Thermal-Safe Test Scheduling for Core-Based System-on-a-Chip Integrated Circuits

Overheating has been acknowledged as a major problem during the testing of complex system-on-chip (SOC) integrated circuits. Several power-constrained test scheduling solutions have been recently proposed to tackle this problem during system integration. However, we show that these approaches cannot...

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Bibliographic Details
Main Authors: Rosinger, Paul (Author), Al-Hashimi, Bashir (Author), Chakrabarty, Krishnendu (Author)
Format: Article
Language:English
Published: 2005-11.
Subjects:
Online Access:Get fulltext
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100 1 0 |a Rosinger, Paul  |e author 
700 1 0 |a Al-Hashimi, Bashir  |e author 
700 1 0 |a Chakrabarty, Krishnendu  |e author 
245 0 0 |a Thermal-Safe Test Scheduling for Core-Based System-on-a-Chip Integrated Circuits 
260 |c 2005-11. 
856 |z Get fulltext  |u https://eprints.soton.ac.uk/261582/1/main.pdf 
520 |a Overheating has been acknowledged as a major problem during the testing of complex system-on-chip (SOC) integrated circuits. Several power-constrained test scheduling solutions have been recently proposed to tackle this problem during system integration. However, we show that these approaches cannot guarantee hot-spot-free test schedules because they do not take into account the non-uniform distribution of heat dissipation across the die and the physical adjacency of simultaneously active cores. This paper proposes a new test scheduling approach that is able to produce short test schedules and guarantee thermal-safety at the same time. Two thermal-safe test scheduling algorithms are proposed. The first algorithm computes an exact (shortest) test schedule that is guaranteed to satisfy a given maximum temperature constraint. The second algorithm is a heuristic intended for complex systems with a large number of embedded cores, for which the exact thermal-safe test scheduling algorithm may not be feasible. Based on a low-complexity test session thermal cost model, this algorithm produces near-optimal length test schedules with significantly less computational effort compared to the optimal algorithm. 
655 7 |a Article