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With technology scaling down, hundreds and thousands processing elements (PEs) can be integrated on a single chip. Network-on-chip (NoC) has been proposed as an efficient solution to handle this distinctive challenge. In this thesis, we have explored the high performance NoC design for MPSoC and CMP structures from the performance modeling in the offline design phase to the routing algorithm and NoC architecture optimization. More specifically, we first deal with the issue of how to estimate an NoC design fast and accurately in the synthesis inner loop. For this purpose, we propose a machine learning based latency regression model to evaluate the NoC designs with respect to different configurations. Then, for high performance NoC designs, we tackle one of the most important problems, i.e., the routing algorithms design. For avoiding temperature hotspots, a thermal-aware routing algorithm is proposed to achieve an even temperature profile for application-specific Network-on-chips (NoCs). For improving the reliability, a routing algorithm to achieve maximum performance under fault is proposed. Finally, in the architecture level, we propose two new NoC structures using bi-directional links for the performance optimization. In particular, we propose a flit-level speedup scheme to enhance the network-on-chip(NoC) performance utilizing bidirectional channels. We also propose a flexible NoC architecture which takes advantage of a dynamic distributed routing algorithm and improves the NoC communication performance with moderate energy overhead. From the simulation results on both synthetic traffic and real workload traces, significant performance improvement in terms of latency and throughput can be achieved.

High performance network-on-chips (NoCs) design : performance modeling, routing algorithm and architecture optimization