2nd Workshop on Scheduling Variable CapacityResources for Sustainability

This is the report for the second workshop on Scheduling Variable Capacity Resources for Sustainability. The first workshop in 2023 nucleated a research community focused on compute scheduling in the new age of renewable power generation -- where variation in weather and solar radiation drives variation in compute capacity (opportunity). The goal was to mobilize a combination of the scheduling community, cloud resource management community, and new leaders creating adaptive datacenters. These adaptive grid loads could then accelerate the use of clean renewable energy and thereby power grid decarbonization. This first workshop posited 1) variable capacity, flexible compute platforms; 2) dynamic grids and datacenter-grid decoupling; 3) adaptive scheduling approaches to accommodate these varying platforms and respond to grid demands; and 4) a growing social and government demand for carbon progress in datacenter systems. In September 2025, all of these technical changes come to reality, at large scale because of the AI fueled explosion of datacenter power demand and grid stress.However, in September 2025, the world of variable capacity scheduling is also shaped by two radical changes. First, a geo-political shock. While the dangers of climate change continue to grow, the turn of the US government's policies away from renewables, even promoting fossil fuels, has created a global turmoil. Second, a workload shock. Over the past two years, the AI revolution dramatically accelerated the growth of electric power consumption by computing -- in North America, Europe, Asia (notably China), and the Middle East. In short, the trends that motivated the workshop have only increased in importance and urgency.At the second workshop, we assessed progress made in 2.5 years on the key problems of variable capacity scheduling, and also trends, challenges, and opportunities:- Platforms are rapidly increasing in dynamics, with growing adoption of dynamic power management and adaptive scheduling to meet demand-response and other grid needs. There is a growing two-way relationship between datacenters and grids;opportunities abound.- Workloads become more malleable, delay flexible, or even acceptably approximate. AI training workloads are a major example, with hyper-parameter optimization and checkpoints enabling significant flexibility. - The scheduling algorithms and metrics are evolving rapidly, reflecting the interplay between flexible workloads and dynamically varying platforms. New metrics are emerging to capture both performance and non-performance attributes (e.g. carbon emissions), and new notions of progress (model improvement).- Societal concerns about the sustainability of computing have exploded into the public eye with growing resistance and protest against datacenters. Criticism of perpetual growth gives rise to questions about new models of sufficiency, as well as growing awareness, responsibilities, and action.The talks and position papers of the participants are available at https://people.cs.uchicago.edu/~aachien/workshops/varsched25/.