Parallel Programming Languages and Domain-Specific Languages: A Comprehensive Review

Abstract

Authors: Shyamsunder Tiwari, Sneha Desai, Amrendra Tripathi, Umehs Chandra, Vipul Ojha

Abstract: With the rapid evolution of multi-core processors, graphics processing units, and distributed computing platforms, parallel programming has become a crucial area of research and development. Traditional sequential programming models are no longer sufficient to exploit the full potential of modern hardware architectures. As a result, various parallel programming languages and domain-specific languages (DSLs) have been proposed to simplify parallel software development while improving performance and scalability. This paper presents a comprehensive review of parallel programming languages and DSLs, focusing on their design principles, programming models, advantages, and limitations. The study covers both general-purpose parallel languages such as OpenMP, MPI, CUDA, and OpenCL, as well as DSLs tailored for specific domains like machine learning, scientific computing, and data analytics. Comparative analysis is provided through tables and conceptual figures. The paper also discusses current challenges and future research directions in the development of parallel programming languages and DSLs.

Keywords: Parallel programming, Domain-specific languages, OpenMP, MPI, CUDA, DSLs, High-performance computing