Automatic Parallelization: Predicaments in Computationally Expensive Operations

Authors

  • Nahar Hashmukh Prayank Department of Computer Science, Shri Venkateshwara University, Gajraula Distt- Amroha (U.P), India.
  • Bhavsar Department of Computer Science, Shri Venkateshwara University, Gajraula Distt- Amroha (U.P), India.
  • Dharmesh kumar Bhalchandra Department of Computer Science, Shri Venkateshwara University, Gajraula Distt- Amroha (U.P), India.
  • Vishal Bhatnagar Department of Computer Science, Shri Venkateshwara University, Gajraula Distt- Amroha (U.P), India.
  • Richa Tomer Department of Computer Science, Shri Venkateshwara University, Gajraula Distt- Amroha (U.P), India.
  • S.K. Agarwal Department of Computer Science, Shri Venkateshwara University, Gajraula Distt- Amroha (U.P), India.

Keywords:

Subroutines, Procedures, Parallelization, Compilers.

Abstract

The applications developed for parallelizing are either single file based programs or algorithm structures. The commercial large scale application pose problems when performing automatic parallelization and needs to be addressed and hence thought to be implausible. This paper tries to surface the impediments to be addressed so that the parallelization techniques may be applied to these applications. Benchmark suite which are specifically developed to expose the computing requirement and are well acclaimed in the industry have been adopted. Benchmarks used are from High Performance Group of the Standard Performance rating Corporation (SPEC), both parallel and serial versions of applications are used.

Automatic parallel serial codes are compared with its parallel variants in this paper. Parallelizing compiler is employed that takes language (formula based) codes and inserts Open Multi-Processing directives around loops determined to be autonomous. Different problems were faced by an automatic parallelizing compiler when dealing with full applications procedures, optimizations based on superficial techniques, array input output and size variations , Multilanguage hurdles, extreme inclination to library (system-defined functions), and endowment accumulations. The results presented in this paper shall benefit parallelizing compilers with capabilities for handling large scale science and engineering applications.

Downloads

Published

2020-07-19 — Updated on 2020-07-19

How to Cite

Prayank, N. H., Bhavsar, Bhalchandra, D. kumar, Bhatnagar, V., Tomer, R., & Agarwal, S. (2020). Automatic Parallelization: Predicaments in Computationally Expensive Operations. International Journal of Recent Advances in Science and Technology, 1(1), 1–5. Retrieved from https://ijrast.com/index.php/ijrast/article/view/47