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.