PARALLEL PROCESSING - A CASE STUDY OF PVM APPLICATION PROGRAMMING INTERFACE Nurul Athirah Abdul Rahim #1, Mohamed Faidz Mohammed Said #2 # Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA 70800 Seremban, Negeri Sembilan, MALAYSIA 1 athirahrahim9502@gmail.com 2 faidzms@ieee.org Abstract—Nowadays computer modelling has been used regularly throughout the geosciences in an effort to produce synthetic data for comparison with real data. Parallel programming model itself is an abstraction of parallel computer architecture. Parallel computing itself is a kind of computation in which numerous calculations or the implementation of processes are carried out concurrently. Parallel Virtual Machine (PVM) system uses the message-passing model to let programmers to exploit dispersed computing across wide diversity of computer categories. PVM is an alternative which is cheap, useful and manageable. Besides that, by using PVM it can integrate current departmental services without experiencing additional hardware costs. Virtual machine or also known as VM can appraise enormous expressions and it was written in numerically fast language. Furthermore, this method can express the parallel computation of a single phase space point in an easy and understandable ways. The objective of this research is to study the application and the use of PVM in parallel computing. The result shows that PVM has many advantages and also has some disadvantages. Keywords: Parallel Virtual Machine, API REFERENCES [1] A. Geist, A. Beguelin, J. Dongarra, W. Jiang, R. Manchek, and V. Sunderam, PVM: Parallel Virtual Machine a users' guide and tutorial for Networked Parallel Computing. 1994, pp. 13-20. [2] G. Bosilca, G. Fedak, and F. Cappello, "OVM: Out-of-order execution parallel virtual machine," Future Generation Computer Systems vol. Vol 18, pp. 525-537, 2002. [3] C. Niccanna and C. J. Bean, "The use of a Parallel Virtual Machine (PVM) for Finite-difference wave simulations," Computers& Geosciences, vol. Vol 23, pp. 771-783, 1997. [4] C. D. Napoli, M. Giordano, and M. M. Fumari, "A PVM-based distributed parallel symbolic system," Advances in Engineering Software vol. Vol 28, pp. 303-312, 1997. [5] S.-J. Shyu and B.M.T.Lin, "An Application of Parallel Virtual Machine Framework to Film Production Problem," Computers and Mathematics with Applications vol. Vol 39, pp. 53-62, 2000. [6] A. K. Tiwari and K. K. S. b, "Implementation of generalized cross validation based image denoising in parallel virtual machine environment," Digital Signal Processing, vol. Vol 14, pp. 138–157, 2004, doi: 10.1016/j.dsp.2003.05.001. [7] W. Li, X. Huang, and N. Zheng, "Parallel implementing OpenGL on PVM," Parallel Computing vol. Vol 23, pp. 1839- 1850, 1997. [8] N. Yalamanchilli and W. Cohen, "Communication Performance of Java-based Parallel Virtual Machines," pp. 1-6, 1998. [9] X. Li, Z. Qian, S. Lu, and J. W. b, "Energy efficient virtual machine placement algorithm with balanced and improved resource utilization in a data center," Mathematical and Computer Modelling, vol. Vol 58, pp. 1222–1235, 2013, doi: 10.1016/j.mcm.2013.02.003. [10] B. C. Nejad, Thorsten Ohl b, and J. Reuter, "Simple, parallel virtual machines for extreme computations," Computer Physics Communications, vol. Vol 196, pp. 58-69, 2015, doi: 10.1016/j.cpc.2015.05.015. [11] F. Fernandes, D. Beserra, E. D. Moreno, B. Schulze, and R. C. G. Pinto, "A virtual machine scheduler based on CPU and I/O-bound features for energy-aware in high performance computing clouds," Computers and Electrical Engineering, vol. Vol 56, pp. 854–870, 2016, doi: 10.1016/j.compeleceng.2016.09.003. [12] M. C, S. Filho, C. C. Monteiro, P. R. M. Inácio, and M. M. Freire, "Approaches for optimizing virtual machine placement and migration in cloud environments: A survey," J. Parallel Distrib. Comput, vol. Vol 111, pp. 222–250, 2017, doi: 10.1016/j.jpdc.2017.08.010. [13] M. Kumara and S.C.Sharmab, "Dynamic load balancing algorithm for balancing the workload among virtual machine in cloud computing," Procedia Computer Science, vol. Vol 115, pp. 322–329, 2017. [14] S. Sotiriadis, N. Bessis, E. G. M. Petrakis, C. Amza, Catalin Negru d, and M. Mocanu, "Virtual machine cluster mobility in inter-cloud platforms," Future Generation Computer Systems vol. Vol 74, pp. 179–189, 2017, doi: 10.1016/j.future.2016.02.007. [15] D. A. Grove and P. D. Coddington, "Modeling message-passing programs with a Performance Evaluating Virtual Parallel Machine," Performance Evaluation, vol. Vol 60, pp. 165-187, 2005, doi: 10.1016/j.peva.2004.10.019.