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|Title:||Silica-Embedded Silicon Nanophotonic On-Chip Networks||Authors:||Kakoulli, Elena
|Keywords:||Adaptive Routing Algorithm;Flow-Control;Nanophotonic Network-on-Chip;Silicon-in-Silica;Topology||Category:||Electrical Engineering - Electronic Engineering - Information Engineering||Field:||Engineering and Technology||Issue Date:||Jun-2017||Publisher:||Institute of Electrical and Electronics Engineers Inc.||Source:||IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2017, Volume 36 , Issue 6, Pages 978 - 991||metadata.dc.doi:||https://doi.org/10.1109/TCAD.2016.2611516||Abstract:||On-chip nanophotonics offer high throughput, yet energy-efficient communication, traits that can prove critical to the continuance of multicore chip scalability. In this paper we investigate and propose silicon nanophotonic components that are embedded entirely in the silica (SiO2) substrate, i.e., reside subsurface, as opposed to die on-surface silicon nanophotonics of prior-art. Among several offered advantages, such Siliconin-Silica (SiS) nanophotonic structures empower the implementation of non-obstructive interconnect geometries that deliver an improved power-performance balance, as demonstrated experimentally. First, using exhaustive simulations based on commercial-grade optical software-based tools, we show that such SiS structures are feasible, and derive their geometry characteristics and design parameters. As a second step, utilizing SiS optical channels and filters, we then design two distinct SiS-based nanoPhotonic Network-on-Chip (PNoC) mesh-diagonal links topologies as a means of demonstrating our proof of concept. In further pushing the performance envelope, we next develop (1) an associated contention-aware adaptive routing function, and (2) a parallelized photonic channel allocation scheme, with both coupled to SiS-based PNoCs as elements, to respectively replace under-performing routing and flow-control photonic protocols currently utilized. An extensive experimental evaluation, including utilizing traffic benchmarks gathered from full-system chip multiprocessor simulations, shows that our methodology boosts network throughput by up to 59:7%, reduces communication latency by up to 78:7%, while improving the throughput-to-power ratio by up to 31:6% when compared to the state-of-the-art.||URI:||http://ktisis.cut.ac.cy/handle/10488/9237||ISSN:||02780070||Rights:||© 2016 IEEE.||Type:||Article|
|Appears in Collections:||Άρθρα/Articles|
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