TASSER: A Temperature-Aware Statistical Soft-Error-Rate Analysis Framework for Combinational Circuits

Abstract

Soft error has become one of the most critical reliability issues for nano-scaled CMOS designs. Many previous works discovered that the pulse width due to a particle strike on the device increases with temperature, but its system-level effect has not yet been investigated with statistical soft-error-rate (SER). Therefore, in this paper, a combinational circuit (c17 from ISCAS\'85) using a 45nm CMOS technology is f rst observed under different temperatures for SER. As a result, a SER increase (2.16X more) is found on c17 as the ambient temperature elevates from 25 degrees C to 125 degrees C. Second, along with growing design complexity, the operational temperatures of gates are distributed in a wide range and much higher than the ambient temperature in reality. Therefore, we are motivated to build a temperature-aware SSER analysis framework that integrates statistical cell modeling to consider the ambient temperature (T-a) and the temperature variation (T-v), simultaneously. Experimental result shows that our SSER analysis framework is highly effcient (with multiple-order speed-ups) and accurate (with only <4% errors), when compared with Monte-Carlo SPICE simulation.