STATIC TIMING ANALYSIS OF THE NON-GAUSSIAN VARIATION SOURCES FOR VLSI CIRCUITS

SSTA requires accurate statistical distribution models of non-Gaussian random variables of process parameters and timing variables. As CMOS technology scales down, process variation introduces significant uncertainty in power and performance to VLSI circuits and significantly affects their reliability. Although Static- Timing Analysis (STA) it is an excellent tool, but current trends in process scaling have imposed significant difficulties to STA. As one of the promising solutions, Statistical static timing analysis (SSTA) has become the frontier research topic in recent years in combating such variation effects. This paper will be focusing on two aspects of SSTA and its applications in VLSI designs: (1) Statistical timing modeling and analysis; and (2) Architectural implementations of the atomic operations (max and add). Experimental results have shown that our approach can provide 282 times speedup when compared to a conventional CPU implementation.