If you are happy to use Ubuntu 14.04 LTS (Ubuntu-MATE in our case) then setting up a system with the NVIDIA DIGITS software stack is simple. I’ll give you some guidance on getting everything working, from the Linux install to the DIGITS web interface.
A brief description of graphics driver Timeout Detection and Recovery, why it can be problematic for intensive GPU codes, and how to work around it so that Windows can be a viable GPU computing platform.
I was preparing a Puget Systems Traverse Skylake based laptop for GPU accelerated molecular dynamics demos at the upcoming ACS meeting and decided to see if I could get Ubuntu 16.04 beta working with NVIDIA CUDA 7.5. It worked!
Machine Learning is getting a lot of attention these days and with good reason. There are mountains of data to work with and computing resources to handle the problems are easily attainable. Even a single GPU accelerated workstation is capable of serious work.
NVIDIA and PGI are offering “PGI Accelerator with OpenACC” free to academia (or 90 day trial for commercial users) under the banner “NVIDIA OpenACC Toolkit”. It’s about time!
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.
Fedora 22 is full of new goodness like kernel 4.0 and gcc 5.1 and yes, you can install and run CUDA on it! It’s not officially supported but I did manage to get it working!
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.
The next 18 months are going to see more shakeup and factioning in the computing world than we have seen in over a decade. Intel is pulling more and more of the compute architecture onto a single piece of silicon and tightly integrating the whole hardware stack. That’s good and bad. It may let them achieve better performance. However, this is going to leave users with a choice of “all Intel” or something else entirely. And, the “something else” is starting to seriously take shape.
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