Abstract
Technology scaling over the years has enabled the integration of multi-ple processing cores on a single chip with Network-on-chip (NoC) becoming aninterconnect standard for facilitating large scale connectivity between cores. How-ever, these NoC components, like any other circuit components, are also becomingmore susceptible to faults with further scaling. The ability to adapt and perform re-liably in the presence of these faults is an emerging design challenge for NoC-basedmultiprocessor systems. A crucial requirement for such designs is to effectively de-tect the faults during runtime, in particular with the ability to differentiate betweentemporary and permanent faults. Developing interconnect architectures with online,low-cost fault detection capabilities remains largely unaddressed and is a major de-sign challenge for current and future scalable NoC-based multiprocessor systems.This chapter introduces SMART, a novel "real-time" strategy for detecting faults inNoC interconnect by using biological synapses and neurons to detect temporal andspatial faults. Analysis of fault scenarios and results from real-time experimentson an FPGA implementation of SMART using the example EMBRACE NoC areprovided.
| Original language | English |
|---|---|
| Title of host publication | Energy Efficient Fault Tolerant Systems |
| Editors | J Mathew, RA Shafik, D Pradhan |
| Publisher | Springer |
| Pages | 241-268 |
| ISBN (Print) | 978-1-4614-4192-2 |
| DOIs | |
| Publication status | Published (in print/issue) - 12 Jul 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Networks-on-chip
- Fault detection
- Neural networks
- Hardware
- FPGA
Fingerprint
Dive into the research topics of 'Bio-Inspired Online Fault Detection in NoC Interconnect'. Together they form a unique fingerprint.Student theses
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Scalable hierarchical networks-on-chip architecture for brain-inspired computing
Carrillo L., S. (Author), Harkin, J. (Supervisor) & McDaid, L. (Supervisor), Jan 2013Student thesis: Doctoral Thesis
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