fs

Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 22.04 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 2311191-PTS-FS16700400
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November 18 2023
  2 Hours, 15 Minutes
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November 18 2023
  2 Hours, 16 Minutes
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November 18 2023
  2 Hours, 15 Minutes
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November 18 2023
  7 Hours, 13 Minutes
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fsOpenBenchmarking.orgPhoronix Test SuiteIntel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads)Dell 0DXP1F (3.7.0 BIOS)Intel Tiger Lake-LP16GBMicron 2300 NVMe 512GBIntel Xe TGL GT2 15GB (1350MHz)Realtek ALC289Intel Wi-Fi 6 AX201Ubuntu 22.046.2.0-36-generic (x86_64)GNOME Shell 42.2X Server + Wayland4.6 Mesa 22.0.1OpenCL 3.01.3.204GCC 11.4.0ext41920x1200ProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLOpenCLVulkanCompilerFile-SystemScreen ResolutionFs PerformanceSystem Logs- Transparent Huge Pages: madvise- Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xac - Thermald 2.4.9 - Python 3.10.12- gather_data_sampling: Mitigation of Microcode + 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 IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected

sbcdResult OverviewPhoronix Test Suite100%106%113%119%PyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchBlenderPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchPyTorchBlenderBlenderPyTorchBlenderCPU - 1 - ResNet-50CPU - 1 - ResNet-152CPU - 16 - ResNet-50CPU - 16 - ResNet-152CPU - 32 - ResNet-50CPU - 256 - ResNet-50CPU - 64 - ResNet-152CPU - 256 - ResNet-152Classroom - CPU-OnlyCPU - 16 - Efficientnet_v2_lCPU - 256 - Efficientnet_v2_lCPU - 512 - ResNet-152CPU - 32 - ResNet-152CPU - 1 - Efficientnet_v2_lCPU - 512 - ResNet-50CPU - 64 - ResNet-50CPU - 64 - Efficientnet_v2_lCPU - 512 - Efficientnet_v2_lBMW27 - CPU-OnlyPabellon Barcelona - CPU-OnlyCPU - 32 - Efficientnet_v2_lFishy Cat - CPU-Only

fspytorch: 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 - 512 - ResNet-50pytorch: CPU - 64 - ResNet-152pytorch: CPU - 256 - ResNet-152pytorch: CPU - 512 - 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_lpytorch: CPU - 512 - Efficientnet_v2_lblender: BMW27 - CPU-Onlyblender: Classroom - CPU-Onlyblender: Fishy Cat - CPU-Onlyblender: Pabellon Barcelona - CPU-Onlysbcd31.0811.5114.2313.8613.825.4913.905.5713.835.545.555.567.374.084.114.104.134.10417.281100.02528.211401.8830.159.9313.7813.6513.755.6313.765.5813.745.615.605.597.324.114.124.114.084.12417.641103.33528.721405.3730.6210.9713.7813.7913.795.6213.815.6113.815.615.595.597.364.134.124.124.124.12416.741101.16528.011401.1324.759.7913.8113.5313.795.5813.685.6213.775.625.625.627.334.134.114.124.124.11416.311113.84528.781402.14OpenBenchmarking.org

PyTorch

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50sbcd714212835SE +/- 0.45, N = 1331.0830.1530.6224.75MIN: 24.28 / MAX: 32.05MIN: 23.77 / MAX: 31.47MIN: 23.7 / MAX: 31.5MIN: 13.75 / MAX: 31.86
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50sbcd714212835Min: 23.99 / Avg: 24.75 / Max: 30.13

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152sbcd3691215SE +/- 0.02, N = 311.519.9310.979.79MIN: 9.43 / MAX: 12.68MIN: 5.85 / MAX: 12.52MIN: 9 / MAX: 12.55MIN: 7.71 / MAX: 9.95
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152sbcd3691215Min: 9.75 / Avg: 9.79 / Max: 9.81

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50sbcd48121620SE +/- 0.05, N = 314.2313.7813.7813.81MIN: 12.34 / MAX: 16.52MIN: 12.06 / MAX: 14.04MIN: 11.44 / MAX: 14MIN: 11.95 / MAX: 14.1
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50sbcd48121620Min: 13.74 / Avg: 13.81 / Max: 13.91

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50sbcd48121620SE +/- 0.10, N = 313.8613.6513.7913.53MIN: 12.24 / MAX: 14.1MIN: 11.36 / MAX: 13.96MIN: 12.26 / MAX: 13.98MIN: 7.72 / MAX: 13.95
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50sbcd48121620Min: 13.39 / Avg: 13.53 / Max: 13.73

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50sbcd48121620SE +/- 0.03, N = 313.8213.7513.7913.79MIN: 12.08 / MAX: 14.09MIN: 12.17 / MAX: 13.99MIN: 12.1 / MAX: 14.08MIN: 12.11 / MAX: 14.04
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50sbcd48121620Min: 13.74 / Avg: 13.79 / Max: 13.84

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152sbcd1.26682.53363.80045.06726.334SE +/- 0.04, N = 35.495.635.625.58MIN: 4.9 / MAX: 5.6MIN: 5.35 / MAX: 5.71MIN: 5.35 / MAX: 5.69MIN: 4.32 / MAX: 5.7
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152sbcd246810Min: 5.5 / Avg: 5.58 / Max: 5.63

