Bhavisha Vishalbhai Parvadiya,
- Assistant Professor, Department of Computer Science and Engineering, Sardar Patel College of Administration and Management, Gujarat, India
Abstract
The accelerating demand for computational power in scientific, engineering, and data-intensive domains has driven high-performance computing (HPC) systems toward unprecedented levels of parallelism and architectural complexity. Contemporary HPC platforms integrate multicore CPUs, many-core GPUs, accelerators, and deep memory hierarchies, creating significant challenges for software development and performance optimization. Traditional general-purpose programming languages and parallel programming frameworks provide low-level control over hardware resources but require extensive manual tuning, resulting in poor productivity and limited performance portability. Domain-specific languages (DSLs) have emerged as a transformative approach to HPC software development by offering high-level abstractions that encode domain knowledge directly into language constructs and compiler infrastructures. This enables aggressive, semantics-aware optimizations that are difficult or impossible to achieve using conventional programming paradigms. This paper presents a comprehensive and deeply analytical study of the design principles, classification, and optimization techniques of DSLs for HPC applications. It further examines prominent DSL frameworks through detailed case studies, analyzes their performance benefits, and discusses open challenges and future research directions in the context of exascale and energy-aware computing.
Keywords: Compiler optimization, domain-specific languages, heterogeneous systems, high-performance computing, parallel architecture, performance portability
[This article belongs to Recent Trends in Parallel Computing ]
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Recent Trends in Parallel Computing
| Volume | 13 | |
| Issue | 01 | |
| Received | 28/01/2026 | |
| Accepted | 01/02/2026 | |
| Published | 20/03/2026 | |
| Publication Time | 51 Days |