DREAM-2026: Workshop on Data Reduction and Energy-Aware Data Movement

AI and data-intensive workloads are driving up both computational and energy demands, with data movement and storage now consuming energy on par with computation. Yet, these costs remain poorly understood and rarely optimized. This workshop brings together researchers and practitioners from AI, HPC, and energy domains to address the challenges of modeling, profiling, and optimizing data flows for performance and sustainability. Topics include power profiling, bottleneck analysis, and energy-aware strategies across diverse architectures, from high-end HPC to resource-constrained systems. The workshop emphasizes holistic energy optimization, highlighting data movement as a critical factor in application performance and sustainability. It encourages the development of methods and tools that improve energy efficiency and supports collaboration toward more sustainable computing practices.

This conference invites submissions addressing, though not exclusively, the following areas: sustainability, performance modeling, i/o and ai workloads.