Title
Addressing network-on-chip router transient errors with inherent information redundancy
Abstract
We exploit the inherent information redundancy in the control path of Network-on-Chip (NoC) routers to manage transient errors, preventing packet loss and misrouting. Outputs of the routing arbitration units in NoC routers can be used to determine arbitration failures, because the valid arbitration outputs are a subset of all possible values. This feature is exploited to detect and correct logic and register errors in the router arbitration control path. The proposed method is complementary to other error management methods for NoC routers. An analytical reliability model of our method is provided, including parameters such as logic unit size, different error rates for logic gates and registers, and the location of faulty elements. Compared to triple-modular redundancy (TMR), the proposed method improves the arbiter reliability by two orders of magnitude while reducing the total area and power by 43% and 64%, respectively. In the presented case studies, two traffic traces from the PARSEC benchmark suite are used to evaluate the average latency and energy consumption. Simulations performed on a 4× 4 NoC show that our method reduces the average latency by up to 50% and reduces average energy by up to 70% compared to other methods.
Year
DOI
Venue
2013
10.1145/2485984.2485993
ACM Trans. Embedded Comput. Syst.
Keywords
Field
DocType
routing arbitration unit,valid arbitration output,noc routers,average latency,average energy,inherent information redundancy,network-on-chip router transient error,arbitration failure,router arbitration control path,noc show,error management method,triple modular redundancy
Arbiter,Logic gate,Parsec,Computer science,Parallel computing,Triple modular redundancy,Network on a chip,Packet loss,Real-time computing,Redundancy (engineering),Router
Journal
Volume
Issue
ISSN
12
4
1539-9087
Citations 
PageRank 
References 
6
0.45
24
Authors
3
Name
Order
Citations
PageRank
Qiaoyan Yu117428.58
Meilin Zhang2403.16
Paul Ampadu328528.55