Dell’s Dr. Jeff Layton writes about the need for flexibility in the evolution of GPU applications and systems: “In my interactions with a great number of HPC customers, I’ve found one thing to be true: writing code for GPUs is an evolutionary process. Actually writing any code follows an evolutionary process, but it is more pronounced with GPU applications because small changes can have a...

Oak Ridge National Laboratory, one of the big supercomputer centers funded by the US Department of Energy, has tapped Cray to build a monster cluster that will weigh in at 20 petaflops when it is completed next year.

In this video, Andy Shue from the University of Illinois presents an overview of the programming resources available at gpucomputing.net.

Stanford University will soon power up a new GPU-powered supercomputer for computational biology. Developed in partnership with Scalable Informatics and Xtreme Compute Technologies, the system will comprise 100 Tesla C2050 GPUs in a heterogeneous cluster to be dubbed “numbercruncher”.