Cuda 6

Nvidia has announced Cuda 6, the latest version of its parallel programming language, designed for programming GPUs to accelerate applications by replacing existing CPU-based libraries.

Unified Memory is a new feature introduced with Cuda 6 which aims to simplify programming by enabling applications to access CPU and GPU memory without copying data from one to the other. This enables easier support for GPU acceleration in a range of programming languages, Nvidia claims.

Drop-in libraries have also been added which accelerates applications' BLAS and FFTW calculations by up to 8x by simply replacing the existing CPU libraries with the GPU accelerated equivalents.

Multi-GPU scaling is also now available. Re-designed BLAS and FFT GPU libraries automatically scale performance across up to eight GPUs in a single node, delivering more than nine teraflops of double precision performance per node, and supporting larger workloads than ever before (up to 512GB). In addition to this Multi-GPU scaling compatability has been added for the new BLAS drop-in library.

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.


For functionality and security for externalised research, software providers have turned to the cloud, writes Sophia Ktori


Robert Roe looks at the latest simulation techniques used in the design of industrial and commercial vehicles


Robert Roe investigates the growth in cloud technology which is being driven by scientific, engineering and HPC workflows through application specific hardware


Robert Roe learns that the NASA advanced supercomputing division (NAS) is optimising energy efficiency and water usage to maximise the facility’s potential to deliver computing services to its user community


Robert Roe investigates the use of technologies in HPC that could help shape the design of future supercomputers