Parallel algorithms and cluster computing

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High-performance computing has transformed scientific progress over the past two decades. The surge in computing power, coupled with the development of effective algorithms, has significantly advanced physics and engineering, enabling the analysis of complex problems previously beyond analytical reach. The rise of massive parallel computing and cluster computers has further expanded the ability to study realistic systems. This work highlights key advancements in high-performance computing and its impact on various scientific fields. Recent progress is anchored in three distinct areas of science, where pressing challenges in physics and mechanical engineering drive the development of innovative tools and approaches. Complex physical systems characterized by frustration and disorder, as well as the analysis of elastic and non-elastic movement in solids and coupled fluid systems, can only be effectively addressed through state-of-the-art computing power and algorithms. The pursuit of scientific accuracy and quantitative precision has led to an increased demand for computing resources. Formulating the right questions in these domains has yielded new insights unattainable through traditional experimental methods. Additionally, the effectiveness of high-performance computing relies heavily on the advancement of efficient algorithms.