Title :
Solving Markov chains using bounded aggregation on a massively parallel processor
Author_Institution :
Dept. of Math., Youngstown State Univ., OH, USA
Abstract :
An SIMD implementation of a method for approximating the stationary distribution vector of a Markov chain is presented. A key feature of the implementation is the simultaneous computation of several matrix inverses. Computational results from a MasPar MP-1 system are discussed
Keywords :
Markov processes; aggregation; matrix inversion; parallel processing; Markov chains; MasPar MP-1 system; SIMD implementation; bounded aggregation; massively parallel processor; matrix inverses; stationary distribution vector; Application software; Arithmetic; Computer architecture; Computer networks; Heart; Mathematics; Nearest neighbor searches; Queueing analysis; Registers; Steady-state;
Conference_Titel :
Parallel and Distributed Processing, 1993. Proceedings of the Fifth IEEE Symposium on
Conference_Location :
Dallas, TX
Print_ISBN :
0-8186-4222-X
DOI :
10.1109/SPDP.1993.395541
