Work

Technology trends in computing hardware and their impacts on high-performance scientific computing Part II: Memory systems, interconnects, and system integration

Year: 2026

Type: article

Abstract: In Part I of this paper (Hanindhito et al., 2026), we argued understanding technology trends in computing hardware is necessary for designing next-generation algorithms for scientific computing. Using a language that is accessible to a general computational or data scientist, or applied mathematician, we aim to help our targeted readers better understand how technology trends in computing hardware are going to impact their computations, and what characteristics algorithms should exhibit to best harness modern hardware. In Part I, we covered background material, general-purpose processors, and hardware accelerators. In Part II, we review memory systems, inter-device communication, heterogeneous computing and system integration, and why energy efficiency has become a central issue in hardware design, and why it cannot be ignored in cluster-sized computers. We conjecture how the above changes may impact scientific computing, and offer options for leveraging modern hardware for both old and modern scientific software.

Source: The International Journal of High Performance Computing Applications

DOI: 10.1177/10943420251347461

Authors: Bagus Hanindhito, Arash Fathi, Dimitrios Gourounas, Dimitar Trenev, Andreas Gerstlauer, Lizy K. John

Institutions: The University of Texas at Austin, ExxonMobil (United States)

Language: English

Topic: Parallel Computing and Optimization Techniques

Subfield: Hardware and Architecture

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,400

Funders: ExxonMobil Research and Engineering Company, Division of Computing and Communication Foundations