Abstract: Methods and systems for solving a linear system include setting resistances in an array of settable electrical resistances in accordance with values of an input matrix. A series of input vectors is applied to the array as voltages to generate a series of respective output vectors. Each input vector in the series of vectors is updated based on comparison of the respective output vectors to a target vector. A solution of a linear system is determined that includes the input matrix based on the updated input vectors.

Abstract: Techniques are provided to implement hardware accelerated computing of eigenpairs of a matrix. For example, a system includes a processor, and a resistive processing unit coupled to the processor. The resistive processing unit includes an array of cells which include respective resistive devices, wherein at least a portion of the resistive devices are tunable to encode values of a given matrix which is storable in the array of cells. When the given matrix is stored in the array of cells, the processor is configured to determine an eigenvector of the stored matrix by executing a process which includes performing analog matrix-vector multiplication operations on the stored matrix to converge an initial vector to an estimate of the eigenvector of the stored matrix.

Abstract: A method is presented for computing an equilibrium distribution of Markov processes. The method includes storing weight values in an analog crossbar array of transition probability matrices, where the analog crossbar array of transition probability matrices represents a weight matrix with m rows and n columns, computing an eigenvector associated with a real eigenvalue of modulus one for each of the transition probability matrices, applying a gradient-based eigenvalue solver to converge to a dominant eigenpair, and determining a probability of changing from one state to another state in a stochastic entity based on outcomes of the gradient-based eigenvalue solver.

Abstract: Matrix inversion systems and methods are implemented using an analog resistive processing unit (RPU) array for hardware accelerated computing. A request is received from an application to compute an inverse matrix of a given matrix, and a matrix inversion process is performed in response to the received request. The matrix inversion process includes storing a first estimated inverse matrix of the given matrix in an array RPU cells, performing a first iterative process on the first estimated inverse matrix stored in the array of RPU cells to converge the first estimated inverse matrix to a second estimated inverse matrix of the given matrix, and reading the second estimated inverse matrix from the array of RPU cells upon completion of the first iterative process. An inverse matrix is returned to the application, wherein the returned inverse matrix is based, at least in part, on the second estimated inverse matrix.

Abstract: Methods and systems for solving a linear system include setting resistances in an array of settable electrical resistances in accordance with values of an input matrix. A series of input vectors is applied to the array as voltages to generate a series of respective output vectors. Each input vector in the series of vectors is updated based on comparison of the respective output vectors to a target vector. A solution of a linear system is determined that includes the input matrix based on the updated input vectors.

Abstract: A computer-implemented method for Eigenpair computation is provided. The method includes computing, her a hardware processor, an Eigenvector and respective Eigenvalues of the Eigenvector of a matrix by using a modified Stochastic Optimization process including performing a matrix vector product on a Resistive Processing Unit (RPU) crossbar array operatively coupled to the hardware processor and performing a scalar vector product on a digital device operatively coupled to the hardware processor and representing, for each of an Eigenpair, an initial guess for the Eigenvector and the respective Eigenvalues. The computing step includes storing the matrix in the RPU crossbar array.

Abstract: A computer-implemented method for Eigenpair computation is provided. The method includes computing an Eigenvector and respective Eigenvalues of the Eigenvector by using a Stochastic Optimization process. The computing step includes storing the matrix in a Resistive Processing Unit (RPU) crossbar array.

Abstract: A vehicle weight detection method, system, and non-transitory computer readable medium, include calculating a first difference between a first expected weight of a vehicle and a first current weight of the vehicle based on On-Board Dash (OBD) input data, calculating a second difference between a second expected weight of the vehicle and a second current weight of the vehicle based on a spring-mass-damper mechanical algorithm using vehicle data received from a user device, and a comparing circuit configured to compare each of the first difference and the second difference to a predetermined weight difference threshold value.

Abstract: A vehicle weight detection method, system, and non-transitory computer readable medium, include calculating a first difference between a first expected weight of a vehicle and a first current weight of the vehicle based on On-Board Dash (OBD) input data, calculating a second difference between a second expected weight of the vehicle and a second current weight of the vehicle based on a spring-mass-damper mechanical algorithm using vehicle data received from a user device, and a comparing circuit configured to compare each of the first difference and the second difference to a predetermined weight difference threshold value.

Abstract: A vehicle weight detection method, system, and non-transitory computer readable medium, include calculating a first difference between a first expected weight of a vehicle and a first current weight of the vehicle based on On-Board Dash (OBD) input data, calculating a second difference between a second expected weight of the vehicle and a second current weight of the vehicle based on a spring-mass-damper mechanical algorithm using vehicle data received from a user device, a comparing circuit configured to compare each of the first difference and the second difference to a predetermined weight difference threshold value, and a location checking circuit configured to checks if a location of the vehicle matches a location in a list of verified weight change locations of a database if the comparing circuit detects at least one of the first difference and the second difference is greater than the predetermined weight difference threshold value.

