IP Library › Granted Patent US 12,320,844
Granted Patent B2
US 12,320,844 · App. 18/369,171 · Granted Jun 3, 2025

Integrated circuit profiling and anomaly detection

Inventors: Evelyn Landman (Haifa, IL); Yahel David (Kibbutz Gazit, IL); Eyal Fayneh (Givatayim, IL); Shai Cohen (Haifa, IL); Yair Talker (Binyamina, IL)
Assignee: PROTEANTECS LTD.
G01R31/31707G01R31/2803G01R31/2894G01R31/31718G06N3/08G06N7/01
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Quick Facts
Patent No.
US 12,320,844
App. No.
18/369,171
Granted
Jun 3, 2025
Kind
B2
Abstract

A computerized method for IC classification, outlier detection and/or anomaly detection comprising using at least one hardware processor for testing each of the plurality of ICs in accordance with an IC design on a wafer, wherein the IC design comprises a plurality of sensors. The at least one hardware processor is used for testing each of the plurality of ICs by: collecting a plurality of sensor values, the plurality of sensor values including sensor values from each of the plurality of sensors; comparing the plurality of sensor values to a classification scheme, thereby obtaining a classification for each tested IC; and recording the classification of the tested IC.

Claims (71)

1. A computer program product comprising computer readable instructions that are configured, when operated on at least one hardware processor, to:

collect at least one sensor value from each of a plurality of sensors that are comprised in multiple Integrated Circuit (IC) dies that are manufactured according to a common IC design, wherein the at least one sensor value is indicative of field performance of the respective IC die; and

classify each of the multiple IC dies based on the field performance indicated by the at least one sensor value.

2. The computer program product of claim 1 , wherein the instructions are further configured to compare the collected at least one sensor value to a classification scheme, thereby enabling the classification of each of the multiple IC dies.

3. The computer program product of claim 2 , wherein the classification scheme is based on at least one of:

simulations of a plurality of IC operations of the common IC design and a fabrication process, wherein the simulations are selected from the group consisting of: at least one complete IC design simulation, at least one partial IC design simulation, and at least one device simulation for the fabrication process;

a plurality of training sensor values collected during a pre-production tape-out test; or

the collected at least one sensor value.

4. The computer program product of claim 2 , wherein the comparing comprises:

estimating high coverage measurements from the collected at least one sensor value using a function and/or a rule that are determined from a training set of: sensor values, and training high coverage measurements.

5. The computer program product of claim 1 , wherein the instructions are further configured to:

(i) from each of the IC dies, determine a set of parameters of a fabrication process based on the classification and the collected at least one sensor value; and

(ii) select a second set of parameters of the fabrication process based on the common IC design and the sets of parameters of the fabrication process for each of the IC dies,

to enable manufacturing additional IC dies using the second set of parameters.

6. The computer program product of claim 2 , wherein the instructions are further configured to:

determine the classification scheme based on a plurality of classification values by:

establishing a matrix representation from the plurality of classification values, each row of the matrix representation comprising classification values in respect of one of the IC dies;

computing a covariance matrix from the matrix representation and a singular value decomposition (SVD) for the covariance matrix;

determining, using the SVD, a plurality of distance values, each distance value representing a respective distance between one of the IC dies and another one of the IC dies; and

identifying, from the plurality of distance values, at least one family, thereby defining the classification scheme.

7. The computer program product of claim 6 , wherein the step of identifying comprises:

classifying a first IC die of the IC dies in a first family, such that the first family is defined by the first IC die;

comparing a distance value, from the plurality of distance values, representing a distance between the first IC die and a second IC die of the IC dies with a predetermined threshold;

if the distance value is less than the predetermined threshold, classifying the second IC die in the first family; and

if the distance value is greater than the predetermined threshold, classifying the second IC die in a second family, such that the second family is defined by the second IC die.

8. The computer program product of claim 7 , wherein the step of identifying further comprises, for each other IC die of the IC dies:

identifying a group of distance values, from the plurality of distance values, each distance value in the group of distance values representing a distance between the other IC die and a respective IC die of the IC dies that defines a respective family;

comparing each distance value from the group of distance values with the predetermined threshold;

if a distance value from the group of distance values, representing a distance between the respective other IC die and a specific IC die of the IC dies that defines a specific family, is less than the predetermined threshold, classifying the other IC die in the specific family; and

if all the distance values from the group of distance values are greater than the predetermined threshold, classifying the other IC die in a new family, such that the new family is defined by the other IC die.

