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.

HTML result view exported from: https://openbenchmarking.org/result/2311191-PTS-FS16700400&gru&sro.

fsProcessorMotherboardChipsetMemoryDiskGraphicsAudioNetworkOSKernelDesktopDisplay ServerOpenGLOpenCLVulkanCompilerFile-SystemScreen ResolutionsbcdIntel 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 11.4.0ext41920x1200OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseProcessor Details- Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xac - Thermald 2.4.9 Python Details- Python 3.10.12Security Details- 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

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

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-50bcds714212835SE +/- 0.45, N = 1330.1530.6224.7531.08MIN: 23.77 / MAX: 31.47MIN: 23.7 / MAX: 31.5MIN: 13.75 / MAX: 31.86MIN: 24.28 / MAX: 32.05

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 1 - Model: ResNet-152bcds3691215SE +/- 0.02, N = 39.9310.979.7911.51MIN: 5.85 / MAX: 12.52MIN: 9 / MAX: 12.55MIN: 7.71 / MAX: 9.95MIN: 9.43 / MAX: 12.68

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-50bcds48121620SE +/- 0.05, N = 313.7813.7813.8114.23MIN: 12.06 / MAX: 14.04MIN: 11.44 / MAX: 14MIN: 11.95 / MAX: 14.1MIN: 12.34 / MAX: 16.52

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-50bcds48121620SE +/- 0.10, N = 313.6513.7913.5313.86MIN: 11.36 / MAX: 13.96MIN: 12.26 / MAX: 13.98MIN: 7.72 / MAX: 13.95MIN: 12.24 / MAX: 14.1

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-50bcds48121620SE +/- 0.03, N = 313.7513.7913.7913.82MIN: 12.17 / MAX: 13.99MIN: 12.1 / MAX: 14.08MIN: 12.11 / MAX: 14.04MIN: 12.08 / MAX: 14.09

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 16 - Model: ResNet-152bcds1.26682.53363.80045.06726.334SE +/- 0.04, N = 35.635.625.585.49MIN: 5.35 / MAX: 5.71MIN: 5.35 / MAX: 5.69MIN: 4.32 / MAX: 5.7MIN: 4.9 / MAX: 5.6

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-50bcds48121620SE +/- 0.12, N = 313.7613.8113.6813.90MIN: 9.38 / MAX: 13.97MIN: 11.69 / MAX: 14.05MIN: 11.92 / MAX: 14.02MIN: 10.84 / MAX: 14.08

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 32 - Model: ResNet-152bcds1.26452.5293.79355.0586.3225SE +/- 0.01, N = 35.585.615.625.57MIN: 4.83 / MAX: 5.65MIN: 5.32 / MAX: 5.68MIN: 4.5 / MAX: 5.69MIN: 4.59 / MAX: 5.66

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-50

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-50bcds48121620SE +/- 0.02, N = 313.7413.8113.7713.83MIN: 12.06 / MAX: 13.95MIN: 12.27 / MAX: 14.04MIN: 7.55 / MAX: 14.1MIN: 12.12 / MAX: 14.03

PyTorch

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

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 64 - Model: ResNet-152bcds1.26452.5293.79355.0586.3225SE +/- 0.00, N = 35.615.615.625.54MIN: 5.34 / MAX: 5.67MIN: 5.32 / MAX: 5.68MIN: 5.31 / MAX: 5.71MIN: 5.28 / MAX: 5.59

PyTorch

Device: CPU - Batch Size: 256 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: ResNet-152bcds1.26452.5293.79355.0586.3225SE +/- 0.01, N = 35.605.595.625.55MIN: 4.17 / MAX: 5.67MIN: 5.31 / MAX: 5.66MIN: 5.19 / MAX: 5.7MIN: 4.7 / MAX: 5.67

PyTorch

Device: CPU - Batch Size: 512 - Model: ResNet-152

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: ResNet-152bcds1.26452.5293.79355.0586.3225SE +/- 0.01, N = 35.595.595.625.56MIN: 5.31 / MAX: 5.66MIN: 4.43 / MAX: 5.65MIN: 3.95 / MAX: 5.71MIN: 4.51 / MAX: 5.64

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_lbcds246810SE +/- 0.03, N = 37.327.367.337.37MIN: 5.07 / MAX: 7.42MIN: 6.88 / MAX: 7.43MIN: 5.29 / MAX: 7.45MIN: 5.71 / MAX: 7.46

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_lbcds0.92931.85862.78793.71724.6465SE +/- 0.00, N = 34.114.134.134.08MIN: 3.78 / MAX: 4.16MIN: 3.56 / MAX: 4.17MIN: 3.27 / MAX: 4.18MIN: 3.25 / MAX: 4.13

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_lbcds0.9271.8542.7813.7084.635SE +/- 0.00, N = 34.124.124.114.11MIN: 3.84 / MAX: 4.17MIN: 3.19 / MAX: 4.17MIN: 2.84 / MAX: 4.16MIN: 3.08 / MAX: 4.17

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_lbcds0.9271.8542.7813.7084.635SE +/- 0.00, N = 34.114.124.124.10MIN: 3.42 / MAX: 4.17MIN: 3.51 / MAX: 4.17MIN: 3.1 / MAX: 4.17MIN: 3.43 / MAX: 4.15

PyTorch

Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_lbcds0.92931.85862.78793.71724.6465SE +/- 0.00, N = 34.084.124.124.13MIN: 3.42 / MAX: 4.13MIN: 2.98 / MAX: 4.17MIN: 2.81 / MAX: 4.19MIN: 3.25 / MAX: 4.19

PyTorch

Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l

OpenBenchmarking.orgbatches/sec, More Is BetterPyTorch 2.1Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_lbcds0.9271.8542.7813.7084.635SE +/- 0.00, N = 34.124.124.114.10MIN: 3.39 / MAX: 4.17MIN: 2.97 / MAX: 4.17MIN: 2.87 / MAX: 4.18MIN: 2.87 / MAX: 4.15

Blender

Blend File: BMW27 - Compute: CPU-Only

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: BMW27 - Compute: CPU-Onlybcds90180270360450SE +/- 0.10, N = 3417.64416.74416.31417.28

Blender

Blend File: Classroom - Compute: CPU-Only

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Classroom - Compute: CPU-Onlybcds2004006008001000SE +/- 12.91, N = 41103.331101.161113.841100.02

Blender

Blend File: Fishy Cat - Compute: CPU-Only

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Fishy Cat - Compute: CPU-Onlybcds110220330440550SE +/- 0.85, N = 3528.72528.01528.78528.21

Blender

Blend File: Pabellon Barcelona - Compute: CPU-Only

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 4.0Blend File: Pabellon Barcelona - Compute: CPU-Onlybcds30060090012001500SE +/- 1.37, N = 31405.371401.131402.141401.88

Phoronix Test Suite v10.8.4