Proceedings of the 23rd Symposium on Integrated Circuits and System Design 2010
DOI: 10.1145/1854153.1854171
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Generating power-hungry test programs for power-aware validation of pipelined processors

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Cited by 4 publications
(12 citation statements)
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“…In this paper we propose an inexpensive technique 2 A decision-point is a point that a module's state (testing/heating/cooling) or test/heating node may change. (a) 22 to order the tests and heating sequences so that required temperature cycling effects can be achieved without the use of temperature chambers in a short time.…”
Section: Discussionmentioning
confidence: 99%
See 2 more Smart Citations
“…In this paper we propose an inexpensive technique 2 A decision-point is a point that a module's state (testing/heating/cooling) or test/heating node may change. (a) 22 to order the tests and heating sequences so that required temperature cycling effects can be achieved without the use of temperature chambers in a short time.…”
Section: Discussionmentioning
confidence: 99%
“…But, in order to have more effective heating sequences, input stimuli that generate even larger switching activities must be found. Authors in [22] have introduced an automated framework for finding high power test programs. The proposed approach is based on a meta-heuristic that generates alternative test programs and evaluates their power consumption.…”
Section: Temperature Cycling and Scheduling Techniquesmentioning
confidence: 99%
See 1 more Smart Citation
“…Moreover, specialized techniques for this purpose can be developed. These methods are, in essence, similar to [9]. The authors in [9] introduced a power-hungry test stimulus generation technique.…”
Section: Temperature-gradient Based Burn-in a Preliminaries Andmentioning
confidence: 99%
“…These methods are, in essence, similar to [9]. The authors in [9] introduced a power-hungry test stimulus generation technique. The produced stimuli cause large switching activity which results in large power density and high temperature.…”
Section: Temperature-gradient Based Burn-in a Preliminaries Andmentioning
confidence: 99%