SC25 ACM & IEEE-CS Award Presentations: Seymour Cray & Sidney Fernbach Awards

Seymour Cray Award
A Retrospective on Science-Driven System Architecture, and Grand Challenges for the New Century, John Shalf, Lawrence Berkeley National Laboratory

This talk opens with a brief retrospective on the speaker’s path through computer architecture and HPC—highlighting the lessons from early work on energy-efficient computing, co-design campaigns for exascale/petascale computing, procurement models anchored in real scientific workflows, and cross-disciplinary work that now shape his outlook. Against that backdrop, he argues that energy continues to be the dominant design constraint, stalling a decade of once-relentless performance gains in HPC and creating an energy crisis in hyperscale AI.

Leveraging the latest technology roadmaps, the speaker updates what “post-exascale” systems are likely to look like and why the historical drivers of improvement are becoming more challenging to sustain. He then reframes co-design: from narrow kernel–hardware tuning toward an end-to-end, materials-to-systems and workflow-aware practice that couples advanced packaging with targeted architectural specialization. Finally, he lays out strategies for continued progress without the aid of the old scaling playbook—focusing on energy proportionality, domain-specific acceleration, and evolving the definition of co-design to exploit the mathematical structure of the algorithms being accelerated.

He also lays out opportunities for deeper collaboration with our colleagues in hyperscale computing by leveraging their supply chain and through organizations such as the Open Compute Project. The thesis is that sustained performance growth will come from pragmatic, cross-layer co-design and smaller, workflow-effective systems rather than ever-larger monolithic machines.

48:00
Sidney Fernbach Award
Abstraction and Automation: From Workflows to Intelligent Systems and the Future of Scientific Discovery, Ewa Deelman, University of Southern California

Scientific computing has evolved through successive layers of abstractio — from machine code to workflows, from manual scheduling to autonomous orchestration. Each innovation focused on making complexity manageable while preserving scientific intent. The Pegasus Workflow Management System was built in this tradition: translating high-level scientific descriptions into efficient and reliable execution across diverse high-performance and distributed systems.

Today, as artificial intelligence reshapes both systems and science, systems are no longer just executing—they are reasoning, predicting, and adapting. Scientific discovery is enhanced with automation throughout the scientific lifecycle: from hypothesis generation to result interpretation and publication.

This enhanced automation opens transformative possibilities for new discoveries and technological advances. However, it also requires us to confront deeper questions about transparency, trust, and the role of human judgment in an increasingly automated world.

This talk reflects on the enduring design principles that have sustained Pegasus through decades of technological change, explores how AI is redefining the balance between abstraction and understanding, and emphasizes the need for critical thinking and creativity while scientists are increasingly relying on cognitive automation.

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https://sc25.supercomputing.org/
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SC25 • 16–21 NOV 2025 • ST. LOUIS, MO
The International Conference for High Performance Computing, Networking, Storage, and Analysis