A Comparative Study of the Implementation of SJF and SRT Algorithms on the GPU Processor Using CUDA

GPUs (Graphical Processing Units) have become in a few years very powerful tools for the calculation of parallel tasks. They are currently used in several fields such as image processing applications and in bioinformatics and medical applications, video and audio coding and decoding, digital modeling. Their advantages are low cost, faster processing and lower power consumption compared to the equivalent power of the processor (central processing unit). It’s simple to program a GPU graphics processor using a programming language such as CUDA C to perform tasks that are typically calculated in parallel. But then you need to understand the different architectural aspects of GPU GPU. In this article, we will define and implement the Shortest Job First (SJR) and Shortest Remaining Time (SRT) algorithms in a single-threaded CPU environment using the C language, then the same algorithms are implemented on GPU using the CUDA language. C, in order to compare the different performances of the implementation of the two algorithms on the GPU and CPU processors and to ascertain the effectiveness of this study.