TY - GEN

T1 - An algorithm for solving massive matrix inversion in cloud computing systems

AU - Bae, Do Hyun

AU - Bayartsogt, Munkhbayar

AU - Kim, Jin Suk

PY - 2011

Y1 - 2011

N2 - In this paper we introduce a parallel approach to calculate massive matrix inversion. It needs large size of memory to compute with large size of matrices. Because of the memory requirements, we consider an algorithm to optimize memory distribution in cloud computing system. In matrix inversion using Gauss-Jordan algorithm, we found out a lot of regional memory access tendency in the algorithm. We also consider this memory access tendency. To solve these problems, we divide the matrix data as many as numbers of processors which was assigned to calculate matrix inversion. Dividing directions both horizontal and vertical are possible to imply. Matrix inversion has steps, and this step is increase according to the size of the matrix, and previous step calculation results are used at each step calculation results. To do above process, we use a parallel scheduler. Parallel scheduler manages the all processors and synchronizes these processors calculation. Research is focused on solving massive matrix inversion, so we test our research in cloud computing system, and we obtain the progress results.

AB - In this paper we introduce a parallel approach to calculate massive matrix inversion. It needs large size of memory to compute with large size of matrices. Because of the memory requirements, we consider an algorithm to optimize memory distribution in cloud computing system. In matrix inversion using Gauss-Jordan algorithm, we found out a lot of regional memory access tendency in the algorithm. We also consider this memory access tendency. To solve these problems, we divide the matrix data as many as numbers of processors which was assigned to calculate matrix inversion. Dividing directions both horizontal and vertical are possible to imply. Matrix inversion has steps, and this step is increase according to the size of the matrix, and previous step calculation results are used at each step calculation results. To do above process, we use a parallel scheduler. Parallel scheduler manages the all processors and synchronizes these processors calculation. Research is focused on solving massive matrix inversion, so we test our research in cloud computing system, and we obtain the progress results.

KW - Gauss-Jordan algorithm

KW - cloud computing

KW - distributed computing system

KW - matrix inversion

UR - http://www.scopus.com/inward/record.url?scp=84863129061&partnerID=8YFLogxK

U2 - 10.1145/2103380.2103392

DO - 10.1145/2103380.2103392

M3 - Conference contribution

AN - SCOPUS:84863129061

SN - 9781450310871

T3 - Proceedings of the 2011 ACM Research in Applied Computation Symposium, RACS 2011

SP - 61

EP - 66

BT - Proceedings of the 2011 ACM Research in Applied Computation Symposium, RACS 2011

T2 - 2011 ACM Research in Applied Computation Symposium, RACS 2011

Y2 - 2 November 2011 through 5 November 2011

ER -