Abstract

Data Management requires computing devices that can perform data processes to form better information. With the development of data, the processor can be done with one unit only, over time required computing devices that have high performance. Parallel Computing is one of the techniques of doing computing simultaneously by utilizing several independent computers simultaneously. Parallel computers can be grouped according to the level at which hardware supports parallelism. This classification is generally analogous to the distance between basic computing nodes. This research will focus on looking at the widely used classification trends in this parallelism that affect the performance of these calculations. This study uses a systematic literature review to find many classifications in parallel computing. literature is taken from a reputable journal database is ACM Digital Library, IEEE Xplore Digital Library, Science Direct, Emerald Insight. The results of this study are mostly conducted in the United States and China so as to provide many contributions. classification of parallelism, mostly done in parallel computing include Distributed Parallel, Multi-Core Processor, Massively Parallel Computing, and Graph Processing Unit (GPU). In this study also illustrates the advantages in the application of computer parallel based on its classification. In essence the advantages in the application of computer parallel improve performance performance, as well as effective and efficiency in a process that is done

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