@conference {Kasmi2015,
	title = {Taking advantage of GPU/CPU architectures for sparse Conjugate Gradient solver computation},
	booktitle = {Proceedings of 2015 IEEE World Conference on Complex Systems, WCCS 2015},
	year = {2015},
	note = {cited By 0},
	abstract = {Solving large sparse linear systems is a time and energy consuming process. This paper presents an efficient exploitation of graphic processing units (GPUs) for accelerating Conjugate Gradient iterative solver (CG). We use the high-level software library PARALUTION for sparse linear algebra on multi/many-core systems, which supports GPU (with CUDA and OpenCL) and Multi-CPU implementations of CG method using different storage formats. We discuss and compare performance using three platforms. {\textcopyright} 2015 IEEE.},
	doi = {10.1109/ICoCS.2015.7483268},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978427957\&doi=10.1109\%2fICoCS.2015.7483268\&partnerID=40\&md5=af973d4adddb0778d096c29e4a71e051},
	author = {Kasmi, N.a and Zbakh, M.a and Mahmoudi, S.A.b and Manneback, P.b}
}
