Title
Self-adaptive system for addressing permanent errors in on-chip interconnects
Abstract
We present a self-contained adaptive system for detecting and bypassing permanent errors in on-chip interconnects. The proposed system reroutes data on erroneous links to a set of spare wires without interrupting the data flow. To detect permanent errors at runtime, a novel in-line test (ILT) method using spare wires and a test pattern generator is proposed. In addition, an improved syndrome storing-based detection (SSD) method is presented and compared to the ILT method. Each detection method (ILT and SSD) is integrated individually into the noninterrupting adaptive system, and a case study is performed to compare them with Hamming and Bose-Chaudhuri-Hocquenghem (BCH) code implementations. In the presence of permanent errors, the probability of correct transmission in the proposed systems is improved by up to 140% over the standalone Hamming code. Furthermore, our methods achieve up to 38% area, 64% energy, and 61% latency improvements over the BCH implementation at comparable error performance.
Year
DOI
Venue
2010
10.1109/TVLSI.2009.2013711
VLSI) Systems, IEEE Transactions
Keywords
Field
DocType
proposed system reroutes data,self-adaptive system,self-contained adaptive system,spare wire,detection method,ilt method,noninterrupting adaptive system,bch implementation,proposed system,permanent error,on-chip interconnects,code implementation,network on chip,information technology,adaptive systems,forward error correction,reliability,bch code,adaptive system,automatic test pattern generation,fault tolerance,hamming codes,system on a chip,data flow,hamming code,error correction,testing,chip,fault tolerant,bch codes
Automatic test pattern generation,Hamming code,Forward error correction,System on a chip,Computer science,Adaptive system,Electronic engineering,Error detection and correction,BCH code,Hamming distance
Journal
Volume
Issue
ISSN
18
4
1063-8210
Citations 
PageRank 
References 
38
1.01
20
Authors
5
Name
Order
Citations
PageRank
Teijo Lehtonen11579.93
David H. Wolpert24334591.07
Pasi Liljeberg3114792.79
Juha Plosila495683.79
Paul Ampadu528528.55