TB-TBP: a task-based adaptive routing algorithm for network-on-chip in heterogenous CPU-GPU architectures
Juan Fang, Zhichao Wei, Yaqi Liu, Yumin Hou
Abstract
Abstract With the rapid development of heterogeneous network-on-chip (NoC), a vast amount of shared resources are integrated into NoC. Intense resource competition exists between CPUs and GPUs, leading to congestion and a decrease in overall network performance. Reasonable node placement can minimize network conflicts at the topology level. This paper first discusses the placement of shared last-level cache and memory controller, then selects a more rational placement method and optimizes the path. To solve the hot spots problem in center placement method, a task-based routing algorithm is designed to plan the path. Simulation results demonstrate that, compared to the traditional routing algorithm, the overall network latency is reduced by 9%, and the CPU performance is improved by 13.6%. Furthermore, a dynamic task-based routing algorithm is proposed. Compared to the static task routing algorithm, the overall network latency is reduced by 2.08%, and the CPU performance is improved by 4.09%.