Paper Info
Title
Runtime management of adaptive MPSoCs for graceful degradation.
Abstract
In this paper we propose optimization algorithms for the runtime management of gracefully degradable adaptive MP-SoCs. Assuring the reliability of all hardware components in a system becomes increasingly difficult. On top of the growing defect densities and rising complexity of conventional testing, wear-out effects may reduce the availability of on-chip resources during system lifetime. However, adaptability of modern MPSoCs can provide the means for permanent fault tolerance and graceful degradation via runtime system management. We have developed custom heuristics as well as tailored existing optimization techniques (simulated annealing and genetic algorithm), to deliver a fast and efficient response to unpredictable loss of system resources. We have emulated the resulting runtime manager on the Intel Single-Chip Cloud Computer (SCC), an experimental chip multiprocessor developed by Intel Labs. Comparison of the different algorithms in terms of solution quality and response time, and the scaling of their response time with the size of problem input, indicate that our custom heuristics are faster by at least one order of magnitude, but simulated annealing and genetic algorithm are more consistent in dealing with constraints to the allowed solutions, e.g. limited system reconfiguration time. All algorithms scale well, since their response time, in almost every case, grows sub-linearly with respect to the input size.
Year
DOI
Venue
2016
10.1145/2968455.2968517
CASES
Field
DocType
ISBN
Simulated annealing,Computer science,Parallel computing,Response time,Multiprocessing,Real-time computing,Fault tolerance,Heuristics,Genetic algorithm,Cloud computing,Runtime system,Embedded system
Conference
978-1-5090-3589-2
Citations 
PageRank 
References 
1
0.34
18
Authors
5
Name
Order
Citations
PageRank
Stavros Tzilis193.58
Ioannis Sourdis245644.17
Vasileios Vasilikos361.12
Dimitrios Rodopoulos4569.74
Dimitrios Soudris524348.41