Geometric Deep Reinforcement Learning for Dynamic DAG Scheduling

1 code implementation • 9 Nov 2020 • Nathan Grinsztajn, Olivier Beaumont, Emmanuel Jeannot, Philippe Preux

In this paper, we propose a reinforcement learning approach to solve a realistic scheduling problem, and apply it to an algorithm commonly executed in the high performance computing community, the Cholesky factorization.

Combinatorial Optimization reinforcement-learning +2