX: 6.87MIN: 3.09 / MAX: 7.11

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-50ab4812162015.8613.72MIN: 13.05 / MAX: 19.69MIN: 5.4 / MAX: 20.19

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: ResNet-152ab2468105.936.12MIN: 4.07 / MAX: 7.46MIN: 4.5 / MAX: 6.7

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: ResNet-152ab1.31852.6373.95555.2746.59255.865.59MIN: 4.18 / MAX: 6.58MIN: 3.08 / MAX: 7.82

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: ResNet-152ab2468106.026.15MIN: 5.41 / MAX: 6.78MIN: 3.67 / MAX: 6.86

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lab2468106.606.50MIN: 2.38 / MAX: 8.69MIN: 3.03 / MAX: 9.45

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lab0.8281.6562.4843.3124.143.073.68MIN: 1.97 / MAX: 4.84MIN: 1.84 / MAX: 4.81

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lab0.80781.61562.42343.23124.0393.493.59MIN: 2.11 / MAX: 4.99MIN: 2.08 / MAX: 4.37

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lab0.85051.7012.55153.4024.25253.783.77MIN: 3.03 / MAX: 4.36MIN: 2.09 / MAX: 4.51

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lab0.86631.73262.59893.46524.33153.853.69MIN: 2.11 / MAX: 4.99MIN: 2.02 / MAX: 4.78

TensorFlow

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: AlexNetab4812162015.7115.71

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: AlexNetab2040608010092.7091.49

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: AlexNetab20406080100101.75101.38

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: AlexNetab20406080100104.18106.50

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: GoogLeNetab71421283530.8929.65

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 1 - Model: ResNet-50ab36912157.919.41

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: GoogLeNetab112233445548.0547.93

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 16 - Model: ResNet-50ab4812162014.3314.36

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: GoogLeNetab112233445547.2547.45

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 32 - Model: ResNet-50ab4812162014.7714.75

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: GoogLeNetab112233445546.5146.41

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.16.1Device: CPU - Batch Size: 64 - Model: ResNet-50ab4812162015.3515.37

Blender

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: BMW27 - Compute: CPU-Onlyab4080120160200163.16161.09

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Junkshop - Compute: CPU-Onlyab50100150200250249.71249.42

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Fishy Cat - Compute: CPU-Onlyab50100150200250234.47230.59

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Barbershop - Compute: CPU-Onlyab4008001200160020001770.951757.80

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Pabellon Barcelona - Compute: CPU-Onlyab130260390520650572.70578.85

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.1Blend File: Classroom - Compute: CPU-Onlyab100200300400500405.38440.58