@inproceedings{1cf913c7b86d4d98a70a3627385ea19b,
title = "Exploiting mixed precision floating point hardware in scientific computations",
abstract = "By using a combination of 32-bit and 64-bit floating point arithmetic, the performance of many dense and sparse linear algebra algorithms can be significantly enhanced while maintaining the 64-bit accuracy of the resulting solution. The approach presented here can apply not only to conventional processors but also to exotic technologies such as Field Programmable Gate Arrays (FPGA), Graphical Processing Units (GPU), and the Cell BE processor. Results on modern processor architectures and the Cell BE are presented.",
keywords = "Iterative refinement, Krylov methods, factorization",
author = "Alfredo Buttari and Jack Dongarra and Jakub Kurzak and Julie Langou and Julien Langou and Piotr Luszczek and Stanimire Tomov",
year = "2008",
language = "English",
isbn = "9781586038397",
series = "Advances in Parallel Computing",
publisher = "IOS Press BV",
pages = "19--36",
booktitle = "High Performance Computing and Grids in Action",
}