论文标题
使用深度加固学习的路由和放置宏
Routing and Placement of Macros using Deep Reinforcement Learning
论文作者
论文摘要
由于这种疏忽，芯片放置一直是任何半导体区域中最耗时的任务之一，因此许多项目被推动，而在实际市场中的筹码可用性被推迟。将宏放置在芯片上的工程师还需要最佳地放置它，以减少三个重要因素，例如功率，性能和时间。看看这些先前的问题，我们想使用强化学习引入一种新方法，我们在其中训练模型以将芯片网表的节点放在芯片画布上。我们希望建立一个神经体系结构，该神经体系结构将正确奖励各种输入网络列表的代理商。
Chip placement has been one of the most time consuming task in any semi conductor area, Due to this negligence, many projects are pushed and chips availability in real markets get delayed. An engineer placing macros on a chip also needs to place it optimally to reduce the three important factors like power, performance and time. Looking at these prior problems we wanted to introduce a new method using Reinforcement Learning where we train the model to place the nodes of a chip netlist onto a chip canvas. We want to build a neural architecture that will accurately reward the agent across a wide variety of input netlist correctly.
