Subho Banerjee

Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters

The problem of scheduling of workloads onto heterogeneous processors (e.g., CPUs, GPUs, FPGAs) is of fundamental importance in modern data centers. Current system schedulers rely on application/system-specific heuristics that have to be built on a case-by-case basis. Recent work has demonstrated ML…