DPBC-VCP: A Network-On-Chip Prioritization Mechanism Combined with VCP for CPU-GPU Heterogeneous Systems

When executing CPU and GPU applications in CPU-GPU heterogeneous systems, a common phenomenon arises where CPU applications performance is often interfered by GPU applications. This study substantiates this observation through an analysis of resource contention and identifies the limitations of the Virtual Channel Partitioning (VCP) approach in the crossbar switch allocation stage. In response to the resource contention problem in crossbar switch allocation stage, we propose a Probability-Based CPU-first Arbitration Strategy that enhances the priority of CPU packets in contention through specific probabilities. Furthermore, we introduce a Dynamic Probability-Based CPU-first Arbitration Strategy (DPBC) that dynamically selects probability values based on application execution phases to strike a balance between optimal CPU and GPU performance. Moreover, we combine this dynamic strategy with VCP to further enhance CPU performance, propose the DPBC-VCP method. The DPBC-VCP, a combination of network partitioning and prioritization techniques, yields an average enhancement of 48% in CPU performance compared to the baseline, with only a marginal 2.45% reduction in GPU performance.