Genetic Algorithm-based thermal uniformity–aware X-filling to reduce peak temperature during testing

High temperature occurs in testing of complex System-on-Chip designs and it may become a critical concern to be carefully taken into account with continual development in Very Large Scale Integration technology. Peak temperature significantly affects the reliability and the performance of the chip....

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Main Authors: Arulmurugan Azhaganantham, Murugesan Govindasamy
Format: Article
Language:English
Published: SAGE Publishing 2018-09-01
Series:Measurement + Control
Online Access:https://doi.org/10.1177/0020294018784969
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spelling doaj-e001cbe956e74de597c4798665fcb2012020-11-25T03:03:21ZengSAGE PublishingMeasurement + Control0020-29402018-09-015110.1177/0020294018784969Genetic Algorithm-based thermal uniformity–aware X-filling to reduce peak temperature during testingArulmurugan AzhagananthamMurugesan GovindasamyHigh temperature occurs in testing of complex System-on-Chip designs and it may become a critical concern to be carefully taken into account with continual development in Very Large Scale Integration technology. Peak temperature significantly affects the reliability and the performance of the chip. So it is essential to minimize the peak temperature of the chip. Heat generation by power consumption and heat dissipation to the surrounding blocks are the two prominent factors for the peak temperature. Power consumption can be minimized by a careful mapping of don’t cares in precomputed test set. However, it does not provide the solution to peak temperature minimization because the non-uniformity in spatial power distribution may create localized heating event called “hotspot.” The peak temperature on the hotspot is minimized by Genetic Algorithm–based don’t care filling technique that reduces the non-uniformity in spatial power distribution within the circuit under test while maintaining the overall power consumption at a lower level. Experimental results on ISCAS89 benchmark circuits demonstrate that 6%–28% peak temperature reduction can be achieved.https://doi.org/10.1177/0020294018784969
collection DOAJ
language English
format Article
sources DOAJ
author Arulmurugan Azhaganantham
Murugesan Govindasamy
spellingShingle Arulmurugan Azhaganantham
Murugesan Govindasamy
Genetic Algorithm-based thermal uniformity–aware X-filling to reduce peak temperature during testing
Measurement + Control
author_facet Arulmurugan Azhaganantham
Murugesan Govindasamy
author_sort Arulmurugan Azhaganantham
title Genetic Algorithm-based thermal uniformity–aware X-filling to reduce peak temperature during testing
title_short Genetic Algorithm-based thermal uniformity–aware X-filling to reduce peak temperature during testing
title_full Genetic Algorithm-based thermal uniformity–aware X-filling to reduce peak temperature during testing
title_fullStr Genetic Algorithm-based thermal uniformity–aware X-filling to reduce peak temperature during testing
title_full_unstemmed Genetic Algorithm-based thermal uniformity–aware X-filling to reduce peak temperature during testing
title_sort genetic algorithm-based thermal uniformity–aware x-filling to reduce peak temperature during testing
publisher SAGE Publishing
series Measurement + Control
issn 0020-2940
publishDate 2018-09-01
description High temperature occurs in testing of complex System-on-Chip designs and it may become a critical concern to be carefully taken into account with continual development in Very Large Scale Integration technology. Peak temperature significantly affects the reliability and the performance of the chip. So it is essential to minimize the peak temperature of the chip. Heat generation by power consumption and heat dissipation to the surrounding blocks are the two prominent factors for the peak temperature. Power consumption can be minimized by a careful mapping of don’t cares in precomputed test set. However, it does not provide the solution to peak temperature minimization because the non-uniformity in spatial power distribution may create localized heating event called “hotspot.” The peak temperature on the hotspot is minimized by Genetic Algorithm–based don’t care filling technique that reduces the non-uniformity in spatial power distribution within the circuit under test while maintaining the overall power consumption at a lower level. Experimental results on ISCAS89 benchmark circuits demonstrate that 6%–28% peak temperature reduction can be achieved.
url https://doi.org/10.1177/0020294018784969
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