NVIDIA GTC 2023 was outstanding! To say that about a virtual conference tells you how much I value it. This post is largely a catalog of the talks I found interesting along with titles that I think will be interesting to a larger audience and my colleagues at Puget Systems.
WSL2 offers improved performance over version 1 by providing more direct access to the host hardware drivers. Recent “Insider Dev Channel” builds of Win10 even allows access to the Windows NVIDIA display driver for GPU computing applications for WSL2 Linux applications! The performance improvements with WSL2 are largely because this version is running as a privileged virtual machine on to of MS Hyper-V. This means that at least low level support for the Hyper-V virtualization layer needs to be enabled to use it. In particular, the Windows feature “VirtualMachinePlatform” must be enabled for WSL2. We tested to see if there was any negative application performance impact.
NVIDIA has just launched the GTX 980 Ti and I got to run some benchmarks on one. How is the Linux CUDA performance? Almost as good as the TitanX! This is another great card from NVIDIA for single precision compute loads. We’ve got some number to show it.
Another great GTC meeting. NVIDIA does this right! The most interesting aspects for me this year were the talks on “Deep Learning” (Artificial Neural Networks) and OpenPOWER. I have some observations and links to recordings of the keynotes and talks. Enjoy!
Modern high-end laptops can be treated as desktop system replacements so it’s expected that people will want to try to do some serious computing on them. Doing GPU accelerated computing on a laptop is possible and performance can be surprisingly good with a high-end NVIDIA GPU. [I’m looking at GTX 980m and 970m ]. However, first you have to get it to work! Optimus technology can present serious problems to someone who wants to run a Linux based CUDA laptop computing platform. Read on to see what worked.
I’m going to walk you through a basic install and configuration for a development system to do CUDA and OpenACC GPU programming. This is not a detailed howto but if you have some linux admin skills it will be a reasonable guide to get you started. We’ll do a basic NVIDIA GPU programming setup including CentOS 6.5, CUDA development environment and a PGI compiler setup with OpenACC. The most interesting part may be the OpenACC setup. OpenACC is a relatively new option for GPU programming and allows for a directive (pragma) based coding model.
I had the pleasure of attending the NVIDIA Graphics Technology Conference ( GTC ) last week. Wonderful conference! If you have any doubts about the quality of the conference you are in luck. They have most of the content on-line, you can check it out yourself …
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