GPU and SoC specialist Nvidia has released the CUDA 6 parallel programming model. CUDA is a parallel computing platform and programming model that strives to increase in computing performance by harnessing the power of the graphics processing unit.
The CUDA 6 Release Candidate is packed with new features including Unified Memory to let CUDA applications access CPU and GPU memory, without the need to manually copy data from one to the other.
"This is a major time saver that simplifies the programming process, and makes it easier for programmers to add GPU acceleration in a wider range of applications," says the Nvidia programing team.
There are also Drop-in Libraries for developers who want to instantly accelerate an application by up to x8 times — the new drop-in libraries can automatically accelerate BLAS and FFTW calculations by simply replacing the existing CPU-only BLAS or FFTW library with the new, GPU-accelerated equivalent.
This news also encompasses Multi-GPU Scaling — Redesigned BLAS and FFT GPU libraries automatically scale performance across up to eight GPUs in a single node. This provides over nine teraflops of double-precision performance per node, supporting larger workloads than ever before (up to 512GB).
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.