SHARP

As the relentless quest for higher throughput and lower energy cost continues in heterogenous multicores, there is a strong demand for energy-efficient and high-performance Network-on-Chip (NoC) architectures. Heterogeneous architectures that can simultaneously utilize both the serialized nature of the CPU as well as the thread level parallelism of the GPU are gaining traction in the industry. A critical issue with heterogeneous architectures is finding an optimal way to utilize the shared resources such as the last level cache and NoC without hindering the performance of either the CPU or the GPU core. Photonic interconnects are a disruptive technology solution that has the potential to increase the bandwidth, reduce latency, and improve energy-efficiency over traditional metallic interconnects. In this article, we propose a CPU-GPU heterogeneous architecture called Shared Heterogeneous Architecture with Reconfigurable Photonic Network-on-Chip (SHARP) that clusters CPU and GPU cores around the same router and dynamically allocates bandwidth between the CPU and GPU cores based on application demands. The SHARP architecture is designed as a Single-Writer Multiple-Reader (SWMR) crossbar with reservation-assist to connect CPU/GPU cores that dynamically reallocates bandwidth using buffer utilization information at runtime. As network traffic exhibits temporal and spatial fluctuations due to application behavior, SHARP can dynamically reallocate bandwidth and thereby adapt to application demands. SHARP demonstrates 34% performance (throughput) improvement over a baseline electrical CMESH while consuming 25% less energy per bit. Simulation results have also shown 6.9% to 14.9% performance improvement over other flavors of the proposed SHARP architecture without dynamic bandwidth allocation.