PARALLEL COMPUTING - A CASE STUDY ON MULTICORE COMPUTING Afiqah Ahmad #1, Mohamed Faidz Mohamed Said #2 # Faculty of Computer & Mathematical Sciences, Universiti Teknologi MARA 70300 Seremban, Negeri Sembilan, MALAYSIA 1 afiqah.aa95@gmail.com 2 faidzms@ieee.org Abstract—There are generally technical problems in integrating components in parallel computing. In could be overcome by applying certain mathematical approaches that would scientifically solve specific issues relating to parallelism. The improvement in computer technology by using numerical method will be mainly discussed in this paper. One of the issues is the installation of multi-core processor to achieve better performance during the completion of programs. The processing and completing one task commonly take too much time. The majority improvements of technology in computers involve mathematical methods. The prominent numerical techniques used are matrix computation, time reduction as well as linear system for computational area. Ordinarily, matrix unit computation is used to maximize on-chip resource utilization and to leverage the advantages of the current multi-core revolution to improve the performance of data-parallel applications. Besides that, branch and bound (B&B) algorithm, heterogeneous architecture and pipeline algorithm are also used in science and chemical area in order to confirm chemical reaction into living organism. In this paper, a further discussion of different approaches will be given with distinct algorithms and techniques that are used from previous researches. Based on those processes and methods for each area involved, some of it give good results and excellence performances. Keywords: multi-core, branch and bound, parallel computing REFERENCES [1] T.-T. Vu and B. Derbel, "Parallel Branch-and-Bound in Multi-Core Multi-CPU Multi-GPU Heterogeneous Environments," Future Generation Computer Systems, vol. 56, no. Supplement C, pp. 95-109, 2016/03/01/ 2016, doi: https://doi.org/10.1016/j.future.2015.10.009. [2] I. Chakroun, N. Melab, M. Mezmaz, and D. Tuyttens, "Combining Multi-Core and GPU Computing for Solving Combinatorial Optimization Problems," Journal of Parallel and Distributed Computing, vol. 73, no. 12, pp. 1563-1577, 2013/12/01/ 2013, doi: https://doi.org/10.1016/j.jpdc.2013.07.023. [3] M. I. Soliman and A. F. Al-Junaid, "A Shared Matrix Unit for a Chip Multi-Core Processor," Journal of Parallel and Distributed Computing, vol. 73, no. 8, pp. 1146-1156, 2013/08/01/ 2013, doi: https://doi.org/10.1016/j.jpdc.2013.03.004. [4] P. D. Michailidis and K. G. Margaritis, "Scientific Computations on Multi-Core Systems Using Different Programming Frameworks," Applied Numerical Mathematics, vol. 104, no. Supplement C, pp. 62-80, 2016/06/01/ 2016, doi: https://doi.org/10.1016/j.apnum.2014.12.008. [5] G. Sornet, F. Dupros, and S. Jubertie, "A Multi-level Optimization Strategy to Improve The Performance of Stencil Computation," Procedia Computer Science, vol. 108, no. Supplement C, pp. 1083-1092, 2017/01/01/ 2017, doi: https://doi.org/10.1016/j.procs.2017.05.217. [6] V. Martínez, F. Dupros, M. Castro, and P. Navaux, "Performance Improvement of Stencil Computations for Multi-core Architectures Based on Machine Learning," Procedia Computer Science, vol. 108, no. Supplement C, pp. 305-314, 2017/01/01/ 2017, doi: https://doi.org/10.1016/j.procs.2017.05.164. [7] Y. Lu, Y. Li, B. Song, W. Zhang, H. Chen, and L. Peng, "Parallelizing Image Feature Extraction Algorithms on Multi-Core Platforms," Journal of Parallel and Distributed Computing, vol. 92, no. Supplement C, pp. 1-14, 2016/05/01/ 2016, doi: https://doi.org/10.1016/j.jpdc.2016.03.001. [8] C. V. P. Mohan and P. Talukdar, "Three dimensional numerical modeling of simultaneous heat and moisture transfer in a moist object subjected to convective drying," International Journal of Heat and Mass Transfer, vol. 53, no. 21-22, pp. 4638-4650, 2010. [9] Y. Zhang, G. Xiao, and T. Baba, "Accelerating Sequential Programs on Commodity Multi-Core Processors," Journal of Parallel and Distributed Computing, vol. 74, no. 4, pp. 2257-2265, 2014/04/01/ 2014, doi: https://doi.org/10.1016/j.jpdc.2013.12.009. [10] M. M. Jaghoori et al., "PMG: Multi-Core Metabolite Identification," Electronic Notes in Theoretical Computer Science, vol. 299, no. Supplement C, pp. 53-60, 2013/12/25/ 2013, doi: https://doi.org/10.1016/j.entcs.2013.11.005. [11] T. Qiu, A. Zhao, R. Ma, V. Chang, F. Liu, and Z. Fu, "A Task-Efficient Sink Node Based on Embedded Multi-Core soC for Internet of Things," Future Generation Computer Systems, 2016/12/23/ 2016, doi: https://doi.org/10.1016/j.future.2016.12.024. [12] T. Hussain, "A Novel Hardware Support for Heterogeneous Multi-Core Memory System," Journal of Parallel and Distributed Computing, vol. 106, no. Supplement C, pp. 31-49, 2017/08/01/ 2017, doi: https://doi.org/10.1016/j.jpdc.2017.02.008. [13] P. Kegel, M. Steuwer, and S. Gorlatch, "dOpenCL: Towards Uniform Programming of Distributed Heterogeneous Multi-/Many-Core Systems," Journal of Parallel and Distributed Computing, vol. 73, no. 12, pp. 1639-1648, 2013/12/01/ 2013, doi: https://doi.org/10.1016/j.jpdc.2013.07.021. [14] H. Salamy, "An Effective Approach to Schedule Time Reduction on Multi-Core Embedded Systems," Computers & Electrical Engineering, vol. 64, no. Supplement C, pp. 15-33, 2017/11/01/ 2017, doi: https://doi.org/10.1016/j.compeleceng.2016.07.001. [15] A. Ahmad. (2017). Parallel Computing – A Case Study on Multi-core Computing. Available: https://www.youtube.com/watch?v=fdMn-3owkxg&rel=0 [Accessed: 28-Nov-2017]