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 fs - Phoronix Test Suite 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&sro&gru .
fs Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL OpenCL Vulkan Compiler File-System Screen Resolution s b c d Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads) Dell 0DXP1F (3.7.0 BIOS) Intel Tiger Lake-LP 16GB Micron 2300 NVMe 512GB Intel Xe TGL GT2 15GB (1350MHz) Realtek ALC289 Intel Wi-Fi 6 AX201 Ubuntu 22.04 6.2.0-36-generic (x86_64) GNOME Shell 42.2 X Server + Wayland 4.6 Mesa 22.0.1 OpenCL 3.0 1.3.204 GCC 11.4.0 ext4 1920x1200 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Processor Details - Scaling Governor: intel_pstate powersave (EPP: balance_performance) - CPU Microcode: 0xac - Thermald 2.4.9 Python Details - Python 3.10.12 Security 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
fs pytorch: CPU - 1 - ResNet-50 pytorch: CPU - 1 - ResNet-152 pytorch: CPU - 16 - ResNet-50 pytorch: CPU - 32 - ResNet-50 pytorch: CPU - 64 - ResNet-50 pytorch: CPU - 16 - ResNet-152 pytorch: CPU - 256 - ResNet-50 pytorch: CPU - 32 - ResNet-152 pytorch: CPU - 512 - ResNet-50 pytorch: CPU - 64 - ResNet-152 pytorch: CPU - 256 - ResNet-152 pytorch: CPU - 512 - ResNet-152 pytorch: CPU - 1 - Efficientnet_v2_l pytorch: CPU - 16 - Efficientnet_v2_l pytorch: CPU - 32 - Efficientnet_v2_l pytorch: CPU - 64 - Efficientnet_v2_l pytorch: CPU - 256 - Efficientnet_v2_l pytorch: CPU - 512 - Efficientnet_v2_l blender: BMW27 - CPU-Only blender: Classroom - CPU-Only blender: Fishy Cat - CPU-Only blender: Pabellon Barcelona - CPU-Only s b c d 31.08 11.51 14.23 13.86 13.82 5.49 13.90 5.57 13.83 5.54 5.55 5.56 7.37 4.08 4.11 4.10 4.13 4.10 417.28 1100.02 528.21 1401.88 30.15 9.93 13.78 13.65 13.75 5.63 13.76 5.58 13.74 5.61 5.60 5.59 7.32 4.11 4.12 4.11 4.08 4.12 417.64 1103.33 528.72 1405.37 30.62 10.97 13.78 13.79 13.79 5.62 13.81 5.61 13.81 5.61 5.59 5.59 7.36 4.13 4.12 4.12 4.12 4.12 416.74 1101.16 528.01 1401.13 24.75 9.79 13.81 13.53 13.79 5.58 13.68 5.62 13.77 5.62 5.62 5.62 7.33 4.13 4.11 4.12 4.12 4.11 416.31 1113.84 528.78 1402.14 OpenBenchmarking.org
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 b c d s 7 14 21 28 35 SE +/- 0.45, N = 13 30.15 30.62 24.75 31.08 MIN: 23.77 / MAX: 31.47 MIN: 23.7 / MAX: 31.5 MIN: 13.75 / MAX: 31.86 MIN: 24.28 / MAX: 32.05
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 b c d s 3 6 9 12 15 SE +/- 0.02, N = 3 9.93 10.97 9.79 11.51 MIN: 5.85 / MAX: 12.52 MIN: 9 / MAX: 12.55 MIN: 7.71 / MAX: 9.95 MIN: 9.43 / MAX: 12.68
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 b c d s 4 8 12 16 20 SE +/- 0.05, N = 3 13.78 13.78 13.81 14.23 MIN: 12.06 / MAX: 14.04 MIN: 11.44 / MAX: 14 MIN: 11.95 / MAX: 14.1 MIN: 12.34 / MAX: 16.52
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 b c d s 4 8 12 16 20 SE +/- 0.10, N = 3 13.65 13.79 13.53 13.86 MIN: 11.36 / MAX: 13.96 MIN: 12.26 / MAX: 13.98 MIN: 7.72 / MAX: 13.95 MIN: 12.24 / MAX: 14.1
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 b c d s 4 8 12 16 20 SE +/- 0.03, N = 3 13.75 13.79 13.79 13.82 MIN: 12.17 / MAX: 13.99 MIN: 12.1 / MAX: 14.08 MIN: 12.11 / MAX: 14.04 MIN: 12.08 / MAX: 14.09
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 b c d s 1.2668 2.5336 3.8004 5.0672 6.334 SE +/- 0.04, N = 3 5.63 5.62 5.58 5.49 MIN: 5.35 / MAX: 5.71 MIN: 5.35 / MAX: 5.69 MIN: 4.32 / MAX: 5.7 MIN: 4.9 / MAX: 5.6
