On soft error rate analysis of scaled CMOS designs

Fast-Yet-Accurate Statistical Soft-Error-Rate Analysis Considering Full-Spectrum Charge Collection

“…This section provides an overview of the statistical SER analysis presented in [11]. Figure 4 shows the modified statistical analysis flow appended and considers full-spectrum charge collection, mainly involving cell characterization, signal probability computation, electrical-probability computation, and SER estimation.…”

“…Based on the approach in [11], to enable a better SSER analysis, we need to find more accurate, but efficient, first-strike function strike δ and propagation function prop δ to encompass the process-variation effect. Hence, this study uses a learning with data construction method for statistical model extraction.…”

“…Variations such as, hot carrier injection (HCI), negative bias temperature instability (NBTI), and inter-die channel length variation, on combinational circuits are also analyzed for soft errors in [9] and [10], which have not yet been exercised on large-scale designs. Later, Peng et al [11] propose an accurate statistical soft error rate (SSER) framework built on learning-based statistical models for transient-fault distributions. Using statistical tables for cell models in Monte-Carlo simulation, the work [12] investigates an alternative SSER approach that is more accurate, but runs slower than the previous method [11].…”

“…Later, Peng et al [11] propose an accurate statistical soft error rate (SSER) framework built on learning-based statistical models for transient-fault distributions. Using statistical tables for cell models in Monte-Carlo simulation, the work [12] investigates an alternative SSER approach that is more accurate, but runs slower than the previous method [11]. However, both works [11][12] simplify the SER estimation by injecting only four levels of electrical charges.…”

“…Using statistical tables for cell models in Monte-Carlo simulation, the work [12] investigates an alternative SSER approach that is more accurate, but runs slower than the previous method [11]. However, both works [11][12] simplify the SER estimation by injecting only four levels of electrical charges. Therefore, this study poses a simple, yet important, question, "Are four levels of electrical charges enough to converge SER correctly and properly address the process variation effect?"…”