EE HPC WG: TPC'

2026

This discussion forum focussed on the sustainability challenges of large-scale AI, aligned with the mission of advancing responsible and scalable AI for science. As trillion-parameter models demand unprecedented compute, energy, and data resources, critical questions arise around carbon footprint, infrastructure efficiency, and equitable access. The forum convened researchers, industry practitioners, and infrastructure providers to examine trade-offs between performance and sustainability, share best practices in energy-efficient model design and deployment, and identified collaborative pathways for greener AI. By fostering cross-sector dialogue, this session aimed to shape actionable strategies for sustainable AI at extreme scale.

• • Sid Jana - intro, overview of topic, sustainability challenges

  • Tejus Rajan- MLPerf Power

  • Brice Videau  - Userspace Runtime Control for Performance–Energy Efficient AI Workloads

  • Stephanie Brink - A Global Perspective on Supercomputer Power Provisioning: Case Studies from U.S. and Europe

  • Daniel Wilson - Flexible AI: How Data Centers Can Help Solve Their Own Power Problem