Empirical Investigation Of Cloud, Grid and Virtualization Using Compilar Optimization Level For Threads Processe (International Journal of Innovative Research in Computer Science & Technology, 2021)
This research focused on the  implementation of Open MP. It considers the parallelization  of an application code that simulates the thermal gradient of  material in two dimensions. A ‘C language’ program code  called jacobi2d.c that solves a rectangular 2-dimensional  heat conductivity problem using Jacobi iterative method  was used. The boundary conditions required to compute a  temperature distribution for a rectangular 2D problem are:  Top 300C, Bottom 500C, Left 400C and Right 900C with a  range of problem sizes enter as a run-time parameter to alter  the problem sizes and convergence criteria. Also, there  were computations and readings for iterations and runtime  for four values of M and N which were selected for 01, 02,  and 03 optimizations. In Table 1 Readings, four values  were selected for each of the iterations. The results show  the performance of the runtime as the processor increases  from 01-optimization, to 02-optimization and finally to 03- optimization. It can be deduced from the representation that  the run time of the values reduces as more resources are  allocated to execution through the increase in optimization  level. Also, in Table 2 Readings, the runtime decreases as it  moves from thread1, thread2, thread3, and thread4,  comparing the last values for thread1 which are M is 180, N  is 200, and their runtime which is 42.797187001. Also the  last values for thread2 which are M is 180, N is 200, their  runtime which is 21.772106003. When the two runtimes  were compared, it was discovered that there was a decrease  in the runtime because the more the thread increases, the  more system resources they share such as a processor which  may affect their runtime by increasing it.
Keywords: Cloud Computing; Compiler Optimization; Grid; Thread Processes