HyPPI NoC: Bringing Hybrid Plasmonics to an Opto-Electronic Network-on-Chip

As we move towards an era of hundreds of cores, the research community has witnessed the emergence of optoelectronic network on-chip designs based on nanophotonics, in order to achieve higher network throughput, lower latencies, and lower dynamic power. However, traditional nanophotonics options face limitations such as large device footprints compared with electronics, higher static power due to continuous laser operation, and an upper limit on achievable data rates due to large device capacitances. Nanoplasmonics is an emerging technology that has the potential for providing transformative gains on multiple metrics due to its potential to increase the light-matter interaction. In this paper, we propose and analyze a hybrid opto-electric NoC that incorporates Hybrid Plasmonics Photonics Interconnect (HyPPI), an optical interconnect that combines photonics with plasmonics. We explore various opto-electronic network hybridization options by augmenting a mesh network with HyPPI links, and compare them with the equivalent options afforded by conventional nanophotonics as well as pure electronics. Our design space exploration indicates that augmenting an electronic NoC with HyPPI gives a performance to cost ratio improvement of up to 1.8×. To further validate our estimates, we conduct trace based simulations using the NAS Parallel Benchmark suite. These benchmarks show latency improvements up to 1.64×, with negligible energy increase. We then further carry out performance and cost projections for fully optical NoCs, using HyPPI as well as conventional nanophotonics. These futuristic projections indicate that all-HyPPI NoCs would be two orders more energy efficient than electronics, and two orders more area efficient than all-photonic NoCs.

I. Introduction and Motivation

With the drive towards an increasing number of cores over the past decade, the field has witnessed network-on-chip (NoC) architectures becoming mainstream in highperformance computing and embedded processors. However, challenges arising from the steadily rising memory demands of applications, as well as the rising power budget for on-chip networks, has led researchers to actively investigate nanophotonics-based opto-electronic networks [1].