Abstract: A neural network circuit is provided. The neural network circuit includes a memory device including memristors connected in a matrix, a controller arranged to control a voltage application device to perform writing, deleting and reading data in the memory device, multiple current-to-voltage (I-V) conversion amplifier circuits arranged to convert currents flowing through the memory elements into voltages and outputting the voltages, and multiple current adjusters respectively corresponding to the I-V conversion amplification circuits, each current adjuster being arranged to adjust a total current value input to a corresponding I-/V conversion amplification circuit to zero.

Abstract: A method, system and computer program product, the method comprising: obtaining a test template comprising a multiplicity of elements, including a first element and another element; generating a partially instantiated test template comprising a first instance for the first element and the another element in an uninstantiated form; generating, based on the partially instantiated test template, a first test complying with the test template, the first test comprising the first instance for the first element and an instance for the another element; executing the first test to obtain a first result; generating, based on the partially instantiated test template, a second test complying with the test template, the second test comprising the first instance for the first element and another instance for the another element, thereby using the first instance for generating the first and second tests; and executing the second test to obtain a second result.

Abstract: Described are techniques for predicting gradual performance degradation with non-linear characteristics. The techniques including a method comprising inputting a new data sample to a failure prediction model, wherein the failure prediction model is trained using a labeled historical dataset, wherein respective data points are associated with a look-back window and a prediction horizon to create respective training samples, wherein the respective training samples are clustered in a plurality of clusters, and wherein the plurality of clusters are each associated with a normalcy score and an anomaly score. The method further comprises outputting a classification associated with the new data sample based on comparing a first anomaly score of a first cluster of the plurality of clusters that includes the new data sample to an average anomaly score of clusters of the plurality of clusters having the normalcy score greater than the anomaly score.

Abstract: Systems and methods are provided for detecting fault conditions associated with an distribution point in a communication system using retrain event data. The retrain event data is collected for all of the ports associated with a target site of the distribution point. The collected retrain event data can then be organized into several different categories such as upstream related retrain events and downstream related retrain events. A screening criteria can be selected that is associated with a fault condition. The screening criteria can be evaluated using one or more evaluation metrics. Each evaluation metric can be based on normalized parameters generated from the categorized retrain event data. If all of the evaluation metrics associated with a screening criteria are satisfied, then the screening criteria is satisfied and the target site is determined to have a fault condition.

Abstract: An error in content generated by a first electronic device can be detected by a second electronic device. The second electronic device receives, in one or more messages, first message content and second message content generated by integrated circuit logic within the first electronic device. The second electronic device compares the first message content with predetermined message content. Based on detecting a mismatch between the first message content and the predetermined message content, the second electronic device initiates error recovery for the one or more messages. Initiating error recovery can include, for example, logging an error in the integrated circuit logic, requesting for the first electronic device to regenerate the first message content and second message content, or initiating execution of a program that detects and corrects programming errors in the integrated circuit logic.

Abstract: Methods, apparatuses and systems for cloud-based disaster recovery are provided. The method, for example, includes configuring, at a cloud-based computing platform, a declaration including servers associated with a plurality of selected workloads configured based on information provided by a user for corresponding servers used at a client machine, the declaration including generated steps listing the servers, and restoring the servers for each of the generated steps of the declaration upon receiving, from the client machine, a failure indication associated with the servers.

Abstract: Methods, apparatuses and systems for cloud-based disaster recovery are provided. The method, for example, includes configuring, at a cloud-based computing platform, workloads including servers used by a client machine, the workloads configured based on user information provided at the client machine, determining if the workloads are compliant with one or more objectives, if the configured workloads are compliant with the one or more objectives, merging the workloads for creating a declaration comprising generated steps to which the servers are added, restoring the servers for each of the generated steps of the declaration upon receiving, from the client machine, a failure indication associated with the servers.

Abstract: A redundant processing fabric in an autonomous vehicle may include processing, by a first processing unit of a plurality of processing units, sensor data from a first sensor of a plurality of sensors, where the plurality of processing units are coupled to the plurality of sensors via a switched fabric, wherein the plurality of processing units and plurality of sensors are included in the autonomous vehicle; determining a failure in processing the sensor data by the first processing unit; and redirecting, via the switched fabric, sensor data from the first sensor a redundant processing unit.

Abstract: A method and an apparatus for outputting information are provided. The method includes: acquiring at least one piece of test data generated in a target period; performing a fitting calculation on the at least one piece of test data to obtain estimated test data in the target period; and determining, for a test time point in the target period, a difference value between test data generated at the test time point and corresponding estimated test data as a target difference value; determining at least one historical correspondence difference value corresponding to the determined target difference value; and generating and outputting a data fluctuation value based on the determined target difference value and the determined at least one historical correspondence difference value.

Abstract: Methods and devices for providing reserved failover capacity across a plurality of data centers are described herein. An exemplary method includes determining whether a management process is executing at a first data center corresponding to a first physical location. In accordance with a determination that the management process is not executing at the first data center corresponding to the first physical location a host is initiated at a second data center corresponding to a second physical location and the management process is executed on the initiated host at the second data center corresponding to the second physical location.

