SMART-MIG applies MF-MARL for constant-complexity MIG repartitioning plus heuristics for scheduling, reporting 18% better energy-tardiness efficiency than static partitioning and 27% above a theoretical energy lower bound.
MIG User Guide 2014; NVIDIA Multi-Instance GPU User Guide r580 documentation — docs.nvidia.com
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SMART-MIG: A Learning Framework for Scalable and Energy-Efficient GPU Scheduling
SMART-MIG applies MF-MARL for constant-complexity MIG repartitioning plus heuristics for scheduling, reporting 18% better energy-tardiness efficiency than static partitioning and 27% above a theoretical energy lower bound.