Silica-Embedded Silicon Nanophotonic On-Chip Networks.
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| Title: | Silica-Embedded Silicon Nanophotonic On-Chip Networks. |
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| Authors: | Kakoulli, Elena1, Soteriou, Vassos1, Koutsides, Charalambos1, Kalli, Kyriacos1 |
| Source: | IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems. Jun2017, Vol. 36 Issue 6, p978-991. 14p. |
| Subjects: | Nanophotonic integrated circuits, Multicore processors, Silicon compounds, Photonics, Optical waveguides |
| 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 silicon-in-silica (SiS) nanophotonic structures empower the implementation of nonobstructive 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. [ABSTRACT FROM PUBLISHER] |
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| Database: | Engineering Source |
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