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Temperature-Gradient Based Burn-In for 3D Stacked ICs
Linköping University, Department of Computer and Information Science, ESLAB - Embedded Systems Laboratory. Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science, ESLAB - Embedded Systems Laboratory. Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science, ESLAB - Embedded Systems Laboratory. Linköping University, Department of Computer and Information Science, Software and Systems. Linköping University, The Institute of Technology.
2013 (English)In: The 12th Swedish System-on-Chip Conference (SSoCC 2013), Ystad, Sweden, May 6-7, 2013 (not reviewed, not printed)., 2013Conference paper, Oral presentation only (Other academic)
Abstract [en]

3D Stacked IC fabrication, using Through-Silicon-Vias, is a promising technology for future integrated circuits. However, large temperature gradients may exacerbate early-life-failures to the extent that the commercialization of 3D Stacked ICs is challenged. The effective detection of these early-life-failures requires that burn-in is performed when the IC’s temperatures comply with the thermal maps that properly specify the temperature gradients. In this paper, two methods that efficiently generate and maintain the specified thermal maps are proposed. The thermal maps are achieved by applying heating and cooling intervals to the chips under test through test access mechanisms. Therefore, no external heating system is required. The scheduling of the heating and cooling intervals is based on thermal simulations. The schedule generation is guided by functions that are derived from the temperature equations. Experimental results demonstrate the efficiency of the proposed method.

Place, publisher, year, edition, pages
2013.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-92594OAI: oai:DiVA.org:liu-92594DiVA: diva2:621303
Conference
SSoCC'13
Available from: 2013-05-14 Created: 2013-05-14 Last updated: 2013-05-14

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