Parallel Computing Experiences with CUDA

2008536 citationsJournal Article

Authors

Michael Garland · Nvidia (United States)

Scott Le Grand · Nvidia (United Kingdom)

John Nickolls · Nvidia (United Kingdom)

Joshua A. Anderson · Iowa State University

Jim Hardwick · TechniScan (United States)

Scott Morton · Hess (United States)

Everett Phillips ·

Abstract

The CUDA programming model provides a straightforward means of describing inherently parallel computations, and NVIDIA's 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.

Topics & Keywords

Parallel Computing and Optimization Techniques Algorithms and Data Compression Low-power high-performance VLSI design

UN Sustainable Development Goals

Affordable and clean energy

Publication Details

Published in: IEEE Micro

Volume 28, Issue 4, pp. 13-27

DOI: 10.1109/mm.2008.57

Field-Weighted Citation Impact: 42.90