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
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results
Show Result Confidence Charts

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
Performance Per
Dollar
Date
Run
  Test
  Duration
s
November 18 2023
  2 Hours, 15 Minutes
b
November 18 2023
  2 Hours, 16 Minutes
c
November 18 2023
  2 Hours, 15 Minutes
d
November 18 2023
  7 Hours, 13 Minutes
Invert Hiding All Results Option
  3 Hours, 30 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):


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-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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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

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-Onlysbcd90180270360450SE +/- 0.10, N = 3417.28417.64416.74416.31

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: Fishy Cat - Compute: CPU-Onlysbcd110220330440550SE +/- 0.85, N = 3528.21528.72528.01528.78

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: CPU-Onlysbcd30060090012001500SE +/- 1.37, N = 31401.881405.371401.131402.14