A Method for Fast Calculation of SRAM Failure Probability Using Adaptive Mesh Division and Sliding Window Technique

An adaptive grid and sliding window technology, applied in computing, special data processing applications, instruments, etc., can solve the problem of low precision

Inactive Publication Date: 2019-12-20
FUDAN UNIV
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Problems solved by technology

[0009] In terms of the spherical coordinate method, Fonseca et al. [22] proposed a spherical sampling method, which samples the radial direction of the spherical ball through simple Monte-Carlo, and then calculates the failure point in the radial direction of the radius, but the accuracy of this method is low

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  • A Method for Fast Calculation of SRAM Failure Probability Using Adaptive Mesh Division and Sliding Window Technique
  • A Method for Fast Calculation of SRAM Failure Probability Using Adaptive Mesh Division and Sliding Window Technique
  • A Method for Fast Calculation of SRAM Failure Probability Using Adaptive Mesh Division and Sliding Window Technique

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Embodiment Construction

[0116] Now, the method of the present invention will be described through the implementation process of specific examples.

[0117] Implementation example 1

[0118] The circuit that the inventive method adopts is as Figure 8 As shown, the calculated SRAM cell read failure is compared with the Monte Carlo method and YENSS, tangent method, MIS, MNIS, and SCC. In this example, the ranges of threshold voltages Vth1 and Vth5 of transistors M1 and M5 are both [0V, 0.8V]. This is a two-dimensional parameter space solution problem. Firstly through the spherical coordinate transformation, as shown in formula (10).

[0119] V th1 =r×sinθ,V th5 =r×cosθ, 0≤θ<2π (10)

[0120] where θ 1 and θ 2 Spherical coordinate angle range. In this example, the initial value of r is 1, θ is divided into 10 cells, and the obtained boundary curve g boundary As shown in formula (11).

[0121] g boundary =g(r,θ),θ 1 ≤θ≤θ 2 (11)

[0122] The SRAM unit read failure obtained by this method is ...

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Abstract

The invention belongs to the field of semiconductor manufacturability design, and specifically relates to a simulation method for rapidly calculating the SRAM failure probability by considering the deep sub-micrometer technology disturbance. In the method, the spheroid transformation is carried out in a parameter space, and the self-adaption grid division and slide window technology is adopted, the technology can greatly reduce the sampling amount, obtain the SRAM failure probability conforming to the accuracy requirement and the failure boundary information of the parameter space. The precise SPICE simulation is adopted, empirical and semi-empirical models are not depended on. In the simulation process, the precision is high, and the simulation frequency is low, so the rapid calculation is achieved. The SRAM failure probability can be obtained, and the parameter space failure boundary distribution is also obtained, the optimization design of the circuit is benefited.

Description

technical field [0001] The invention belongs to the field of SRAM failure probability calculation considering nano-technology disturbance in semiconductor design, and in particular relates to a method of performing ellipsoid transformation in parameter space and adopting adaptive grid division and sliding window method, which can greatly reduce sampling Quantity, to obtain the SRAM failure probability that meets the accuracy requirements. Background technique [0002] As the feature size of nanoscale integrated circuit manufacturing process continues to decrease, process disturbance and random deviation significantly affect the performance of the circuit [1, 2]. In SRAM circuit design, SRAM memory cells are generally designed with the smallest size [3], so that the design margin is small; at the same time, an SRAM chip contains millions of memory cells, even if the failure probability of a memory cell is high, the SRAM chip The probability of failure may also not meet the d...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/50
Inventor 曾璇严昌浩王胜国吴震宇
Owner FUDAN UNIV
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