Adaptive virtual channel partitioning for network-on-chip in heterogeneous architectures

Abstract

Current heterogeneous chip-multiprocessors (CMPs) integrate a GPU architecture on a die. However, the heterogeneity of this architecture inevitably exerts different pressures on shared resource management due to differing characteristics of CPU and GPU cores. We consider how to efficiently share on-chip resources between cores within the heterogeneous system, in particular the on-chip network. Heterogeneous architectures use an on-chip interconnection network to access shared resources such as last-level cache tiles and memory controllers, and this type of on-chip network will have a significant impact on performance. In this article, we propose a feedback-directed virtual channel partitioning (VCP) mechanism for on-chip routers to effectively share network bandwidth between CPU and GPU cores in a heterogeneous architecture. VCP dedicates a few virtual channels to CPU and GPU applications with separate injection queues. The proposed mechanism balances on-chip network bandwidth for applications running on CPU and GPU cores by adaptively choosing the best partitioning configuration. As a result, our mechanism improves system throughput by 15% over the baseline across 39 heterogeneous workloads.