9. The computer program product of claim 6 , wherein the instructions are further configured to normalize the matrix representation prior to computing the covariance matrix.

10. The computer program product of claim 6 , wherein the plurality of classification values are based on at least one of:

simulated values determined from a simulation of the common IC design;

a plurality of training sensor values collected from the sensors of the common IC design during a pre-production tape-out test; or

measured sensor values collected from the sensors.

11. The computer program product of claim 6 , wherein the step of identifying the classification scheme is part of the step of comparing the plurality of collected sensor values to the classification scheme, thereby enabling the classification of each of the multiple IC dies.

12. The computer program product of claim 6 , wherein:

the plurality of classification values are based on simulated sensor values determined from a simulation of the common IC design;

the step of determining the classification scheme takes place before the step of comparing the collected at least one sensor value to the classification scheme; and

the step of comparing the collected at least one sensor value to the classification scheme comprises:

establishing a collected data matrix representation from the collected sensor values, each row of the matrix representation comprising collected sensor values in respect of one of the IC dies, and

determining, using the collected data matrix representation, a plurality of collected data distance values, each distance value representing a respective distance between one IC die of the IC dies and another one of the IC dies,

wherein the classifying is based on the plurality of distance values scheme.

13. The computer program product of claim 12 , wherein:

the step of computing the covariance matrix from the matrix representation comprises normalizing the matrix representation prior to computing the covariance matrix, to define normalization coefficients thereby; and

the step of establishing the collected data covariance matrix comprises normalizing the matrix representation using the defined normalization coefficients.

14. The computer program product of claim 6 , wherein the matrix representation is established from at least one of:

simulated sensor values determined from a simulation of the common IC design;

operational parameters determined from a simulation of the common IC design; or

design signature values.

15. The computer program product of claim 6 , wherein the matrix representation is established from Pre-Si (pre-silicon) data, and wherein the step of determining, using the SVD, the plurality of distance values, comprises:

defining a set of Pre-Si SVD signatures by identifying at least one of the following:

vectors of the SVD for which the corresponding principal values of the SVD are greater than a pre-defined value, or

a pre-defined number of vectors of the SVD for which the corresponding principal values of the SVD are the greatest; and

determining the plurality of distance values using the defined set of Pre-Si SVD signatures.

16. The computer program product of claim 15 , wherein the step of determining the plurality of distance values using the defined set of Pre-Si SVD signatures comprises:

calculating at least some of the plurality of distance values, each of the at least some of the plurality of distance values being based on a distance between one of the Pre-Si SVD signatures and another of the Pre-Si SVD signatures.

17. The computer program product of claim 15 , wherein the step of determining the plurality distance values using the defined set of Pre-Si SVD signatures comprises:

configuring a plurality of estimators from the simulated sensor values and the set of Pre-Si SVD signatures, each estimator generating an estimated SVD signature from input sensor values;

estimating from the plurality of estimators, for each of the plurality of IC dies, a respective Post-Si SVD signature from the collected sensor values; and

calculating at least some of the plurality of distance values, each of the at least some of the plurality of distance values being based on a distance between one of the Post-Si SVD signatures and another of the Post-Si SVD signatures.

18. The computer program product of claim 15 , wherein the step of determining the plurality distance values using the defined set of Pre-Si SVD signatures further comprises:

calculating further distance values of the plurality of distance values, each of the further distance values being based on a distance between one of the Pre-Si SVD signatures and one of the Post-Si SVD signatures.

19. A method comprising operating at least one hardware processor to:

collect at least one sensor value from each of a plurality of sensors that are comprised in multiple Integrated Circuit (IC) dies that are manufactured according to a common IC design, wherein the at least one sensor value is indicative of field performance of the respective IC die; and

classify each of the multiple IC dies based on the field performance indicated by the at least one sensor value.

20. A computerized system comprising:

(a) at least one hardware processor; and

(b) a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by said at least one hardware processor to:

collect at least one sensor value from each of a plurality of sensors that are comprised in multiple Integrated Circuit (IC) dies that are manufactured according to a common IC design, wherein the at least one sensor value is indicative of field performance of the respective IC die, and

classify each of the multiple IC dies based on the field performance indicated by the at least one sensor value.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 17, 2023
From: LANDMAN, EVELYN; DAVID, YAHEL; FAYNEH, EYAL; COHEN, SHAI; TALKER, YAIR
To: PROTEANTECS LTD.
Reel/Frame 064928/0910 →
Continuity (3)
Continuation 17047243
Provisional Application 62657986 · Apr 16, 2018
Related Publication 20240003968A1 · Jan 4, 2024
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