Abstract
Computational physics has played important roles in real world problems. This paper is within the applied computational physics area. The aim of this study is to observe the performance of parallel computations using a cluster of workstations (COW) to simulate elasticity problems. Parallel computations with the COW configuration are conducted using the Message Passing Interface (MPI) standard. In parallel computations with COW, we consider five scenarios with twenty simulations. In addition to the execution time, efficiency is used to evaluate programming algorithm scenarios. Sequential and parallel programming performances are evaluated based on their execution time and efficiency. Results show that the one-dimensional elasticity equations are not appropriate to be solved in parallel with MPI_Send and MPI_Recv technique in the MPI standard, because the total amount of time to exchange data is considered more dominant compared with the total amount of time to conduct the basic elasticity computation.
Highlights
One of mathematics models describing elastic wave propagation in solid media is the elasticity partial differential equation model
We obtain that the one-dimensional elasticity equations are not appropriate to be solved using parallel programming with MPI_Send and MPI_Recv technique in the Message Passing Interface (MPI) standard, because the total amount of time to exchange data is considered more dominant compared with the total amount of time to conduct the basic elasticity computation using the finite volume method
We recommend that if the total time needed in the data exchange is larger than the total time needed in the basic computations, the sequential computation may be better to implement than the parallel
Summary
One of mathematics models describing elastic wave propagation in solid media is the elasticity partial differential equation model. This model can be applied in the real world, such as propagation of earthquakes, acoustic waves and waves on an elastic medium. This paper deals with elasticity problems for their numerical solutions. It is difficult for a single computer to gain high speed computation. This paper investigates if we obtain high speed and efficiency in parallel computations using a cluster of workstation to solve elasticity problems.
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