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Multi-start point importance sampling technology-based SRAM failure probability quick calculation method

A technology of importance sampling and failure probability, applied in calculation, design optimization/simulation, special data processing applications, etc., can solve problems such as large variance and high sample correlation

Active Publication Date: 2018-02-23
FUDAN UNIV
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Problems solved by technology

However, because the method uses Markov Chain Monte Carlo (Markov Chain Monte Carlo) technology, the correlation between samples is high, and the results obtained have large variance.

Method used

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  • Multi-start point importance sampling technology-based SRAM failure probability quick calculation method
  • Multi-start point importance sampling technology-based SRAM failure probability quick calculation method
  • Multi-start point importance sampling technology-based SRAM failure probability quick calculation method

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Embodiment Construction

[0075] Through the implementation process of specific examples, the method of the present invention is described in detail.

[0076] Implementation example 1

[0077] Using a 6-tube static memory unit, the circuit diagram is as follows image 3 As shown, it is necessary to calculate the failure probability of the memory cell under the process disturbance of the threshold voltage of the transistor. In this example, the threshold voltages Vth1-Vth6 of transistors M1-M6 are disturbed process parameter variables, which is a six-dimensional parameter space solution problem, and the upper and lower bounds of each variable are ±8σ, where σ is the standard deviation of the threshold voltage distribution . Calculate the corresponding failure probability of the three performance parameters of SRAM read current (Iread), static noise margin (SNM), and read noise margin (RNM), and compare with Monte Carlo, MNIS, IBS, and SUS methods .

[0078] By comparing this method with the Monte Ca...

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Abstract

The invention belongs to the field of semiconductor manufacturability design and particularly relates to an SRAM failure probability quick calculation method considering nanometer process disturbance.According to the method, a multi-start point sequence secondary planning algorithm is performed in a parameter space; optimal offset vectors corresponding to multiple failure regions are searched for; an offset probability distribution density function required for importance sampling is built; and the importance sampling is accelerated through an adaptive modeling technology. The method is highin simulation precision and low in simulation frequency, and can achieve the purpose of quick calculation. An SPICE simulation frequency required for estimating an SRAM failure probability and a dimension number of the parameter space roughly form a linear relationship; and compared with the prior art, the method has relatively great advantages in a high-dimensional parameter space.

Description

technical field [0001] The invention belongs to the field of manufacturability design of semiconductors and integrated circuits, and relates to a fast calculation method for SRAM failure probability under the consideration of nanotechnology disturbance. It specifically involves the calculation method of SRAM (static random access memory) failure probability under the condition of nano-process disturbance in the design, especially a method that uses importance sampling technology and adopts the multiple starting point sequence quadratic programming method (Multiple Starting Point-Sequential Quadratic Programming , MSP-SQP) to construct the transition probability density function, which can greatly reduce the sampling amount and obtain the SRAM failure probability that meets the accuracy requirements. Background technique [0002] With the advancement of integrated circuit manufacturing technology to the nanoscale, the robustness and yield problems of integrated circuits cause...

Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 曾璇严昌浩周电王梦硕
Owner FUDAN UNIV
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