This is just a short post to announce a more usable version of the NVIDIA GPU powerlimit setup script that I released a few months ago. This update to version 0.2 uses an interactive mode to set GPU powerlimits and optionally setup a systemd unit file to set these limits on subsequent reboots.
NVIDIA GPU Power Limit vs Performance
This post presents testing data showing that power-limit reduction on NVIDIA GPUs have give significant benefits for both high wattage and lower wattage GPUs. Power-limit vs Performance data is presented for 1-4 A5000 and 1-4 RTX3090 GPUs.
NVIDIA GPU Powerlimit Systemd Setup Script
In this post I am referencing a Bash shell script I recently put together for setting up automatic NVIDIA GPU power-limit lowering at system boot. This allows a reliable way to configure and maintain multi-GPU systems for stable operation under heavy load.
RTX 2080Ti with NVLINK – TensorFlow Performance (Includes Comparison with GTX 1080Ti, RTX 2070, 2080, 2080Ti and Titan V)
More Machine Learning testing with TensorFlow on the NVIDIA RTX GPU’s. This post adds dual RTX 2080 Ti with NVLINK and the RTX 2070 along with the other testing I’ve recently done. Performance in TensorFlow with 2 RTX 2080 Ti’s is very good! Also, the NVLINK bridge with 2 RTX 2080 Ti’s gives a bidirectional bandwidth of nearly 100 GB/sec!
NVLINK on RTX 2080 TensorFlow and Peer-to-Peer Performance with Linux
NVLINK is one of the more interesting features of NVIDIA’s new RTX GPU’s. In this post I’ll take a look at the performance of NVLINK between 2 RTX 2080 GPU’s along with a comparison against single GPU I’ve recently done. The testing will be a simple look at the raw peer-to-peer data transfer performance and a couple of TensorFlow job runs with and without NVLINK.
NVIDIA RTX 2080 Ti vs 2080 vs 1080 Ti vs Titan V, TensorFlow Performance with CUDA 10.0
Are the NVIDIA RTX 2080 and 2080Ti good for machine learning?
Yes, they are great! The RTX 2080 Ti rivals the Titan V for performance with TensorFlow. The RTX 2080 seems to perform as well as the GTX 1080 Ti (although the RTX 2080 only has 8GB of memory). I’ve done some testing using **TensorFlow 1.10** built against **CUDA 10.0** running on **Ubuntu 18.04** with the **NVIDIA 410.48 driver**.