28Feb/11Off

CUDA 4.0 RC Announced

by Dan

Today NVIDIA announced that on March 4th they will be releasing a CUDA 4.0 release candidate to those in their registered developer program. With this release, NVIDIA has endeavored to simplify programming with CUDA, especially in the area of multi-GPU designs. The new capabilities this version introduces drastically simplify the task of writing a general purpose, multi-GPU library, and we’re happy to say that we’ll be benefiting from these new features in our next release.

You can read more about the new version at NVIDIA’s press center.

7Oct/10Off

GPU Computing in Matlab

by John

One of the big announcements at GTC was Matlab's integrated GPU computing toolbox and this generated considerable buzz. And one of the questions we receive most often is regarding the potential for Matlab to experience speedups from GPU computing. Matlab is one of those great products in terms of usability but the most common complaint is that it's too slow, so GPUs are an obvious fit here. Our friends over at Accelereyes have put together a nice summary on the state of GPU computing in Matlab, and we wanted to share that. For the advanced CULA and Matlab users out there, it is also worth checking out our recent blog series where we describe the process of manually integrating CULA routines into Matlab code.

30Sep/10Off

A Year of Accomplishments

by Dan

With GTC2010 wrapped up and with today being the 1 year anniversary of the CULA launch, we the CULA team wanted to reflect on a year of accomplishments. We've constantly improved CULA over this time not only in features and performance but we've also worked hard to make CULA easier to get and use. We've announced partnerships with several awesome vendors who've integrated CULA into their products and others who are distributing CULA to an increasingly wide net of users.

We've got even bigger plans in this coming year, some of which have been announced and some that haven't! Look forward to CULA 2.2 for the realization of these plans, but in the meantime, enjoy reading about some of the highlights of this past year.

Improvements

More Performance [1], [2], [3], [4].
Fermi Support
Using CULA in Matlab
PyCULA
Website Redesign

Partnerships

Accelereyes
The Portland Group
University of Delaware
PSSC Labs

Education

Training
GPU Gems 2