NIVIDA announced availability of the the Titan V card Friday December 8th. We had a couple in hand for testing on Monday December 11th, nice! I ran through many of the machine learning and simulation testing problems that I have done on Titan cards in the past. Results are not the near doubling in performance of past generations… but read on.
You got your new wonderful NVIDIA Pascal GPU … maybe a GTX 1080, 1070, or Titan X(P) … And, you want to setup a CUDA environment for some dev work or maybe try some “machine learning” code with your new card. What are you going to do? At the time of this writing CUDA 8 is still in RC and the deb and rpm packages have drivers that don’t work with Pascal. I’ll walk through the tricks you need to do a manual setup of CUDA 7.5 and 8.0 on top of Ubuntu 16.04 or 14.04 that will work with the new Pascal based GPU’s
I have a Titan Black, Titan X (Maxwell) and a new Titan X (Pascal) in a system for a quick CUDA performance test. Install is on Ubuntu 16.04 with CUDA 8.0rc. We’ll look at nbody from the CUDA samples code and NAMD Molecular Dynamics. It is stunning to see how much the CUDA performance has increased on these wonderful GPU’s in just 3 years.
The new NVIDIA GeForce GTX 1080 and GTX 1070 GPU’s are out and I’ve received a lot of questions about NAMD performance. The short answer is — performance is great! I’ve got some numbers to back that up below. We’ve got new Broadwell Xeon and Core-i7 CPU’s thrown into the mix too. The new hardware refresh gives a nice step up in performance.
Just got a NVIDIA GTX 1080 for testing. I hacked up an install with Ubuntu 16.04 and CUDA 7.5 along with a beta display driver that works! First run after compiling the cuda samples nbody gave 5816 GFLOP/s! A GTX 980 on the same system does 2572 GFLOP/s. However, it’s not all good news …
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!
Molecular Dynamics programs can achieve very good performance on modern GPU accelerated workstations giving job performance that was only achievable using CPU compute clusters only a few years ago. The group at UIUC working on NAMD were early pioneers of using GPU’s for compute acceleration and NAMD has very good performance acceleration using NVIDIA CUDA. We show you how good that performance is on modern Nvidia GPU’s
I have been butting heads with a particularly annoying bug that I hit frequently on installs since I work with systems that need to have kernel modules recompiled for CUDA and the Xeon Phi. I have it mostly figured out and have a fix in this post.
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.
Puget Systems builds custom PCs tailored for your workflow
Extensive in-house testing
making you more productive and giving you more performance for your dollar
Reliable workstations
with fewer crashes and blue screens means more time working, less time waiting on your computer
Support that understands
your complex workflows and can get you back up and running ASAP
Proven track record
check out our customer testimonials and Reseller Ratings
Select your workflow: