The approximate computing paradigm advocates for relaxing accuracy goals in applications to improve energy-efficiency and performance. Recently, this paradigm has been explored to improve the energy efficiency of silicon photonic networks-on-chip (PNoCs). In this paper, we propose a novel framework (LORAX) to enable more aggressive approximation during communication over silicon photonic links in PNoCs. This is the first work that considers loss-aware laser power management and multilevel signaling to enable effective data approximation and energy-efficiency in PNoCs. Simulation results show that our framework can achieve up to 31.4% lower laser power consumption and up to 12.2% better energy efficiency than the best known prior work on approximate communication in PNoCs, for the same application output quality.
|Title of host publication||GLSVLSI 2020 - Proceedings of the 2020 Great Lakes Symposium on VLSI|
|Number of pages||6|
|State||Published - Sep 7 2020|
|Event||30th Great Lakes Symposium on VLSI, GLSVLSI 2020 - Virtual, Online, China|
Duration: Sep 7 2020 → Sep 9 2020
|Name||Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI|
|Conference||30th Great Lakes Symposium on VLSI, GLSVLSI 2020|
|Period||9/7/20 → 9/9/20|
Bibliographical noteFunding Information:
This research was supported by the National Science Foundation (NSF) under grant numbers CCF-1813370 and CCF-2006788.
© 2020 Association for Computing Machinery.
- Approximate computing
- Energy efficiency
ASJC Scopus subject areas
- Engineering (all)