SANTA CLARA, CA -- NVIDIA today announced NVIDIA® CUDA® 6, the latest version of the world's most pervasive parallel computing platform and programming model.
The CUDA 6 platform makes parallel programming easier than ever, enabling software developers to dramatically decrease the time and effort required to accelerate their scientific, engineering, enterprise and other applications with GPUs.
It offers new performance enhancements that enable developers to instantly accelerate applications up to 8X by simply replacing existing CPU-based libraries. Key features of CUDA 6 include:
"By automatically handling data management, Unified Memory enables us to quickly prototype kernels running on the GPU and reduces code complexity, cutting development time by up to 50 percent," said Rob Hoekstra, manager of Scalable Algorithms Department at Sandia National Laboratories. "Having this capability will be very useful as we determine future programming model choices and port more sophisticated, larger codes to GPUs."
"Our technologies have helped major studios, game developers and animators create visually stunning 3D animations and effects," said Paul Doyle, CEO at Fabric Engine, Inc. "They have been urging us to add support for acceleration on NVIDIA GPUs, but memory management proved too difficult a challenge when dealing with the complex use cases in production. With Unified Memory, this is handled automatically, allowing the Fabric compiler to target NVIDIA GPUs and enabling our customers to run their applications up to 10X faster."
In addition to the new features, the CUDA 6 platform offers a full suite of programming tools, GPU-accelerated math libraries, documentation and programming guides.
Version 6 of the CUDA Toolkit is expected to be available in early 2014. Members of the CUDA-GPU Computing Registered Developer Program will be notified when it is available for download. To join the program, register here.
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. With more than two million downloads, supporting more than 240 leading engineering, scientific and commercial applications, the CUDA programming model is taught in over 700 universities and institutions worldwide and is the most popular way for developers to take advantage of GPU-accelerated computing.
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