Nvidia to Port CUDA Directly onto x86 Processors

At the GPU Technology Conference, Nvidia said it would port its CUDA programming language directly to x86 chips.

Chipmaker Nvidia's CEO Jen-Hsun Huang announced during his GPU Technology Conference keynote that the company would be bringing its Compute Unified Device Architecture programming language directly to x86 chips. CUDA is the computing engine in Nvidia GPUs (graphics processing units) that is accessible to software developers through variants of industry standard programming languages. Huang said a timetable isn't yet set, according to the technology blog Electronista.

In addition, the Wall Street Journal reported Huang said its next GPU, codenamed Kepler, would debut in late 2011 and be three or four times more powerful than Fermi, which debuted in April, without a great increase in power consumption. "There are hundreds of engineers working on it," the Journal reported him saying.

The company also announced the addition of research and educational centers dedicated to leveraging the processing power of GPUs to address today's computing issues. CUDA Research Centers are recognized institutions that embrace and utilize GPU computing across multiple research fields. CUDA Teaching Centers are institutions that have integrated GPU computing techniques into their mainstream computer programming curriculum. Existing CUDA Research Centers include Johns Hopkins University, California Polytechnic State University and others; among the new centers are locations at University of California at Los Angeles and HP Labs.

Launched in June, the CUDA Research Center program fosters collaboration with research groups at universities and research institutes that are expanding the frontier of massively parallel computing. Among the benefits are events with researchers and academics, a designated Nvidia technical liaison and access to specialized online and in-person training sessions.

"The addition of these new educational programs underscores the tremendous interest in harnessing the power of GPUs to solve a today's most pressing computing challenges," said Sanford Russell, general manager of CUDA and GPU computing at Nvidia. "There are more than 350 universities worldwide teaching the CUDA programming model within their curriculum, and more than 100,000 programmers actively developing applications that use the GPU. With the addition of these new programs, we expect to see even broader interest and adoption of GPU computing practices across a wide variety of industries worldwide."

Earlier this year, the company unveiled the new series of GeForce 400M GPUs, which Nvidia just unveiled, and includes the GeForce GTX 470M and GTX 460M for enthusiast users and the GeForce GT 445M, GT 435M, GT 425M, GT 420M and GT 415M for performance users. The GeForce 400M Series is also able to deliver stereoscopic 3D images when configured with Nvidia 3D Vision glasses and a 3D display. 3D Vision supports an array of 3D content, including more than 425 games, Blu-ray 3D movies, photos and streaming Web video.

Notebook models featuring the GeForce 400M series and the 3D Vision glasses will be available soon after launch, according to a company release, including the Acer Aspire 5745DG with GeForce GT 425M and the Asus G53Jw with GeForce GTX 460M. In addition, by including support for Nvidia's 3DTV Play technology, users can attach their notebook to a 3D TV and play content that way.

The announcement comes at a time when the company is struggling against competitors such as AMD and Intel. In the second quarter, the GPU maker saw double-digit losses across every segment except for notebooks, where the company grew shipments 10 percent over the first quarter. Nvidia officials announced July 28 that they expect revenues in their fiscal second quarter, which ends July 31, to come in at $800 million to $820 million, down from an earlier projection of $950 million to $970 million.