Performance Analysis of Multi-threaded Sorting for Unsorted Data Using Remote Procedure Call

Samiha Khan, Asma Ul Hussna, Sanjida Ali Shusmita, Md. Ashekur Rahman, Iffat Immami Trisha, Md Sabbir Hossain, Annajiat Alim Rasel
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Abstract

Distributed procedures that use a message-passing approach communicate with one another by transferring bits of information in order to provide unique access to all available tasks. Almost every single modern computer now has a CPU with several cores, which provides additional computing capacity. Moreover, parallel execution is critical in the new age of big data to enhance performance to a reasonable threshold. Indeed, parallelization brings with it additional issues that must be tack-led. However, parallel algorithms are studied and contrasted in comparison to their consecutive equivalents. In our paper, we look at sorting the unsorted numbers in distributed systems. Multi-threaded methods and performance, along with the difficulty of defining time, affect speed as well. Following that, an experiment was conducted in which a set of algorithms was implemented as well as the data was gathered through benchmarking and testing. To establish the validity of parallelization, the data were inspected and analyzed with its associated source code. A review was carried out in order to obtain a better idea of the scope of sorting algorithms and parallel computing. In this paper, a multi-sorting threading algorithm approach has been conducted based on previous work. The primary idea behind the algorithm is simple as well as Remote Procedure Calls (RPCs) approach has been used.
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使用远程过程调用对未排序数据进行多线程排序的性能分析
使用消息传递方法的分布式过程通过传输信息位来相互通信,以便提供对所有可用任务的唯一访问。现在几乎每台现代计算机都有一个多核的中央处理器,它提供了额外的计算能力。此外,在新的大数据时代,并行执行对于将性能提升到合理的阈值至关重要。实际上,并行化带来了额外的问题,这些问题必须以解决为导向。然而,并行算法的研究和对比,比较其连续等效。在我们的论文中,我们着眼于对分布式系统中未排序的数字进行排序。多线程方法和性能,以及定义时间的困难,也会影响速度。接下来,我们进行了一个实验,实施了一套算法,并通过对标和测试收集了数据。为了确定并行化的有效性,对数据进行了检查和分析,并附带了相关的源代码。为了更好地了解排序算法和并行计算的范围,进行了回顾。本文在前人工作的基础上,提出了一种多排序线程算法。该算法的主要思想很简单,并且使用了远程过程调用(rpc)方法。
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