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 b c d s 4 8 12 16 20 SE +/- 0.12, N = 3 13.76 13.81 13.68 13.90 MIN: 9.38 / MAX: 13.97 MIN: 11.69 / MAX: 14.05 MIN: 11.92 / MAX: 14.02 MIN: 10.84 / MAX: 14.08
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 b c d s 1.2645 2.529 3.7935 5.058 6.3225 SE +/- 0.01, N = 3 5.58 5.61 5.62 5.57 MIN: 4.83 / MAX: 5.65 MIN: 5.32 / MAX: 5.68 MIN: 4.5 / MAX: 5.69 MIN: 4.59 / MAX: 5.66
PyTorch Device: CPU - Batch Size: 512 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 b c d s 4 8 12 16 20 SE +/- 0.02, N = 3 13.74 13.81 13.77 13.83 MIN: 12.06 / MAX: 13.95 MIN: 12.27 / MAX: 14.04 MIN: 7.55 / MAX: 14.1 MIN: 12.12 / MAX: 14.03
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 b c d s 1.2645 2.529 3.7935 5.058 6.3225 SE +/- 0.00, N = 3 5.61 5.61 5.62 5.54 MIN: 5.34 / MAX: 5.67 MIN: 5.32 / MAX: 5.68 MIN: 5.31 / MAX: 5.71 MIN: 5.28 / MAX: 5.59
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 b c d s 1.2645 2.529 3.7935 5.058 6.3225 SE +/- 0.01, N = 3 5.60 5.59 5.62 5.55 MIN: 4.17 / MAX: 5.67 MIN: 5.31 / MAX: 5.66 MIN: 5.19 / MAX: 5.7 MIN: 4.7 / MAX: 5.67
PyTorch Device: CPU - Batch Size: 512 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-152 b c d s 1.2645 2.529 3.7935 5.058 6.3225 SE +/- 0.01, N = 3 5.59 5.59 5.62 5.56 MIN: 5.31 / MAX: 5.66 MIN: 4.43 / MAX: 5.65 MIN: 3.95 / MAX: 5.71 MIN: 4.51 / MAX: 5.64
PyTorch Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l b c d s 2 4 6 8 10 SE +/- 0.03, N = 3 7.32 7.36 7.33 7.37 MIN: 5.07 / MAX: 7.42 MIN: 6.88 / MAX: 7.43 MIN: 5.29 / MAX: 7.45 MIN: 5.71 / MAX: 7.46
PyTorch Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l b c d s 0.9293 1.8586 2.7879 3.7172 4.6465 SE +/- 0.00, N = 3 4.11 4.13 4.13 4.08 MIN: 3.78 / MAX: 4.16 MIN: 3.56 / MAX: 4.17 MIN: 3.27 / MAX: 4.18 MIN: 3.25 / MAX: 4.13
PyTorch Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l b c d s 0.927 1.854 2.781 3.708 4.635 SE +/- 0.00, N = 3 4.12 4.12 4.11 4.11 MIN: 3.84 / MAX: 4.17 MIN: 3.19 / MAX: 4.17 MIN: 2.84 / MAX: 4.16 MIN: 3.08 / MAX: 4.17
PyTorch Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l b c d s 0.927 1.854 2.781 3.708 4.635 SE +/- 0.00, N = 3 4.11 4.12 4.12 4.10 MIN: 3.42 / MAX: 4.17 MIN: 3.51 / MAX: 4.17 MIN: 3.1 / MAX: 4.17 MIN: 3.43 / MAX: 4.15
PyTorch Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l b c d s 0.9293 1.8586 2.7879 3.7172 4.6465 SE +/- 0.00, N = 3 4.08 4.12 4.12 4.13 MIN: 3.42 / MAX: 4.13 MIN: 2.98 / MAX: 4.17 MIN: 2.81 / MAX: 4.19 MIN: 3.25 / MAX: 4.19
PyTorch Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l b c d s 0.927 1.854 2.781 3.708 4.635 SE +/- 0.00, N = 3 4.12 4.12 4.11 4.10 MIN: 3.39 / MAX: 4.17 MIN: 2.97 / MAX: 4.17 MIN: 2.87 / MAX: 4.18 MIN: 2.87 / MAX: 4.15
Blender Blend File: BMW27 - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.0 Blend File: BMW27 - Compute: CPU-Only b c d s 90 180 270 360 450 SE +/- 0.10, N = 3 417.64 416.74 416.31 417.28
Blender Blend File: Classroom - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.0 Blend File: Classroom - Compute: CPU-Only b c d s 200 400 600 800 1000 SE +/- 12.91, N = 4 1103.33 1101.16 1113.84 1100.02
Blender Blend File: Fishy Cat - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.0 Blend File: Fishy Cat - Compute: CPU-Only b c d s 110 220 330 440 550 SE +/- 0.85, N = 3 528.72 528.01 528.78 528.21
Blender Blend File: Pabellon Barcelona - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.0 Blend File: Pabellon Barcelona - Compute: CPU-Only b c d s 300 600 900 1200 1500 SE +/- 1.37, N = 3 1405.37 1401.13 1402.14 1401.88
Phoronix Test Suite v10.8.4