DocumentCode
2432095
Title
High performance linear equation solver using NVIDIA GPUs
Author
Leow Yoon Kah ; Akoglu, Ali ; Guven, Ibrahim ; Madenci, Erdogan
Author_Institution
Univ. of Arizona, Tucson, AZ, USA
fYear
2011
fDate
6-9 June 2011
Firstpage
367
Lastpage
374
Abstract
The solution of a linear system of equations constitutes an important part in the field of linear algebra that is widely used in industries like aerospace, aeronautics, solid mechanics, fluid dynamics, oil research and numerous others. A direct method for solving these equations is Gaussian Elimination, which consists of forward elimination and back substitution. We have tailored this method to take advantage of the massive parallelism offered by NVIDIA GPU architectures. Thorough evaluations have been performed for variants of our implementation that exploit different memory features on an NVIDIA Tesla C1060 GPU. Compared to a serial implementation on an Intel Core I7, the execution time for forward elimination on the GPU is reduced by a factor of 183X when using both global and shared memory systems, and by a factor of 185X when using only global memory.
Keywords
computer graphic equipment; coprocessors; finite element analysis; linear algebra; parallel architectures; shared memory systems; storage management; Gaussian elimination; NVIDIA GPU architecture; NVIDIA Tesla C1060 GPU; aeronautics; aerospace; back substitution; fluid dynamics; forward elimination; global memory system; high performance linear equation solver; linear algebra; massive parallelism; memory feature; oil research; shared memory system; solid mechanics; Equations; Graphics processing unit; Instruction sets; Kernel; Mathematical model; Matrices; Random access memory;
fLanguage
English
Publisher
ieee
Conference_Titel
Adaptive Hardware and Systems (AHS), 2011 NASA/ESA Conference on
Conference_Location
San Diego, CA
Print_ISBN
978-1-4577-0598-4
Electronic_ISBN
978-1-4577-0597-7
Type
conf
DOI
10.1109/AHS.2011.5963960
Filename
5963960
Link To Document