gpu-server-eu-report
AMD Ryzen Threadripper PRO 5955WX 16-Cores testing with a ASUS Pro WS WRX80E-SAGE SE WIFI II (1302 BIOS) and Gigabyte NVIDIA GeForce RTX 4090 24GB on Ubuntu 22.04 via the Phoronix Test Suite.


AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte: 

	Processor: AMD Ryzen Threadripper PRO 5955WX 16-Cores @ 4.00GHz (16 Cores / 32 Threads), Motherboard: ASUS Pro WS WRX80E-SAGE SE WIFI II (1302 BIOS), Chipset: AMD Starship/Matisse, Memory: 256GB, Disk: 4001GB Western Digital WD_BLACK SN850X 4000GB, Graphics: Gigabyte NVIDIA GeForce RTX 4090 24GB, Audio: NVIDIA Device 22ba, Network: 2 x Intel 10G X550T + Intel Wi-Fi 6 AX210/AX211/AX411

	OS: Ubuntu 22.04, Kernel: 6.5.0-26-generic (x86_64), Desktop: GNOME Shell 42.9, Display Server: X Server 1.21.1.4, Display Driver: NVIDIA, Compiler: GCC 11.4.0, File-System: ext4, Screen Resolution: 800x600


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-50
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 214.60 |===============


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: ResNet-152
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 74.76 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-50
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 213.53 |===============


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-50
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 212.31 |===============


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-50
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 213.68 |===============


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: ResNet-152
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 75.20 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-50
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 213.57 |===============


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: ResNet-152
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 74.44 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-50
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 211.68 |===============


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: ResNet-152
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 75.22 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: ResNet-152
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 75.13 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: ResNet-152
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 74.93 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 1 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 38.73 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 16 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 38.12 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 32 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 38.01 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 64 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 37.76 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 256 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 38.08 |================


PyTorch 2.2.1
Device: NVIDIA CUDA GPU - Batch Size: 512 - Model: Efficientnet_v2_l
batches/sec > Higher Is Better
AMD Ryzen Threadripper PRO 5955WX 16-Cores - Gigabyte . 38.27 |================