Title :
Processor mapping technique for communication free data redistribution on symmetrical matrix
Author :
Hsu, Ching-Hsien ; Yu, Kun-Ming
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Chung Hua Univ., Hsinchu, Taiwan
Abstract :
In this paper, we present the processor mapping technique to eliminate amount of data exchange in runtime data redistribution on symmetric matrices. The main idea of the proposed technique is to develop mathematical functions for mapping destination processors to a new sequence of processor id. The realigned order of destination processors is then used to perform data redistribution in the receiving phase. Together with a local matrix transposition scheme, interprocessor communication can be totally eliminated in runtime redistribution. The other improvement of this approach is that one does not need to compute the complicated communication sets. The indexing cost is reduced largely. The theoretical analysis shows that (p-1)/p data transmission cost can be saved for a redistribution over p×p processors grid. Experimental result also shows that the processor mapping technique provides superior improvement for runtime data redistribution.
Keywords :
data communication; grid computing; matrix algebra; message passing; multiprocessing systems; multiprocessor interconnection networks; processor scheduling; resource allocation; communication free data redistribution; data exchange; data transmission cost; destination processors; indexing cost reduction; interprocessor communication; local matrix transposition; mathematical functions; processor ID; processor grid; processor mapping; runtime data redistribution; runtime support; symmetrical matrix; Computer architecture; Computer science; Costs; Data communication; Data engineering; Distributed computing; Indexing; Matrix decomposition; Runtime; Symmetric matrices;
Conference_Titel :
Parallel Architectures, Algorithms and Networks, 2004. Proceedings. 7th International Symposium on
Print_ISBN :
0-7695-2135-5
DOI :
10.1109/ISPAN.2004.1300483