Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/11224
Title: | Accelerating scientific computations with mixed precision algorithms | Authors: | Baboulin, Marc Buttari, Alfredo Dongarra, Jack Kurzak, Jakub Langou, Julie Luszczek, Piotr Tomov, Stanimire Langou, Julien |
Issue Date: | 2008 | Publisher: | Centro de Matemática da Universidade de Coimbra | Citation: | Pré-Publicações DMUC. 08-44 (2008) | Abstract: | On modern architectures, the performance of 32-bit operations is often at least twice as fast as the performance of 64-bit operations. By using a combination of 32-bit and 64-bit oating point arithmetic, the performance of many dense and sparse linear algebra algorithms can be signi cantly 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 other technologies such as Field Programmable Gate Arrays (FPGA), Graphical Processing Units (GPU), and the STI Cell BE processor. Results on modern processor architectures and the STI Cell BE are presented. | URI: | https://hdl.handle.net/10316/11224 | Rights: | openAccess |
Appears in Collections: | FCTUC Matemática - Vários |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Accelerating scientific computations with mixed precision algorithms.pdf | 207.11 kB | Adobe PDF | View/Open |
Page view(s)
305
checked on Oct 29, 2024
Download(s) 20
907
checked on Oct 29, 2024
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.