An analytical model to estimate PCM failure probability due to process variations

Author

Chang, Mu-Tien ; Jacob, Bruce

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA

fYear

2011

fDate

26-28 Sept. 2011

Firstpage

174

Lastpage

177

Abstract

Phase change memory (PCM) features nonvolatility, high density, and superior power efficiency, making it one of the most promising candidates for future memory systems. This paper studies the impact of process variations on PCM based on a fast analytical model for determining PCM failure probability. The proposed analytical model takes PCM physical dimensions, programming-current amplitude, and programming duration as inputs and produces the corresponding cell resistance. Whether a PCM cell is functional can be determined by comparing the calculated cell resistance with the reference resistance. We further estimate the overall PCM failure probability and demonstrate strategies on how to minimize memory failures. The proposed model thus provides early stage estimation on memory yield.

Keywords

failure analysis; phase change memories; probability; PCM cell resistance; PCM failure probability; PCM physical dimension; memory failure minimization; memory system; phase change memory feature; process variation; programming duration; programming-current amplitude; reference resistance; superior power efficiency; Analytical models; Electrodes; Phase change materials; Programming; Resistance; Solid modeling; Temperature;

fLanguage

English

Publisher

ieee

Conference_Titel

SOC Conference (SOCC), 2011 IEEE International

Conference_Location

Taipei

ISSN

2164-1676

Print_ISBN

978-1-4577-1616-4

Electronic_ISBN

2164-1676

Type

conf

DOI

10.1109/SOCC.2011.6085128

Filename

6085128