Parallel Computing Experiences with CUDA
Top Cited Papers
- 19 September 2008
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Micro
- Vol. 28 (4) , 13-27
- https://doi.org/10.1109/mm.2008.57
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.Keywords
This publication has 16 references indexed in Scilit:
- Relational joins on graphics processorsPublished by Association for Computing Machinery (ACM) ,2008
- GPU acceleration of cutoff pair potentials for molecular modeling applicationsPublished by Association for Computing Machinery (ACM) ,2008
- General purpose molecular dynamics simulations fully implemented on graphics processing unitsJournal of Computational Physics, 2008
- CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignmentBMC Bioinformatics, 2008
- Optimization principles and application performance evaluation of a multithreaded GPU using CUDAPublished by Association for Computing Machinery (ACM) ,2008
- Fast support vector machine training and classification on graphics processorsPublished by Association for Computing Machinery (ACM) ,2008
- Accelerating molecular modeling applications with graphics processorsJournal of Computational Chemistry, 2007
- Screen Savers of the World Unite!Science, 2000
- Fast Parallel Algorithms for Short-Range Molecular DynamicsJournal of Computational Physics, 1995
- A multiple grid scheme for solving the Euler equationsPublished by American Institute of Aeronautics and Astronautics (AIAA) ,1981