標題: Accurate Statistical Soft Error Rate (SSER) Analysis Using A Quasi-Monte Carlo Framework With Quality Cell Models
作者: Kuo, Yu-Hsin
Peng, Huan-Kai
Wen, Charles H. -P.
電機工程學系
Department of Electrical and Computer Engineering
公開日期: 2010
摘要: For CMOS designs in sub 90nm technologies, statistical methods are necessary to accurately estimate circuit SER considering process variations. However, due to the lack of quality statistical models, current statistical SER (SSER) frameworks have not yet achieved satisfactory accuracy. In this work, we present accurate table-based cell models, based on which a Monte Carlo SSER analysis framework is built. We further propose a heuristic to customize the use of quasirandom sequences, which successfully speeds up the convergence of simulation error and hence shortens the runtime. Experimental results show that this framework is capable of more precisely estimating circuit SSERs with reasonable speed.
URI: http://hdl.handle.net/11536/135596
ISBN: 978-1-4244-6455-5
ISSN: 1948-3287
期刊: PROCEEDINGS OF THE ELEVENTH INTERNATIONAL SYMPOSIUM ON QUALITY ELECTRONIC DESIGN (ISQED 2010)
起始頁: 831
結束頁: 838
Appears in Collections:Conferences Paper