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50sbcd48121620SE +/- 0.12, N = 313.9013.7613.8113.68MIN: 10.84 / MAX: 14.08MIN: 9.38 / MAX: 13.97MIN: 11.69 / MAX: 14.05MIN: 11.92 / MAX: 14.02
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50sbcd48121620Min: 13.43 / Avg: 13.68 / Max: 13.83

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152sbcd1.26452.5293.79355.0586.3225SE +/- 0.01, N = 35.575.585.615.62MIN: 4.59 / MAX: 5.66MIN: 4.83 / MAX: 5.65MIN: 5.32 / MAX: 5.68MIN: 4.5 / MAX: 5.69
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152sbcd246810Min: 5.6 / Avg: 5.62 / Max: 5.63

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50sbcd48121620SE +/- 0.02, N = 313.8313.7413.8113.77MIN: 12.12 / MAX: 14.03MIN: 12.06 / MAX: 13.95MIN: 12.27 / MAX: 14.04MIN: 7.55 / MAX: 14.1
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50sbcd48121620Min: 13.73 / Avg: 13.77 / Max: 13.81

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152sbcd1.26452.5293.79355.0586.3225SE +/- 0.00, N = 35.545.615.615.62MIN: 5.28 / MAX: 5.59MIN: 5.34 / MAX: 5.67MIN: 5.32 / MAX: 5.68MIN: 5.31 / MAX: 5.71
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152sbcd246810Min: 5.62 / Avg: 5.62 / Max: 5.63

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152sbcd1.26452.5293.79355.0586.3225SE +/- 0.01, N = 35.555.605.595.62MIN: 4.7 / MAX: 5.67MIN: 4.17 / MAX: 5.67MIN: 5.31 / MAX: 5.66MIN: 5.19 / MAX: 5.7
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152sbcd246810Min: 5.61 / Avg: 5.62 / Max: 5.63

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152sbcd1.26452.5293.79355.0586.3225SE +/- 0.01, N = 35.565.595.595.62MIN: 4.51 / MAX: 5.64MIN: 5.31 / MAX: 5.66MIN: 4.43 / MAX: 5.65MIN: 3.95 / MAX: 5.71
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152sbcd246810Min: 5.6 / Avg: 5.62 / Max: 5.64

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lsbcd246810SE +/- 0.03, N = 37.377.327.367.33MIN: 5.71 / MAX: 7.46MIN: 5.07 / MAX: 7.42MIN: 6.88 / MAX: 7.43MIN: 5.29 / MAX: 7.45
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_lsbcd3691215Min: 7.27 / Avg: 7.33 / Max: 7.37

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lsbcd0.92931.85862.78793.71724.6465SE +/- 0.00, N = 34.084.114.134.13MIN: 3.25 / MAX: 4.13MIN: 3.78 / MAX: 4.16MIN: 3.56 / MAX: 4.17MIN: 3.27 / MAX: 4.18
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_lsbcd246810Min: 4.12 / Avg: 4.13 / Max: 4.13

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lsbcd0.9271.8542.7813.7084.635SE +/- 0.00, N = 34.114.124.124.11MIN: 3.08 / MAX: 4.17MIN: 3.84 / MAX: 4.17MIN: 3.19 / MAX: 4.17MIN: 2.84 / MAX: 4.16
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_lsbcd246810Min: 4.1 / Avg: 4.11 / Max: 4.12

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lsbcd0.9271.8542.7813.7084.635SE +/- 0.00, N = 34.104.114.124.12MIN: 3.43 / MAX: 4.15MIN: 3.42 / MAX: 4.17MIN: 3.51 / MAX: 4.17MIN: 3.1 / MAX: 4.17
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_lsbcd246810Min: 4.11 / Avg: 4.12 / Max: 4.12

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lsbcd0.92931.85862.78793.71724.6465SE +/- 0.00, N = 34.134.084.124.12MIN: 3.25 / MAX: 4.19MIN: 3.42 / MAX: 4.13MIN: 2.98 / MAX: 4.17MIN: 2.81 / MAX: 4.19
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lsbcd246810Min: 4.12 / Avg: 4.12 / Max: 4.13

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lsbcd0.9271.8542.7813.7084.635SE +/- 0.00, N = 34.104.124.124.11MIN: 2.87 / MAX: 4.15MIN: 3.39 / MAX: 4.17MIN: 2.97 / MAX: 4.17MIN: 2.87 / MAX: 4.18
OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lsbcd246810Min: 4.11 / Avg: 4.11 / Max: 4.12

Blender

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: BMW27 - Compute: CPU-Onlysbcd90180270360450SE +/- 0.10, N = 3417.28417.64416.74416.31
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: BMW27 - Compute: CPU-Onlysbcd70140210280350Min: 416.16 / Avg: 416.31 / Max: 416.49

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Classroom - Compute: CPU-Onlysbcd2004006008001000SE +/- 12.91, N = 41100.021103.331101.161113.84
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Classroom - Compute: CPU-Onlysbcd2004006008001000Min: 1098.07 / Avg: 1113.84 / Max: 1152.39

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Fishy Cat - Compute: CPU-Onlysbcd110220330440550SE +/- 0.85, N = 3528.21528.72528.01528.78
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Fishy Cat - Compute: CPU-Onlysbcd90180270360450Min: 527.17 / Avg: 528.78 / Max: 530.06

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: CPU-Onlysbcd30060090012001500SE +/- 1.37, N = 31401.881405.371401.131402.14
OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: CPU-Onlysbcd2004006008001000Min: 1400.18 / Avg: 1402.14 / Max: 1404.78