期刊名称:International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN:2277-6451
电子版ISSN:2277-128X
出版年度:2013
卷号:3
期号:1
出版社:S.S. Mishra
摘要:Parallel computing operates on the principle that large problems can often be divided into smaller ones, which are then solved concurrently to save time (wall clock time) by taking advantage of non -local resources and overcoming memory constraints. The main aim is to form common single node architecture for both MPI and PVM, which demonstrates the performance gain and losses achieved through parallel processing using MPI and PVM as separate cases. We also demonstrates the performance dependency of parallel applications on RAM of the nodes (desktop PCs) used in parallel computing. This can be realized by implementing the parallel applications like solving matrix multiplication problem, using MPI and PVM separately. The single node architecture consists of a client, a master, capable of handling requests from the client, and a slave, capable of accepting problems from the master and sending the solution back. The master and the slave communicate with each other using MPICH-2 and PVM3.4.6 when computation is under MPI and PVM respectively. The master will monitor the progress and be able to compute and report the time taken to solve the problem, taking into account the time spent in assigning the problem into slave and sending the results along with the communication delays. . We aim to evaluate and compare these statistics of both the cases to decide which among MPI and PVM gives faster performance and also compare with the time taken to solve the same problem in serial execution to demonstrate communication overhead involved in parallel computation. We aim to compare and evaluate the statistics obtained for different sizes of RAM under parallel execution in a single node involving only two cores, where one acts as master and other as slave. We also show the dependency of serial execution on RAM for the same problem by executing its serial version under different sizes of RAM.