International Business Machines Corporation

Egduard Ramon Jauregui

Akil Khamisi Sutton

Uma Srinivasan

Zachary Thomas Dreiss

Kyle Indukummar Giesen

Patrick James McKeone

Lisander Lopez

A process to train a machine learning model to predict fault location in a system includes generating a data set for training the machine learning model. The generating includes injecting, at a selected location of the system, a test fault into a simulation of the system using a workload, and recording a respective error syndrome generated by the simulation. Further, the generating includes repeating the injecting, at other selected location(s) of the system, of other test fault(s) into the simulation of the system, and the recording of respective, generated error syndromes. In addition, the process includes training, using the data set, the machine learning model, and providing the trained machine learning model for use in debugging the system, where the debugging includes predicting, using the trained machine learning model, a fault location within the system based on an error syndrome generated by the system due to the fault.

Machine learning model training to assist in system debug

A circuit board includes a ground layer, a core layer positioned on the ground layer, an insulating layer positioned on the core layer, and a trace positioned between the core layer and the insulating layer. The circuit board also includes another ground layer positioned on the insulating layer, and an electromagnetic shield (EMS) extending between and electrically connected to the ground layers alongside the trace to shield the trace from electromagnetic radiation. The EMS extends along at least 90% of a length of the trace.

Circuit board local electromagnetic shielding

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Aurora, CO, United States of America

Egduard Ramon Jauregui