Abstract: A method includes: acquiring a hook point and a virtual program counter by analyzing a virtual machine of a script engine; acquiring a branch virtual machine instruction by analyzing an instruction set architecture; and providing an analysis function to the script engine based on the acquired virtual program counter and the acquired branch virtual machine instruction, wherein the analysis function is provided by applying a hook to the acquired hook point and wherein the hook includes processing of, in response to an occurrence of an exception, changing a pointing destination of a virtual stack pointer to a return destination of a function immediately before a part where the exception has occurred.

Abstract: In one embodiment, a method includes receiving information associated with a plurality of devices. The information includes a manufacturer, a model name, and a current version of software for each of the plurality of devices. The method also includes generating a plurality of classifications. Each of the plurality of classifications is associated with a particular manufacturer and a particular model name. The method further includes determining a number of the plurality of devices in a first classification of the plurality of classifications, categorizing the number of the plurality of devices in the first classification into a plurality of categories by the current version of software, and determining, independent of any type of device identifier, a latest available version of software for the first classification.

Abstract: Compiler techniques lot inline parallelism and re-targetable parallel runtime execution of logic iterators enables selection thereof from the source code or dynamically during the object code execution.

Abstract: A method for pipeline parallelism compiling is provided, which is executed by one or more processors, and includes receiving a source program associated with training of a machine learning model, determining, based on the source program, a plurality of operation groups including operations executed on training data of the machine learning model, generating a plurality of micro-batches from the training data, and determining, for each of the plurality of micro-batches, a plurality of operation sets corresponding to the plurality of operation groups.

Abstract: An AI tool for writing computer code is generated by collecting code entry data from a plurality of remote computing devices, training a code completion network using the code entry data, wherein the code completion network is configured to predict one or more additional code entry activities based on a provided set of code entry activities, and providing the code completion network to one or more development sessions. A code segment is intelligently generated by receiving a request to modify computer code of a program in a development interface, and presenting a text input component and a code description prompt. The technique further includes receiving, via the text input component, a code description, applying at least part of the code description to a code generation network to obtain a code segment suggestion and presenting the code segment suggestion on a display.

Abstract: An AI tool for writing computer code is generated by collecting code entry data from a plurality of remote computing devices, training a code completion network using the code entry data, wherein the code completion network is configured to predict one or more additional code entry activities based on a provided set of code entry activities, and providing the code completion network to one or more development sessions. A code segment is intelligently generated by receiving a request to modify computer code of a program in a development interface, and presenting a text input component and a code description prompt. The technique further includes receiving, via the text input component, a code description, applying at least part of the code description to a code generation network to obtain a code segment suggestion and presenting the code segment suggestion on a display.

Abstract: Provided is a program and computer-implemented method of obfuscating a software code, comprising adding a conditional branch instruction to the software code which, when executed, causes evaluating an opaque predicate (PT, PF, P?). The method comprises a step of generating the opaque predicate which includes performing a multiplication operation having as operands two mixed Boolean-arithmetic expressions. Other embodiments disclosed.

Abstract: Various embodiments described herein support or provide operations including receiving input data that comprises a collection of data units; determining that the collection of data units corresponds to a number of tokens that exceeds an upper limit of tokens; processing the collection of data units to generate a plurality of outputs; and aggregating the plurality of outputs into a final result provided as output of a function.

Abstract: A method for inference performance in an artificial intelligence model provides reduction of pre-processing overhead. The method includes receiving a plurality of operations associated with the artificial intelligence model. A computational graph for the artificial intelligence model is generated. Each of the operations is categorized into one of three categories including: accelerator designated operations, central processing unit (CPU) designated operations, and undetermined processing designated operations. An estimated processing time is determined for the operations. The operations are inserted into the computational graph. The computational graph is divided into sub-graphs. Edges of the sub-graphs where pre-processing steps will be performed is determined.

Abstract: A storage device management system (SDMS) as a component of an application acceleration system; this is for managing AppAccel hardware storage devices (AI hardware SDs) using a distributed hardware F+ Update Server service layer of one or more hardware F+ Update Servers managing a storage set of one or more AI hardware SDs. The one or more hardware F+ Update Servers manage the one or more AI hardware SDs with mechanisms such as SyncLink, data paths, SC Program Store, etc. having multiple uses among which is interoperating with AI hardware SD management components of the one or more hardware F+ Update Servers. The SDMS is composed of the one or more hardware F+ Update Servers and employ these mechanisms on one, many, or all of the one or more AI hardware SDs to enable feedback to the SDMS, which is an important operative part of managing one, many, or all of the one or more AI hardware SDs.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selection of ranked configurations.

