Technology trends in computing hardware and their impacts on high-performance scientific computing Part I: General-purpose processors and hardware accelerators
Bagus Hanindhito, Arash Fathi, Dimitrios Gourounas, Dimitar Trenev, Andreas Gerstlauer, Lizy K. John · The International Journal of High Performance Computing Applications · 2025
Computing technology has evolved significantly during the past five decades. As semiconductor scaling is reaching physical and technological limits, it is driving many transformative changes in computing hardware. This has led to computing systems that rely heavily on multi-core processors and GPUs, and resulted in the development of specialized hardware for applications in machine learning and scientific computing. While modern hardware provides significant computing power, and therefore opportunities, it challenges many established algorithms and workflows in scientific computing: these algorithms may not be able to fully leverage modern hardware. Often times, effective use of modern hardware entails revised algorithms, and even rewriting a considerable portion of an existing code. Understanding technology trends in computing hardware is necessary for designing next-generation algorithms for scientific computing. This paper reviews these trends, along with their drivers, in a language that is accessible to computational and data scientists, and applied mathematicians. In this paper (Part I), we review technology evolution in general-purpose microprocessors and hardware accelerators, along with background material. In Part II (Hanindhito et al., 2026), we consider memory systems, inter-device communication, heterogeneous computing and system integration, energy consumption, and how these trends impact scientific computing.