NVIDIA CUDA 5 Release Candidate Now Available


Last Updated: August 16, 2012 8:29 pm GMT
(Santa Clara, California--August 16, 2012) NVIDIA today announced availability of the NVIDIA® CUDA® 5 Release Candidate, the latest version of the industry’s leading parallel computing platform and programming model.

Publicly available as a free download from the NVIDIA Developer Zone website, the CUDA 5 Release Candidate provides a solid platform for developers to evaluate a host of new features and capabilities before the CUDA 5 Production Release later this year.

CUDA 5 delivers advanced features and tools to make the development of GPU-accelerated applications faster and easier than ever. Highlights include GPU object linking, which allows developers to create libraries that run entirely on the GPU, and NVIDIA® Nsight™ Eclipse Edition, the world’s first integrated development environment (IDE) for developing GPU accelerated applications on Linux- and Mac OS-based systems. CUDA 5 also includes a new integrated documentation system and all-in-one installers that make it easier for developers to get started with parallel programming.

NVIDIA is also providing a number of CUDA 5 educational resources for developers, including a number of upcoming webinars:
· Introducing CUDA 5: Features and Benefits
Wednesday, August 22, 2012 | 10:00 – 10:30 a.m. PDT (GMT-7:00)

· Nsight Eclipse Edition: High Productivity IDE for CUDA Development on Linux & Mac OS
Tuesday, August 28, 2012 | 10:00 – 10:30 a.m. PDT (GMT-7:00)

· GPU Object Linking: Usage and Benefits
Wednesday, September 5, 2012 | 10:00 – 10:30 a.m. PDT (GMT-7:00)

CUDA Registered Developer Program
Parallel programmers are invited to join the CUDA Registered Developer Program for early access to software releases, tools, resources, and information to maximize the potential of CUDA and parallel computing. Visit http://www.nvidia.com/paralleldeveloper for more information.

About CUDA
CUDA is a parallel computing platform and programming model developed by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of GPUs.

More information about GPU Computing is available at the NVIDIA website. To learn more about CUDA or download the latest version, visit the CUDA website. You can also follow us on Twitter (@NVIDIATesla).


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