somervillePyTorchFULL
AMD Ryzen 9 9950X 16-Core testing with a ASUS PRIME B650M-A II (3201 BIOS) and Gigabyte NVIDIA GeForce RTX 2070 SUPER 8GB on Ubuntu 24.04 via the Phoronix Test Suite.


run1: 

	Processor: AMD Ryzen 9 9950X 16-Core @ 5.75GHz (16 Cores / 32 Threads), Motherboard: ASUS PRIME B650M-A II (3201 BIOS), Chipset: AMD Device 14d8, Memory: 4 x 48GB DDR5-3600MT/s G Skill F5-6800J3446F48G, Disk: 2000GB Samsung SSD 980 PRO 2TB, Graphics: Gigabyte NVIDIA GeForce RTX 2070 SUPER 8GB, Audio: NVIDIA TU104 HD Audio, Monitor: VS2447 100Hz, Network: 2 x Intel 10-Gigabit X540-AT2 + Realtek RTL8125 2.5GbE

	OS: Ubuntu 24.04, Kernel: 6.8.0-51-generic (x86_64), Display Server: X Server 1.21.1.11, Display Driver: NVIDIA, OpenCL: OpenCL 3.0 CUDA 12.4.131, Compiler: GCC 13.3.0 + CUDA 12.4, File-System: ext4, Screen Resolution: 1920x1080


PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 12.42 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 12.69 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 12.64 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 12.66 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 12.65 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 21.20 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 21.07 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 512 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 21.21 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 256 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 21.28 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 21.26 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 16.23 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 256 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 52.01 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 29.44 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 512 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 50.91 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 64 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 52.46 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 32 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 52.01 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 16 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 53.13 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 58.24 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 58.27 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 58.30 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 58.26 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 58.38 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 85.67 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 85.82 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 85.97 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 85.68 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 85.85 |=================================================================


PyTorch 2.2.1
Device: CPU - Batch Size: 1 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 73.77 |=================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
run1 . 104.20 |================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 207.52 |================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 208.44 |================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 208.57 |================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 208.83 |================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 207.79 |================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
run1 . 131.72 |================================================================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50
batches/sec > Higher Is Better
run1 . 325.51 |================================================================