COAST: Congestion-Aware Start-Time Recommendations for Carbon-Aware HPC Jobs

Abstract

High-performance computing (HPC) workloads consume substantial amounts of electricity, and their carbon emissions vary over time with the carbon intensity of grid electricity. However, uncoordinated shifting of carbon-aware HPC jobs toward low-carbon periods can concentrate recommended start times in the same time slots, creating congestion and eroding the resulting carbon benefits. This paper proposes COAST, a congestion-aware start-time recommendation mechanism that coordinates HPC jobs by balancing carbon savings against additional job delay and congestion in recommended start-time slots. COAST formulates each decision batch as an exact potential game, enabling best-response updates to converge to stable start-time recommendations. Under an idealized realization model that assumes each job can start at its recommended time, we conduct trace-driven simulations using public HPC energy data and historical grid carbon-intensity traces. The results show that COAST reduces estimated carbon emissions by 15.4\% with 1.5 hours of additional average start delay. Compared with carbon-greedy start-time recommendations, COAST reduces peak time-slot load by 23.8\% while preserving 93\% of the achievable carbon savings. These results quantify the potential benefits of congestion-aware start-time coordination for flexible, carbon-aware HPC jobs.