REINFORCED LEARNING FOR TOPOLOGY GENERATION OF A NETWORK-ON-CHIP

原文（中文）

A computer-implemented method includes loading a simplistic network-on-chip (NoC) topology that is fully routed, and performing reinforcement learning on the NoC topology to identify a sequence of topology transformations that will produce a more optimal NoC topology. Performing the reinforcement learning includes running a plurality of training sessions. Running each training session includes using a machine learning model to apply a set of transformations to the NoC topology according to a policy, computing a cost of the NoC topology after the set of transformations has been applied, and updating the policy in response to the cost.