Pith. sign in

REVIEW 2 cited by

Reinventing High Performance Computing: Challenges and Opportunities

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2203.02544 v1 pith:ONDB4HBN submitted 2022-03-04 cs.DC

classification cs.DC
keywords computingsystemscloudscientificvendorsworldadvancedchange
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Usability Evaluation of Cloud for HPC Applications

    cs.DC 2025-06 conditional novelty 6.0 of 10

    A cross-cloud study of 11 HPC proxy apps finds that clouds with fast networks can handle small to medium HPC workloads, but setup effort, cost, and performance vary widely.

  2. KPerfIR: Towards an Open and Compiler-centric Ecosystem for GPU Kernel Performance Tooling on Modern AI Workloads

    cs.DC 2025-05 conditional novelty 6.0 of 10

    KPerfIR is a compiler-centric profiling infrastructure for Triton, demonstrated by a region-based timing tool that improved Triton's FlashAttention-3 by 24.1%.

Pith tools