Reinforced Learning System Optimizes Datacentre Scheduling Agent


MIT researchers have created a reinforced learning (RL) system that can reduced the time needed to complete data-processing operations.

Decima is a RL-based scheduler that could potentiality save firms millions when they run datacentres as it can help to reduce the energy requirement for processing each task.

Normally the fine-tuning of scheduling algorithms is done by humans, however, Decima aims to move most of these decisions over to automation.

Hongzi Mao, a PhD student in the Department of Electrical Engineering and Computer Science (EECS) commented in a blog that: “If you have a way of doing trial and

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