TAILIEUCHUNG - Evaluation of parallel application’s performance dependency on ram using parallel virtual machine

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. | ISSN:2249-5789 Nanjesh B R et al , International Journal of Computer Science & Communication Networks,Vol 2(6), 641-646 Evaluation of Parallel Application’s Performance Dependency on RAM using Parallel Virtual Machine Sampath S1, Nanjesh B R1 1 Department of Information Science and Engineering Adichunchanagiri Institute of Technology, Chikmagalur, Karnataka, INDIA Abstract Parallel computing is the simultaneous use of multiple compute resources to solve a computational problem. Parallel computing operates on the principle that large problems can often be divided into smaller ones, which are then solved concurrently ("in parallel"). The reasons for using parallel processing are to save time (wall clock time), to solve larger problems and to provide concurrency while taking advantage of nonlocal resources and overcoming memory constraints. We aim to present a framework using PVM that demonstrates the performance dependency of parallel applications on RAM of the nodes (desktop PCs) used in parallel computing. This can be realized by implementing matrix multiplication problem on the framework. The framework 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 . 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 compare and evaluate these 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. Index Terms— Parallel Execution, Cluster Computing, Symmetric

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