STATISTICAL SPICE MODEL PARAMETER CALCULATION METHOD, AND STATISTICAL SPICE MODEL PARAMETER CALCULATION DEVICE AND PROGRAM
A statistical SPICE model parameter calculation method in which it is possible to create a variation model having high accuracy and size dependency. A principal component analysis is performed, for respective device sizes, of a measurement of an element characteristic value of a semiconductor device on which multipoint measurement is performed (principal component analysis process). A statistical SPICE model parameter that reproduces variation of an element characteristic value for a plurality of device sizes is calculated based on a result of the principal component analysis obtained for each of the device sizes and predetermined device size dependency (parameter calculation process).
1 . A statistical SPICE model parameter calculation method comprising:
a principal component analysis process of performing a principal component analysis, for respective device sizes, of a measurement of an element characteristic value of a semiconductor device on which multipoint measurement is performed; and
a parameter calculation process of computing a statistical SPICE model parameter that reproduces variation of an element characteristic value for a plurality of device sizes, based on a result of said principal component analysis obtained for each of said device sizes and a predetermined device size dependency.
2 . The statistical SPICE model parameter calculation method according to claim 1 , further comprising a principal component adjustment process of arranging principal component directions of any 2 device sizes obtained by said principal component analysis, and principal component order.
3 . The statistical SPICE model parameter calculation method according to claim 1 , wherein a response of a SPICE model, in a case where a prescribed element characteristic value is changed, is used to calculate said statistical SPICE model parameter.
4 . The statistical SPICE model parameter calculation method according to claim 1 , wherein a measurement taken from a different sample is included in measurements of said element characteristic value of said semiconductor device on which multipoint measurement is performed.
5 . The statistical SPICE model parameter calculation method according to claim 1 , wherein a measurement taken from said different sample is used to create a variation model according to a common sample variation cause, and a sample-specific variation model, and a parameter obtained from each of said variation models is added to calculate a statistical SPICE model parameter.
6 . The statistical SPICE model parameter calculation method according to claim 1 , comprising:
obtaining a random variation statistical SPICE model parameter,
with a variation obtained by deducting said random variation from variation of a measurement obtained from a plurality of samples as input, obtaining a non-random statistical SPICE model parameter, and
calculating a statistical SPICE model parameter that reproduces each of said random variation and said non-random variation.
7 . A statistical SPICE model parameter calculation device comprising:
a principal component analysis unit that performs principal component analysis, for respective device sizes, of a measurement of an element characteristic value of a semiconductor device on which multipoint measurement is performed; and
a parameter calculation unit that calculates a statistical SPICE model parameter which reproduces variation of an element characteristic value for a plurality of device sizes, based on a result of said principal component analysis obtained for each of said device sizes, and a predetermined device size dependency.
8 . The statistical SPICE model parameter calculation device according to claim 7 , further comprising a principal component adjustment unit that arranges principal component directions of any 2 device sizes obtained by said principal component analysis, and principal component order.
9 . The statistical SPICE model parameter calculation device according to claim 7 , wherein said parameter calculation unit uses a response of a SPICE model, in a case where a prescribed element characteristic value is changed, to calculate said statistical SPICE model parameter.
10 . The statistical SPICE model parameter calculation device according to claim 7 , further comprising an input unit that inputs a measurement of an element characteristic value of a semiconductor device taken from a different sample.
11 . The statistical SPICE model parameter calculation device according to claim 7 , wherein a measurement taken from said different sample is used to create a variation model according to a common sample variation cause, and a sample-specific variation model, and a parameter obtained from each of said variation models is added to calculate a statistical SPICE model parameter.
12 . The statistical SPICE model parameter calculation device according to claim 7 , wherein
a random variation statistical SPICE model parameter is obtained from a predetermined sample,
with a variation obtained by deducting said random variation from variation of a measurement obtained from a plurality of samples as input, a non-random variation statistical SPICE model parameter is obtained, and
a statistical SPICE model parameter that reproduces each of said random variation and said non-random variation is calculated.
13 . A statistical SPICE model parameter calculation program coupled with a computer memory that executes on a computer:
a process of performing a principal component analysis, for respective device sizes, of a measurement of an element characteristic value of a semiconductor device on which multipoint measurement is performed; and
a process of calculating a statistical SPICE model parameter that reproduces variation of an element characteristic value for a plurality of device sizes, based on a result of said principal component analysis obtained for each of said device sizes, and a predetermined device size dependency.
14 . The statistical SPICE model parameter calculation program according to claim 13 , wherein said program further executes on a computer:
a process of arranging principal component directions of any 2 device sizes obtained by said principal component analysis, and principal component order.
15 . The statistical SPICE model parameter calculation program according to claim 13 , wherein said program further uses a response of a SPICE model, in a case where a prescribed element characteristic value is changed, to calculate said statistical SPICE model parameter.
16 . The statistical SPICE model parameter calculation program according to claim 13 , wherein said program uses a measurement taken from said different sample to create a variation model according to a common sample variation cause, and a sample-specific variation model, and adds a parameter obtained from each of said variation models to calculate a statistical SPICE model parameter.
17 . The statistical SPICE model parameter calculation program according to claim 13 , wherein said program
obtains a random variation statistical SPICE model parameter from a predetermined sample,
with a variation obtained by deducting said random variation from variation of a measurement obtained from a plurality of samples as input, obtains a non-random statistical SPICE model parameter, and
calculates a statistical SPICE model parameter that reproduces each of said random variation and said non-random variation.
18 . A circuit simulation method that performs circuit simulation by calculating a statistical SPICE model parameter by said statistical SPICE model parameter calculation method according to claim 1 , and using said statistical SPICE model parameter.
19 . A circuit simulation device including said statistical SPICE model parameter calculation device according to claim 7 , wherein circuit simulation is performed using a statistical SPICE model parameter calculated by said statistical SPICE model parameter calculation device.