Browsing by Author "Chang, Austin C. -C."

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Aging-aware Statistical Soft-Error-Rate Analysis for Nano-Scaled CMOS Designs
(2013-01-01)
Lin, Cosette Y. H.
;
Huang, Ryan H. -M.
;
Wen, Charles H. -P.
;
Chang, Austin C. -C.
;
電機工程學系
Aging and soft errors have become the two most critical reliability issues for nano-scaled CMOS designs. In this paper, the aging effect due to negative bias temperature instability (NBTI) is first analyzed on cells using a 45nm CMOS technology for soft errors. Second, an accurate statistical soft-error-rate (SSER) framework is built and incorporates the aging-aware cell models. As a result, two findings are discovered: (1) PMOS-induced transient faults, comparing to NMOS-induced ones, have more variation in pulse widths since PMOS is more susceptible to NBTI; (2) NBTI together with process variation, induces more soft errors (similar to 19%) and thus needs to be considered, simultaneously, during circuit analysis. Experimental result shows that our SSER framework considering both process variation and aging is efficient (with multiple-order speedups) and achieves high accuracy (with <3% errors) when compared with Monte-Carlo SPICE simulation.
Aging-aware Statistical Soft-Error-Rate Analysis for Nano-Scaled CMOS Designs
(2013)
Lin, Cosette Y. H.
;
Huang, Ryan H. -M.
;
Wen, Charles H. -P.
;
Chang, Austin C. -C.
;
電機資訊學士班
Aging and soft errors have become the two most critical reliability issues for nano-scaled CMOS designs. In this paper, the aging effect due to negative bias temperature instability (NBTI) is first analyzed on cells using a 45nm CMOS technology for soft errors. Second, an accurate statistical soft-error-rate (SSER) framework is built and incorporates the aging-aware cell models. As a result, two findings are discovered: (1) PMOS-induced transient faults, comparing to NMOS-induced ones, have more variation in pulse widths since PMOS is more susceptible to NBTI; (2) NBTI together with process variation, induces more soft errors (similar to 19%) and thus needs to be considered, simultaneously, during circuit analysis. Experimental result shows that our SSER framework considering both process variation and aging is efficient (with multiple-order speedups) and achieves high accuracy (with <3% errors) when compared with Monte-Carlo SPICE simulation.
CASSER: A Closed-Form Analysis Framework for Statistical Soft Error Rate
(2013-10-01)
Chang, Austin C. -C.
;
Huang, Ryan H. -M.
;
Wen, Charles H. -P.
;
電機資訊學士班
;
Undergraduate Honors Program of Electrical Engineering and Computer Science
CMOS designs in the deep submicrometer era require statistical methods to accurately estimate the circuit soft error rate (SER). However, process variation increases the complexity of statistical characteristics related to transient faults, leading to considerable uncertainty in the behavior of soft errors. Regardless of the methods used, current statistical SER (SSER) frameworks invariably involve a tradeoff between accuracy and efficiency. This paper presents accurate cell models in first-order closed form to overcome this problem, thereby enabling the analysis of SSERs in a block-based fashion similar to statistical static timing analysis. These cell models are derived as a closed form in the proposed framework named CASSER, and remain precise under the assumption of a normal distribution for the process parameters. Experimental results demonstrate the efficiency (> 2-order times faster than the latest framework) and accuracy (< 3% error) of CASSER in estimating circuit SERs, when compared with the Monte Carlo SPICE simulation.