US 11,816,016 B2
Identifying causes of anomalies observed in an integrated circuit chip
Gajinder Panesar, Cambridge (GB); and Marcin Hlond, Cambridge (GB)
Assigned to Siemens Industry Software Inc., Plano, TX (US)
Appl. No. 17/780,837
Filed by Siemens Industry Software Inc., Plano, TX (US)
PCT Filed Nov. 26, 2020, PCT No. PCT/EP2020/083479
§ 371(c)(1), (2) Date May 27, 2022,
PCT Pub. No. WO2021/110530, PCT Pub. Date Jun. 10, 2021.
Claims priority of application No. 1917652 (GB), filed on Dec. 3, 2019.
Prior Publication US 2023/0004471 A1, Jan. 5, 2023
Int. Cl. G06F 11/00 (2006.01); G06F 11/34 (2006.01); G01R 31/3185 (2006.01)
CPC G06F 11/348 (2013.01) [G01R 31/318513 (2013.01); G06F 11/349 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method of identifying a cause of an anomalous feature measured from system circuitry on an integrated circuit (IC) chip, the IC chip comprising the system circuitry and monitoring circuitry for monitoring the system circuitry by measuring features of the system circuitry in each window of a series of windows, the method comprising:
(i) identifying a candidate window set in which to search for a cause of the anomalous feature from a set of windows prior to an anomalous window comprising the anomalous feature;
(ii) for each feature of the measured features of the system circuitry:
(a) calculating a first feature probability distribution of the respective measured feature for the candidate window set;
(b) calculating a second feature probability distribution of the respective measured feature for window(s) not in the candidate window set;
(c) comparing the first feature probability distribution and the second feature probability distribution; and
(d) identifying the respective measured feature in a timeframe of the candidate window set as the cause of the anomalous feature when the first feature probability distribution and the second feature probability distribution differ by more than a threshold value;
(iii) iterating steps (i) and (ii) for further candidate window sets from the set of windows prior to the anomalous window; and
(iv) outputting a signal indicating the measured feature(s) of step (ii)(d) identified as the cause of the anomalous feature.