Association for Computing Machinery
With aggressive technology scaling, SRAM design has been seriously challenged by the difficulties in analyzing rare failure events. In this paper, the authors propose to create statistical performance models with accuracy sufficient to facilitate probability extraction for SRAM parametric failures. A piecewise modeling technique is first proposed to capture the performance metrics over the large variation space. A controlled sampling scheme and a nested Monte Carlo analysis method are then applied for the failure probability extraction at cell-level and array-level respectively.