Optimal Network Topologies and Resource Mappings for Heterogeneous Networks-on-Chip

Abstract

Communication has become a bottleneck for modern microprocessors and multicore chips because metal wires don't scale. The problem becomes worse as the number of components increases and chips become bigger. Traditional Systemson-Chips (SoCs) interconnect architectures are based on shared-bus communication, which can carry only one communication transaction at a time. This limits the communication bandwidth and scalability. Networks-on-Chip (NoC) were proposed as a promising solution for designing large and complex SoCs. The NoC paradigm provides better scalability and reusability for future SoCs, however, longdistance multi-hop communication through traditional metal wires suffers from both high latency and power consumption. A radical solution to address this challenge is to add long-range, low power, and high-bandwidth single-hop links between distant cores. The use of optical or on-chip RF wireless links has been explored in this context. However, all previous work has focused on regular mesh-based metal wire fabrics that were expanded with one or two additional link types only for long-distance communication.In this thesis we address the following main research questions to address the above-mentioned challenges: (1) What library of different link types would represent an optimum in the design space? (2) How would these links be used to design an application-specific NoC architecture? (3) How would applications use the resulting NoC architecture efficiently? We hypothesize that networks with a higher degree of heterogeneity, i.e., three or more link types, will improve the network throughput and consume less energy compared to traditional NoC architectures.In order to verify our hypothesis and to address the research challenges, we design i and analyze optimal heterogeneous networks under different realistic traffic models by considering different cost and performance trade-offs in a comprehensive technology-agnostic simulation framework that uses metaheuristic optimization techniques. As opposed to related work, our heterogeneous links can be placed anywhere in the network, which allows to explore the entire search space. The resulting application-specific networks are then analyzed by using complex network techniques, such as community detection and small-worldness, to understand how heterogeneous link types are used to improve the NoCs performance and cost.Next, we use the application-specific networks as a target architecture for other applications. The goal is to evaluate the performance of our new NoCs for applications they have not been designed for by finding optimal resource allocations.Our results show that there is an optimal number of heterogeneous link types for each set of constraints and that networks with three or more heterogeneous link types provide significantly higher throughput along with lower energy consumption compared to both homogeneous link type and regular 2D mesh networks under three different traffic scenarios. Our evolved networks with three different technology-driven ...