Abstract: To predict a failure condition in a power module of a vehicle, it is determined whether a discontinuity in statistical data characterizing physical measurements of the power module meets a threshold criterion. Responsive to the discontinuity meeting the threshold criterion, a data offset in the physical measurements is computed at the discontinuity. A shift correction is applied to the physical measurements in accordance with the computed data offset responsive to a determination that the discontinuity is attributable to a restart of the power module. Other statistical data characterizing the shift-corrected physical measurements are computed and the statistical data and the other statistical data are provided to a machine learning processor that predicts the failure condition in the power module.

Abstract: A technique involves: in response to establishing a stripe in a Redundant Array of Independent Disks (RAID), generating first mapping information of the stripe in a block allocated for the stripe, the RAID being built based on extents obtained by dividing disks, the stripe including a first extent set, the first mapping information recording respective disk locations of the first extent set; in response to a failure occurring in a first disk where a first extent in the first extent set is located, replacing the first extent with a second extent to obtain a second extent set corresponding to the stripe; generating second mapping information of the stripe in the block, to record respective disk locations of the second extent set; and in response to the first disk being recovered from the failure, restoring data in the stripe based on the first mapping information and the second mapping information.

Abstract: One embodiment provides a system for facilitating anomaly detection. During operation, the system determines, by a computing device, a set of testing data which includes a plurality of data points, wherein the set includes a data series for a first variable and one or more second variables, and wherein the one or more second variables are dependent on the first variable. The system divides the set of testing data into a number of groups based on a type of the data series. The system determines an inter-quartile range for a respective group. The system classifies a first testing data point in the respective group as an anomaly based on the inter-quartile range for the respective group, thereby enhancing data mining and outlier detection for the data series for multiple variables.

Abstract: Techniques are provided for system operational analytics using additional features over time-series counters for health score computation. An exemplary method comprises: obtaining log data from data sources of a monitored system; applying a counting function to the log data to obtain time-series counters for a plurality of distinct features within the log data; applying an additional function to the time-series counters for the plurality of distinct features; and processing an output of the additional function using a machine learning model to obtain a health score for the monitored system based on the output of the additional function.

Abstract: Pattern recognition is used to proactively treat defects of repeating circuit topologies. A component of a computing environment is monitored for failures. The component includes one or more repeating circuit topologies. A determination is made as to whether a new failure within a repeating circuit topology of the one or more repeating circuit topologies has occurred within a predefined amount of time from a previous failure matching a selected pattern, in which the selected pattern indicates a non-contiguous growing defect. Based on determining the new failure has occurred within the predefined amount of time from the previous failure matching the selected pattern, corrective action for the component is proactively taken.

Abstract: A computer system that has two or more processing engines (PE), each capable of performing one or more operations on one or more operands but one or more of the PEs performs the operations unreliably. Initial results of each operation are debiased to create a debiased result used by the system instead of the initial result. The debiased result has an expected value equal to a correct output where the correct output is the initial result the respective operation would have produced if the respective operation performed was reliable.

Abstract: A device fault processing method is used to perform fault processing on a peripheral component interconnect express device. The method includes: obtaining, by the controller, first device fault information after detecting that the device is faulty, where the first device fault information is used to indicate that the device is faulty, the first device fault information includes a first value of a fault processing state parameter of the device, and the first value indicates that the device is in a soft reset state; and performing, by the controller, hot reset processing on the device, so as to implement fault processing on the peripheral component interconnect express device without manual intervention in plugging out and plugging in or resetting a pluggable unit in which the peripheral component interconnect express device is located and without manual resetting on a computer system.

Abstract: A system for detecting power failure in a dual processing system includes a first central processing unit (CPU), a second CPU, a power controlling unit, and a complex programmable logic device (CPLD). The power controlling unit is electrically coupled to the first CPU and the second CPU and the CPLD. The CPLD can determine a power failure occurring in relation to the first CPU and the second CPU. If power to the first CPU does not fail but power to the second CPU does fail, the CPLD controls the power controlling unit to stop supplying power for the second CPU only and make a certain number of power restart attempts. A method for detecting a power failure is also provided.

Abstract: An information processing apparatus, includes a first nonvolatile storage device, and a processor coupled to the first nonvolatile storage device, wherein the processor is configured to suspend, when receiving a write request of data from an application, a write process for the write request in a case where second writing of the data into a second nonvolatile storage device of a different information processing apparatus fails while first writing of the data into the first nonvolatile storage device succeeds, record, after the write process is suspended, error information indicative of an error of the second writing, resume, after the error information is recorded, the write process and issue a notification of the application of completion of the write process, and isolate, after the notification of the completion of the write process is issued, a region of the second nonvolatile storage device which is used by the application.

Abstract: A system for dynamically load-balancing at least one redistribution element across a group of computing resources that facilitates at least an aspect of an Industrial Execution Process in an M:N working configuration is illustrated.