test-pytorch Intel Xeon E5-2680 v4 testing with a MACHINIST X99-MR9A PRO MAX (5.11 BIOS) and NVIDIA GeForce RTX 3060 12GB on Ubuntu 22.04 via the Phoronix Test Suite. teste-total: Processor: Intel Xeon E5-2680 v4 @ 3.30GHz (14 Cores / 28 Threads), Motherboard: MACHINIST X99-MR9A PRO MAX (5.11 BIOS), Chipset: Intel Xeon E7 v4/Xeon, Memory: 32GB, Disk: 500GB KINGSTON SNV2S500G + 160GB MAXTOR STM316021 + 512GB P3-512, Graphics: NVIDIA GeForce RTX 3060 12GB, Audio: Realtek ALC897, Monitor: TV-PHILCO, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 22.04, Kernel: 6.5.0-28-generic (x86_64), Desktop: GNOME Shell 42.9, Display Server: X Server 1.21.1.4, Display Driver: NVIDIA 535.171.04, Compiler: GCC 11.4.0, File-System: ext4, Screen Resolution: 1920x1080 PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 29.09 |========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 11.29 |========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 20.75 |========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 20.96 |========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 21.07 |========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 8.80 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 20.86 |========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 8.81 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 21.04 |========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 8.85 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 8.86 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 8.70 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 6.66 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 4.98 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 4.96 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 5.05 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 5.00 |=========================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 4.92 |=========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 102.30 |========================================================= PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 36.32 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 99.64 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 99.91 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 99.62 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 35.53 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 100.18 |========================================================= PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 35.53 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50 batches/sec > Higher Is Better teste-total . 100.21 |========================================================= PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 35.40 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 35.16 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152 batches/sec > Higher Is Better teste-total . 35.50 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 18.22 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 17.79 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 17.87 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 17.96 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 17.87 |========================================================== PyTorch 2.2.1 Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l batches/sec > Higher Is Better teste-total . 18.05 |==========================================================