John R. Nickolls

Scalable Parallel Programming with CUDA

Presents a collection of slides covering the following topics: CUDA parallel programming model; CUDA toolkit and libraries; performance optimization; and application development.

NVIDIA Tesla: A Unified Graphics and Computing Architecture

To enable flexible, programmable graphics and high-performance computing, NVIDIA has developed the Tesla scalable unified graphics and parallel computing architecture. Its scalable parallel array of processors is massively multithreaded and programmable in C or via graphics APIs.

The GPU Computing Era

GPU computing is at a tipping point, becoming more widely used in demanding consumer applications and high-performance computing. This article describes the rapid evolution of GPU architectures-from graphics processors to massively parallel many-core multiprocessors, recent developments in GPU computing architectures, and how the enthusiastic adoption of CPU+GPU coprocessing is accelerating parallel applications.

Parallel Computing Experiences with CUDA

The CUDA programming model provides a straightforward means of describing inherently parallel computations, and NVIDIAs Tesla GPU architecture delivers high computational throughput on massively parallel problems. This article surveys experiences gained in applying CUDA to a diverse set of problems and the parallel speedups over sequential codes running on traditional CPU architectures attained by executing key computations on the GPU.