Author:
Al-Mouhamed Mayez A.,Khan Ayaz H.
Funder
National Plan for Science, Technology, and Innovation (MAARIFAH)
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Reference38 articles.
1. Abu-Sufah W, Karim A (2012) An effective approach for implementing sparse matrix–vector multiplication on graphics processing units. In: IEEE 14th International Conference on High Performance Computing and Communication, pp 453–460
2. Ahamed C, Kassim A, Frdric M (2012) Iterative methods for sparse linear systems on graphics processing unit. In: IEEE 14th International Conference on High Performance Computing and Communication, pp 836–842
3. Alejandro D, Polanco R (2009) Collective communication and barrier synchronization on NVIDIA CUDA GPU. MS thesis, University of Kentucky
4. Aliaga J, Perez J, Quintana-Orti E, Anzt H (2013) Reformulated conjugate gradient for the energy-aware solution of linear systems on GPUs. In: 42nd International Conference on Parallel Processing (ICPP), pp 320–329
5. Anzt H, Tomov S, Dongarra J (2014) Implementing a sparse matrix vector product for the sell-c/sell-c- $$\sigma $$ σ formats on NVIDIA GPUs. Technical report on UT-EECS-14-727, University of Tennessee
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献