Abstract: A vehicle weight detection method, system, and non-transitory computer readable medium, include calculating a first difference between a first expected weight of a vehicle and a first current weight of the vehicle based on On-Board Dash (OBD) input data, calculating a second difference between a second expected weight of the vehicle and a second current weight of the vehicle based on a spring-mass-damper mechanical algorithm using vehicle data received from a user device, a comparing circuit configured to compare each of the first difference and the second difference to a predetermined weight difference threshold value, and a location checking circuit configured to checks if a location of the vehicle matches a location in a list of verified weight change locations of a database if the comparing circuit detects at least one of the first difference and the second difference is greater than the predetermined weight difference threshold value.

Abstract: A system for determining a group of semiconductor manufacturing process steps with a similar influence on individual semiconductor products. The system generates a first table including time stamps for the individual semiconductor products. The system creates a second table including Q-times based on the first table. The Q-times refers to time differences between every pair of the time stamps. The system forms a dependency table by grouping the Q-times with similar dependencies together. The system identifies groups of the similar dependencies. The system extracts semiconductor process steps belonging to the groups.

Abstract: A system for determining a group of semiconductor manufacturing process steps with a similar influence on individual semiconductor products. The system generates a first table including time stamps for the individual semiconductor products. The system creates a second table including Q-times based on the first table. The Q-times refers to time differences between every pair of the time stamps. The system forms a dependency table by grouping the Q-times with similar dependencies together. The system identifies groups of the similar dependencies. The system extracts semiconductor process steps belonging to the groups.

Abstract: A method, system and computer program product are disclosed for identifying false positive indications of high impedance faults in an AC electric power transmission and distribution network. In one embodiment, the method comprises using a procedure to monitor a phase conductor of the network for faults, said procedure generating a fault signal indicating a specified fault in the conductor. In this embodiment, the voltage and current waveform of the electric power conducted through the conductor are monitored. When a phase shift in said waveform is detected over a defined period of time, and said detected phase shift meets one or more given criteria, a correction signal is generated indicating that said fault signal is a false indication of the specified fault. The given criteria may include, for example, that the phase shift is more than a threshold value for a specified period of time.

Abstract: A system, method and/or computer program product for analyzing a functionality of at least two manufactured products obtain a first characteristic of a first manufactured product. The system acquires a second characteristic of a second manufactured product. The system identifies a common feature between the first characteristic and the second characteristic. The system identifies a distinguishable feature between the first characteristic and the second characteristic. The system determines a cause of a deviation of a functionality in the first manufactured product or the second manufactured product or both manufactured products based on the identified common feature or the identified distinguishable feature or both features.

Abstract: A method for detecting high impedance faults, including: receiving an input waveform from a circuit; computing a root mean square of the input waveform; fitting a regression line to the root mean squares; computing a deviation between the regression line and the root mean squares; determining whether the deviations are above a threshold; and outputting a value indicating that a fault has occurred in the circuit when the deviation is above the threshold and outputting a value indicating that a fault did not occur in the circuit when the deviation is below the threshold.

Abstract: A system for determining a group of semiconductor manufacturing process steps with a similar influence on individual semiconductor products. The system generates a first table including time stamps for the individual semiconductor products. The system creates a second table including Q-times based on the first table. The Q-times refers to time differences between every pair of the time stamps. The system forms a dependency table by grouping the Q-times with similar dependencies together. The system identifies groups of the similar dependencies. The system extracts semiconductor process steps belonging to the groups.

Abstract: There are provided a system, method and computer program product for detecting foreign materials in a semiconductor manufacturing process. The manufacturing process uses a plurality of semiconductor manufacturing tools. The system categorizes at least one monitoring wafer according to one or more categories. The system supplies the categorized monitoring wafer to a semiconductor manufacturing tool. The system observes a level of contamination on the categorized monitoring wafer. The system compares the level of contamination to a threshold. The system cleans the tool in a response to determining that the level of contamination is larger than the threshold. The system determines which category of the wafer leaves a highest level of contamination on the tool. The system identifies a root cause of the highest level of contamination on the tool.

Abstract: A system, method and/or computer program product for analyzing a functionality of at least two manufactured products obtain a first characteristic of a first manufactured product. The system acquires a second characteristic of a second manufactured product. The system identifies a common feature between the first characteristic and the second characteristic. The system identifies a distinguishable feature between the first characteristic and the second characteristic. The system determines a cause of a deviation of a functionality in the first manufactured product or the second manufactured product or both manufactured products based on the identified common feature or the identified distinguishable feature or both features.

Abstract: An entertainment system using bio-response includes a narrative, which includes a plurality of narrative segments assembled into at least one of a plurality of sequences, depending on at least one of a user profile and user bio-response, to create a plurality of cogent narratives.