Example MATLAB code in GPULib

I recently had a question from a user looking for information on how to use GPULib with MATLAB; you can find examples of how to use GPULib in the

gpulib-0.3p7/MATLAB/ode_cell/

directory of the current distribution.

We're working on refining the MATLAB interface to the library, and hopefully we'll be able to share that work with you soon. In the meantime, if you have suggestions or comments about using GPULib with MATLAB, please let us know!

GPULib 0.3p7 released

Development continues on GPULib -- the team has made a new release; 0.3p7 can be downloaded at

http://www.txcorp.com/technologies/GPULib/

New version 0.3p6 available

Tech-X has just released a new version of GPULib. It is available from

http://www.txcorp.com/technologies/GPULib/download.php

Questions, comments, bug reports, and feature requests are welcome.

Nvidia's David Kirk on CUDA, CPUs and GPUs

bit-tech has a quite interesting interview up with Nvidia's Chief Scientist David Kirk, where he discusses the future of GPU computing.

http://www.bit-tech.net/hardware/2008/04/30/david-kirk-interview/1

Intel to build sGPU supercomputer: Nvidia Tesla cards to debut in Bull system

http://www.tgdaily.com/content/view/37070/135/

The original Bull NovaScale supercomputer setup was based on 1068 nodes, which will result in a total of 8544 processing cores for a peak floating point performance of 192 TFlops. Apparently the design was recently upgraded with 48 nodes of Nvidia Tesla S900 GPGPU cards with 96 (GT200) GPUs. The expected performance is now about 300 TFlops. In comparison, BlueGene/L, currently the world's most powerful supercomputer, peaks at 596 TFlops an uses 212,992 processing cores.

New version 0.3p1 available

A new version of GPULib (0.3p1) is available at

http://www.txcorp.com/technologies/GPULib/download.php


This new version contains a variety of bug fixes and minor updates. Please contact us if you run into any issues or have feature requests.

Technology preview version 0.3 released

Later today we will release the latest technology preview of the GPULib (version 0.3). This version now contains at least prototypes for all the language bindings (IDL, MATLAB, Python and Java) and many new functions (various collective operations, conditionals, random number generator and more) that should all make it easier to develop algorithms that can keep data on the GPU for as long as possible.

As the name suggests, this is neither a full version nor a full release, but it will give you the opportunity to play around with the library, see if your algorithm could take advantage of a GPU and provide us feedback on missing kernels/functions, surprises you've encountered during installation and use, and hopefully success stories.

We're looking forward to hear from your,

Peter