high-performance computing
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A Comparative Review of Parallel Computing Techniques for High-Performance Computing
Abstract: High-Performance Computing (HPC) has become an essential technology for solving computationally intensive problems in scientific computing, engineering, artificial intelligence, weather forecasting, computational biology, financial modelling, and large-scale data analytics. The increasing complexity and heterogeneity of modern HPC systems have created a strong requirement for efficient parallel computing techniques and portable programming models. Several programming approaches, including Message Passing Interface (MPI), Open Multi-Processing (OpenMP), Compute Unified Device Architecture (CUDA), OpenACC, SYCL, …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 2, 2026 · pp. 16–26 Read article
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Polyhedral Compilation for Imperative Loops: Foundations, Advances, and Emerging Frontiers
Abstract: Polyhedral compilation is a mathematically rigorous framework that models imperative loop nests as sets of integer points constrained by affine inequalities, enabling precise reasoning about data dependences and the legality of complex program transformations. Over the past decade, this framework has evolved from an academic formalism into a practical compiler technology deployed in production compilers, high-performance computing libraries, and machine learning acceleration toolchains. This review surveys the theoretical underpinnings of …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 2, 2026 · pp. 7–15 Read article