pytorch 2.2.1 ryzen AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS) and NVIDIA GeForce RTX 3080 10GB on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS), Chipset: AMD Device 14d8, Memory: 2 x 16GB DRAM-6000MT/s G Skill F5-6000J3038F16G, Disk: 2000GB Samsung SSD 980 PRO 2TB + 123GB SanDisk 3.2Gen1, Graphics: NVIDIA GeForce RTX 3080 10GB, Audio: NVIDIA GA102 HD Audio, Monitor: DELL U2723QE, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 OS: Ubuntu 23.10, Kernel: 6.7.0-060700-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7, Display Driver: NVIDIA 550.54.14, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 12.4.89, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160 b: Processor: AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS), Chipset: AMD Device 14d8, Memory: 2 x 16GB DRAM-6000MT/s G Skill F5-6000J3038F16G, Disk: 2000GB Samsung SSD 980 PRO 2TB + 123GB SanDisk 3.2Gen1, Graphics: NVIDIA GeForce RTX 3080 10GB, Audio: NVIDIA GA102 HD Audio, Monitor: DELL U2723QE, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 OS: Ubuntu 23.10, Kernel: 6.7.0-060700-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7, Display Driver: NVIDIA 550.54.14, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 12.4.89, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160 c: Processor: AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS), Chipset: AMD Device 14d8, Memory: 2 x 16GB DRAM-6000MT/s G Skill F5-6000J3038F16G, Disk: 2000GB Samsung SSD 980 PRO 2TB + 123GB SanDisk 3.2Gen1, Graphics: NVIDIA GeForce RTX 3080 10GB, Audio: NVIDIA GA102 HD Audio, Monitor: DELL U2723QE, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 OS: Ubuntu 23.10, Kernel: 6.7.0-060700-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7, Display Driver: NVIDIA 550.54.14, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 12.4.89, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160 d: Processor: AMD Ryzen 9 7950X 16-Core @ 5.88GHz (16 Cores / 32 Threads), Motherboard: ASUS ROG STRIX X670E-E GAMING WIFI (1905 BIOS), Chipset: AMD Device 14d8, Memory: 2 x 16GB DRAM-6000MT/s G Skill F5-6000J3038F16G, Disk: 2000GB Samsung SSD 980 PRO 2TB + 123GB SanDisk 3.2Gen1, Graphics: NVIDIA GeForce RTX 3080 10GB, Audio: NVIDIA GA102 HD Audio, Monitor: DELL U2723QE, Network: Intel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411 OS: Ubuntu 23.10, Kernel: 6.7.0-060700-generic (x86_64), Desktop: GNOME Shell 45.2, Display Server: X Server 1.21.1.7, Display Driver: NVIDIA 550.54.14, OpenGL: 4.6.0, OpenCL: OpenCL 3.0 CUDA 12.4.89, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160 PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better a . 72.75 |==================================================================== b . 72.66 |==================================================================== c . 72.25 |==================================================================== d . 71.23 |=================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better a . 30.33 |==================================================================== b . 29.81 |=================================================================== c . 29.32 |================================================================== d . 28.96 |================================================================= PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 batches/sec > Higher Is Better a . 49.18 |=================================================================== b . 48.67 |=================================================================== c . 49.73 |==================================================================== d . 47.61 |================================================================= PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 batches/sec > Higher Is Better a . 48.64 |=================================================================== b . 49.02 |==================================================================== c . 48.85 |==================================================================== d . 48.34 |=================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 batches/sec > Higher Is Better a . 48.19 |==================================================================== b . 47.97 |=================================================================== c . 48.52 |==================================================================== d . 48.51 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better a . 20.10 |==================================================================== b . 20.01 |=================================================================== c . 20.16 |==================================================================== d . 20.18 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 batches/sec > Higher Is Better a . 48.89 |==================================================================== b . 47.49 |================================================================== c . 48.61 |==================================================================== d . 48.38 |=================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 batches/sec > Higher Is Better a . 19.81 |================================================================== b . 20.26 |==================================================================== c . 20.06 |=================================================================== d . 20.24 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 batches/sec > Higher Is Better a . 48.44 |=================================================================== b . 48.83 |=================================================================== c . 49.32 |==================================================================== d . 48.19 |================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 batches/sec > Higher Is Better a . 20.30 |==================================================================== b . 19.64 |================================================================== c . 20.06 |=================================================================== d . 20.14 |=================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 batches/sec > Higher Is Better a . 20.54 |==================================================================== b . 19.91 |================================================================== c . 19.79 |================================================================== d . 19.75 |================================================================= PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: ResNet-152 batches/sec > Higher Is Better a . 19.40 |================================================================== b . 19.69 |=================================================================== c . 19.98 |==================================================================== d . 19.93 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 16.55 |==================================================================== b . 16.09 |================================================================== c . 15.77 |================================================================= d . 16.22 |=================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 11.79 |==================================================================== b . 11.77 |==================================================================== c . 11.62 |=================================================================== d . 11.84 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 11.42 |================================================================== b . 11.73 |==================================================================== c . 11.78 |==================================================================== d . 11.73 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 11.80 |==================================================================== b . 11.87 |==================================================================== c . 11.59 |================================================================== d . 11.88 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 11.70 |==================================================================== b . 11.78 |==================================================================== c . 11.75 |==================================================================== d . 11.74 |==================================================================== PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 11.76 |==================================================================== b . 11.67 |=================================================================== c . 11.56 |=================================================================== d . 11.76 |====================================================================