Abstract: A method includes generating an ablation programming language, which defines commands for (i) setting ablation protocol parameters and respective values, (ii) setting a configuration of an ablation system, (iii) applying automatic logic that relates the ablation protocol parameters and the values to the configuration of the ablation system, and (iv) generating one or more graphical user interfaces (GUIs) showing one or more of the parameters of the ablation protocol and the system configuration. The ablation programming language is provided for subsequent use with the ablation system.

Abstract: Disclosed herein are techniques for providing comparative performance metrics to software application developers.

Abstract: A computer-implemented method, system and computer program product for performing user acceptance testing. A virtual environment for virtual sponsor users to interact with a feature or a function of a software product is created. Such virtual sponsor users are virtual representations of actual or real sponsor users. Each of these virtual sponsor users are then assigned a persona type profile of a target audience. Such persona type profiles include the character traits of a user, such as a user or member of the target audience. Interactions of the virtual sponsor users with the feature or the function of the software product are then simulated and tracked. The rate of acceptance of the feature or the function of the software product is then determined based on such tracked interactions. In this manner, user acceptance testing is performed in a swiftly manner that is cost effective.

Abstract: A method for verifying system behavior and correcting design flaws in a finite state machine (FSM)-modeled system or any other representational method that includes receiving from a user device via a model verification platform, data associated with the system design. The data describes states, state transitions, events, and outputs of the FSM-modeled system. The method includes searching the data for predetermined behavior of the FSM-modeled system, including predetermined state(s) and/or mode changes. The method includes flagging the predetermined behavior as a verified behavior and performing a control action in response to the verified behavior, including transmitting a notification to the user device that is indicative of the verified behavior, and a design recommendation where applicable. Instructions for the method may be recorded in a computer readable storage medium and executed by a processor to cause the model verification platform to perform the method.

Abstract: A vehicular multi-location synergic remote calibration method and system is provided. The vehicular multi-location synergic remote calibration system includes: a server, configured to store a calibration database and receive and store a calibration signal from a responder; a requester, configured to invoke the calibration signal from the server to read a calibration signal value; and/or, send a calibration signal write command to the server and send to the server a command for reading the written calibration signal; a responder, configured to send the calibration signal to the server, and further configured to receive a written target value from the server and complete vehicular online calibration.

Abstract: An embodiment causes inserting, into kernel code of an operating system, during execution of the operating system, a traffic monitoring code module. An embodiment extracts, using the traffic monitoring code module, from a plurality of messages between components of a cluster management system managing a first cluster of systems, a first message relating to a resource object, the resource object representing a resource within the first cluster of systems, the traffic monitoring code module triggered by receipt of each of the plurality of messages at a socket of the kernel code. An embodiment constructs, using the first message, a controller-resource object topology, the controller-resource object topology identifying a relationship between the resource object and a controller associated with the resource object.

Abstract: Techniques for generating synthetic data and/or machine learning model testing are described. For example, synthetic data may be generated according to a request by selecting one or more transformation modules to be used to generate synthetic data, instantiating the selected one or more transformation modules, and applying the selected one or more transformation modules in a defined order to at least one dataset to generate synthetic data.

Abstract: Compliance schemes may be associated with compliance types to provide resource compliance management. Compliance types may be created and associated with different compliance schemes. Compliance state for the compliance types may be generated and provided in response to requests to access the compliance state. Queries for compliance state, for example, may request compliance state, and query predicates or other criteria may be applied to the compliance state in order to perform the query.

Abstract: Methods and apparatus are provided for identifying performance bottlenecks in computer programs by tracking data accesses. In embodiments of the present disclosure, trace points are inserted at accessor functions of a computer program to record accesses to data structures of the computer program. The accesses are analyzed to determine patterns of access and to prioritize data structures for refactoring. In embodiments, the analysis is visualized using a hailstone plot wherein the data structures are ranked by priority. In some embodiments, transformation strategies may be generated based on the analysis to improve the performance of the computer program.