Reinventing High Performance Computing: Challenges and Opportunities
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Abstract (arXiv)
The world of computing is in rapid transition, now dominated by a world of smartphones and cloud services, with profound implications for the future of advanced scientific computing. Simply put, high-performance computing (HPC) is at an important inflection point. For the last 60 years, the world's fastest supercomputers were almost exclusively produced in the United States on behalf of scientific research in the national laboratories. Change is now in the wind. While costs now stretch the limits of U.S. government funding for advanced computing, Japan and China are now leaders in the bespoke HPC systems funded by government mandates. Meanwhile, the global semiconductor shortage and political battles surrounding fabrication facilities affect everyone. However, another, perhaps even deeper, fundamental change has occurred. The major cloud vendors have invested in global networks of massive scale systems that dwarf today's HPC systems. Driven by the computing demands of AI, these cloud systems are increasingly built using custom semiconductors, reducing the financial leverage of traditional computing vendors. These cloud systems are now breaking barriers in game playing and computer vision, reshaping how we think about the nature of scientific computation. Building the next generation of leading edge HPC systems will require rethinking many fundamentals and historical approaches by embracing end-to-end co-design; custom hardware configurations and packaging; large-scale prototyping, as was common thirty years ago; and collaborative partnerships with the dominant computing ecosystem companies, smartphone, and cloud computing vendors.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Mar 2022.
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Citing papers per year: 2023: 4; 2024: 0; 2025: 2.
6 papers.
- 2023When Geoscience Meets Foundation Models: Towards General Geoscience Artificial Intelligence Systemcited by 13
- 2023Scope is all you need: Transforming LLMs for HPC Codecited by 12
- 2023MonoCoder: Domain-Specific Code Language Model for HPC Codes and Taskscited by 12
- 2023Conservation Tools: The Next Generation of Engineering--Biology Collaborationscited by 2
- 2025Hardware-Efficient Photonic Tensor Core: Accelerating Deep Neural Networks with Structured Compressioncited by 2
- 2025Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directionscited by 2
- 2025Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions13 May 2025
- 2025Hardware-Efficient Photonic Tensor Core: Accelerating Deep Neural Networks with Structured Compression1 Feb 2025
- 2023MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks20 Dec 2023
- 2023When Geoscience Meets Foundation Models: Towards General Geoscience Artificial Intelligence System13 Sep 2023
- 2023Scope is all you need: Transforming LLMs for HPC Code18 Aug 2023
- 2023Conservation Tools: The Next Generation of Engineering--Biology Collaborations3 Jan 2023