RL-MUL: Multiplier Design Optimization with Deep Reinforcement Learning
RL-MUL: Multiplier Design Optimization with Deep Reinforcement Learning
Multiplication is a fundamental operation in many applications, and multipliers are widely adopted in various circuits. However, optimizing multipliers is challenging and non-trivial due to the huge design space. In this paper, we propose RL-MUL, a multiplier design optimization framework based on reinforcement learning. Specifically, we utilize matrix and tensor …