Efficient method and computer program for modeling and improving static memory performance across process variations and environmental conditions

Abstract

An efficient method and computer program for modeling and improving stating memory performance across process variations and environmental conditions provides a mechanism for raising the performance of memory arrays beyond present levels/yields. Statistical (Monte-Carlo) analyses of subsets of circuit parameters are performed for each of several memory performance variables and then sensitivities of each performance variable to each of the circuit parameters are determined. The memory cell design parameters and/or operating conditions of the memory cells are then adjusted in conformity with the sensitivities, resulting in improved memory yield and/or performance. Once a performance level is attained, the sensitivities can then be used to alter the probability distributions of the performance variables to achieve a higher yield. Multiple cell designs can be compared for performance, yield and sensitivity of performance variables to circuit parameters over particular environmental conditions in order to select the best cell design.