NVIDIA Releases CUDA 5
NVIDIA today made available the NVIDIA CUDA 5 production release, a powerful new version of the world’s most pervasive parallel computing platform and programming model for accelerating scientific and engineering applications on GPUs. It can be downloaded for free from the NVIDIA Developer Zone website. The new programming features of the CUDA 5 platform make the development of GPU-accelerated applications faster and easier than ever, including support for dynamic parallelism, GPU-callable libraries, NVIDIA GPUDirect technology support for RDMA (remote direct memory access) and the NVIDIA Nsight Eclipse Edition integrated development environment (IDE).
New CUDA 5 Features:
CUDA 5 enables developers to take full advantage of the performance of NVIDIA GPUs, including GPU accelerators based on the NVIDIA Kepler compute architecture — the fastest, most efficient, highest-performance computing architecture ever built. Key features include:
- Dynamic Parallelism – Brings GPU acceleration to new algorithms
GPU threads can dynamically spawn new threads, allowing the GPU to adapt to the data. By minimizing the back and forth with the CPU, dynamic parallelism greatly simplifies parallel programming. And it enables GPU acceleration of a broader set of popular algorithms, such as those used in adaptive mesh refinement and computational fluid dynamics applications. - GPU-Callable Libraries – Enables third-party ecosystem
A new CUDA BLAS library allows developers to use dynamic parallelism for their own GPU-callable libraries. They can design plug-in APIs that allow other developers to extend the functionality of their kernels, and allow them to implement callbacks on the GPU to customize the functionality of third-party GPU-callable libraries. The “object linking” capability provides an efficient and familiar process for developing large GPU applications by enabling developers to compile multiple CUDA source files into separate object files, and link them into larger applications and libraries. - GPUDirect Support for RDMA – Minimizes system memory bottlenecks
GPUDirect technology enables direct communication between GPUs and other PCI-E devices, and supports direct memory access between network interface cards and the GPU. It also significantly reduces MPISendRecv latency between GPU nodes in a cluster and improves overall application performance.
- NVIDIA Nsight Eclipse Edition – Generate CUDA code quickly and easily
NVIDIA Nsight Eclipse Edition enables programmers to develop, debug and profile GPU applications within the familiar Eclipse-based IDE on Linux and Mac OS X platforms. An integrated CUDA editor and CUDA samples speed the generation of CUDA code, and automatic code refactoring enables easy porting of CPU loops to CUDA kernels. An integrated expert analysis system provides automated performance analysis and step-by-step guidance to fix performance bottlenecks in the code, while syntax highlighting makes it easy to differentiate GPU code from CPU code.
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