US 11,768,986 B2
High-dimensional multi-distributed importance sampling for circuit yield analysis
Tom Johansson, Lund (SE); Hemanth Prabhu, Lund (SE); Arturo Prieto Llorens, Lund (SE); and Babak Mohammadi, Lund (SE)
Assigned to XENERGIC AB
Appl. No. 17/438,716
Filed by XENERGIC AB, Lund (SE)
PCT Filed Mar. 13, 2020, PCT No. PCT/EP2020/056890
§ 371(c)(1), (2) Date Sep. 13, 2021,
PCT Pub. No. WO2020/182992, PCT Pub. Date Sep. 17, 2020.
Claims priority of application No. 19162801 (EP), filed on Mar. 14, 2019.
Prior Publication US 2022/0156442 A1, May 19, 2022
Int. Cl. G06F 119/22 (2020.01); G06F 30/33 (2020.01)
CPC G06F 30/33 (2020.01) [G06F 2119/22 (2020.01)] 16 Claims
OG exemplary drawing
 
1. A computer-implemented method for simulation of an integrated circuit for yield analysis of the integrated circuit, the method comprising the steps of:
a) for a plurality of variables, generating initial sampling sets by sampling from distributions, which are based on provided distributions, related to physical properties of the integrated circuits;
b) selecting at least one sample from each initial sampling set randomly and combining the selected samples into an initial simulation set;
c) running an initial simulation of an operation of the integrated circuit, applying the initial simulation set, wherein the operation has a criterion for passing and failing the operation;
d) if the initial simulation fails: storing the samples of the initial simulation set into initial sampling distributions for each variable;
e) repeating steps b)-d) a first number of times;
f) building importance sampling distributions based on each initial sampling distribution, wherein the importance sampling distribution comprises a mixture distribution having three sub-distributions corresponding to a lower portion, a center portion and an upper portion, wherein the three sub-distributions of the importance sampling distribution are transformations of the provided distribution according to a function of the initial sampling distribution for each variable, wherein the transformation of the provided distribution for generation of the importance sampling distribution are given by weighing portions of the initial sampling distribution for each variable;
g) generating a secondary simulation set by drawing a number of samples from the importance sampling distribution for each variable;
h) simulating the integrated circuit by applying the secondary simulation set;
i) repeating steps g)-h) a second number of times;
j) mapping of the resulting yields to the provided distributions, thereby obtaining a yield of the integrated circuit.