journal article·2025-08-01Open access

Investigating Supercomputer Performance with Sustainability in the Era of Artificial Intelligence

Haruna Chiroma

Applied Sciences· Volume 15· Issue 15

Abstract

The demand for high-performance computing (HPC) continues to grow, driven by its critical role in advancing innovations in the rapidly evolving field of artificial intelligence. HPC has now entered the era of exascale supercomputers, introducing significant challenges related to sustainability. Balancing HPC performance with environmental sustainability presents a complex, multi-objective optimization problem. To the best of the author’s knowledge, no recent comprehensive investigation has explored the interplay between supercomputer performance and sustainability over a five-year period. This paper addresses this gap by examining the balance between these two aspects over a five-year period. This study collects and analyzes multi-year data on supercomputer performance and energy efficiency. The findings indicate that supercomputers pursuing higher performance often face challenges in maintaining top sustainability, while those focusing on sustainability tend to face challenges in achieving top performance. The analysis reveals that both the performance and power consumption of supercomputers have been rapidly increasing over the last five years. The findings also reveal that the performance of the most computationally powerful supercomputers is directly proportional to power consumption. The energy efficiency gains achieved by some top-performing supercomputers become challenging to maintain in the pursuit of higher performance. The findings of this study highlight the ongoing race toward zettascale supercomputers. This study can provide policymakers, researchers, and technologists with foundational evidence for rethinking supercomputing in the era of artificial intelligence.
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Research context

OpenAlex topics: Green IT and Sustainability · Parallel Computing and Optimization Techniques · Cloud Computing and Resource Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Computer Science Technology, College of Computer Science and Engineering Technology, Applied College, University of Hafr Al Batin, Hafr Al Batin 31991, Saudi Arabia

Funding

Deanship of Research and Innovation at the University of Hafr Al Batin

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