Abstract: A first set and a second set are identified as operands for a set operation of a similarity analysis task iteration. Using respective minimum hash information arrays and contributor count arrays of the two sets, a minimum hash information array and contributor count array of a derived set resulting from the set operation is generated. An entry in the contributor count array of the derived set indicates the number of child sets of the derived set that meet a criterion with respect to a corresponding entry in the minimum hash information array of the derived set. The generated minimum hash information array and the contributor count array are stored as part of input for a subsequent iteration. After a termination criterion of the task is met, output of the task is stored.

Abstract: Techniques for a database management system to predict when in the future a materialized view will have a quiet period during which the materialized view will not be stale. This is a followed by an approach that uses the quiet period prediction to determine an optimized schedule for refreshing the materialized view. The approach combines the quiet period prediction with a query rewrite pattern prediction for the materialized view and an estimated refresh duration for the materialized view to determine the optimized refresh schedule for the materialized view.

Abstract: The disclosed embodiments relate to a system that characterizes susceptibility of an inferential model to follow signal degradation. During operation, the system receives a set of time-series signals associated with sensors in a monitored system during normal fault-free operation. Next, the system trains the inferential model using the set of time-series signals. The system then characterizes susceptibility of the inferential model to follow signal degradation. During this process, the system adds degradation to a signal in the set of time-series signals to produce a degraded signal. Next, the system uses the inferential model to perform prognostic-surveillance operations on the set of time-series signals with the degraded signal. Finally, the system characterizes susceptibility of the inferential model to follow degradation in the signal based on results of the prognostic-surveillance operations.

Abstract: In accordance with an embodiment, described herein is a system and method for dependency analysis for a calculation script in a multidimensional database computing environment. A multidimensional database cube aggregation can be represented as a lattice of blocks or cube, arranged according to a database outline (e.g., intra-dimensional or member hierarchy). When the multidimensional database system performs computations in parallel for a given calculation script, portions of the cube that can be computed concurrently are identified.

Abstract: The disclosed systems, methods and computer readable media relate to managing Non-Volatile Memory Express (NVMe) over Transmission Control Protocol (TCP) (NVMeOTCP) connections between a smart network interface card (smartNIC) and a block storage data plane (BSDP) of a cloud computing environment. A software agent (“agent”) executing at the smartNIC may manage a number of network paths (active and, in some cases, passive network paths). The agent may monitor the network traffic (e.g., input/output operations (IOPS)) through the paths (e.g., using established NVMeOTCP connections corresponding to the paths). If a condition is met relating to a performance threshold associated with the monitored paths, the agent may increase or decrease the number established NVMeOTCP connections to match real time network conditions.

Abstract: Techniques are disclosed for cryptographically secure shuffling processes for generating and utilizing secrets in an infrastructure-as-a-service (IaaS) environment. In an embodiment, a method comprises generating a source list and a destination list, the source list and destination list association with a sequential format and the source list comprising a plurality of elements in the sequential format; generating a first random number and a second random number; determining a first element in the source list, the first element corresponding to a position in the sequential format of the source list based on the first random number; determining a first destination position in the destination list, the first destination position corresponding to a position in the sequential format of the destination list based on the second random number; and updating the destination list to include the first element in the source list at the first destination position.

Abstract: Techniques are disclosed for managing aspects of identifying and/or deploying hardware of a dedicated cloud to be hosted at a customer location (a “DRCC”). A DRCC may comprise cloud infrastructure components provided by a cloud provider but hosted by computing devices located at the customer's (a “cloud owner's”) location. Services of the central cloud-computing environment may be similarly executed at the DRCC. A number of user interfaces may be hosted within the central cloud-computing. These interfaces may be used to track deployment and region data of the DRCC. A deployment state may be transitioned from a first state to a second state based at least in part on the tracking and the deployment state may be presented at one or more user interfaces. Using the disclosed user interfaces, a user may manage the entire lifecycle of a DRCC and its corresponding hardware components.

Abstract: Techniques described herein include frameworks and models for identifying, analyzing, and addressing hangs within distributed and heterogenous computing environments. A hang detection framework may model a distributed computing environment as a complex forest of interrelated requests. The hang detection framework may generate hang graphs based upon requests that are being processed and/or waited upon within the distributed environment. For example, a node within an acyclic graph may represent an execution entity that is currently processing one or more requests. Directed edges that connect one node to another may represent requests upon which an execution entity is waiting for another execution node to fulfill. The model may be used to isolate and address the root cause of hangs within the computing environment.

Abstract: The present disclosure relates to systems and methods for an intelligent assistant (e.g., a chatbot) that can be used to enable a user to generate a machine learning system. Techniques can be used to automatically generate a machine learning system to assist a user. In some cases, the user may not be a software developer and may have little or no experience in either machine learning techniques or software programming. In some embodiments, a user can interact with an intelligent assistant. The interaction can be aural, textual, or through a graphical user interface. The chatbot can translate natural language inputs into a structural representation of a machine learning solution using an ontology. In this way, a user can work with artificial intelligence without being a data scientist to develop, train, refine, and compile machine learning models as stand-alone executable code.

Abstract: A tool may provide a real-time analysis of potential bottlenecks while threads wait on locks held by other threads. For each job currently operating on the server instance, the tool may access a list of threads and retrieve call stacks associated with those threads. The call stacks may then be analyzed to identify threads that are holding a lock, along with any corresponding threads that are waiting on the lock. The locks may be held on memory resources or any other type of computing resource. These bottlenecks may be identified and an adjustment of the configuration of the server instance may be triggered in response that is configured to reduce the likelihood that these types of bottlenecks may occur in the future.

Abstract: Methods, systems, and computer readable media for enabling forwarding of subsequent network function subscription updates. A method includes forwarding, from a bootstrapped network function repository function (NRF) in a first region, a subscription creation request from a consumer network function to a target NRF in a second region. The method includes creating, at the target NRF, a subscription for the consumer network function. The method includes generating, at the target NRF, a hint comprising data indicating one or more alternate NRFs each sharing subscription state data with the target NRF. The method includes sending, from the target NRF to the consumer network function, a subscription response message including the hint.

Abstract: New data structures for analyzing a log are generated. A hierarchical data structure includes a plurality of hierarchical nodes. Each node is associated with data and metadata. Each node may also be associated with analysis data. Information (data, metadata, and/or analysis data) of an ancestor node is imputed to a descendant node; a descendant node inherits the information of an ancestor node. When determining analysis data for a particular hierarchical node, information from any ancestor node to the particular hierarchical node may be used; however, information from non-ancestor nodes is not necessarily used. A timeline data structure includes a reference to a hierarchical node within a hierarchical data structure and a reference to an event type. The timeline data structure is thereby associated with the information of the referenced hierarchical node and information of any ancestor nodes to the referenced hierarchical node.

Abstract: Systems and methods for using InfiniBand routing algorithms for Ethernet fabrics in a high performance computing environment. The method can provide, at a computer comprising one or more microprocessors, a plurality of switches, a plurality of hosts, a topology provider (TP) module, a routing engine (RE) module, and a switch initializer (SI) module. The method can perform a discovery sweep, by the TP, of the plurality of hosts and the plurality of switches and assigns an address to each of the plurality of hosts and the plurality of switches. The method can calculate, by the routing engine, a routing map, based upon a routing scheme, for the plurality of hosts and the plurality of switches, the routing map comprising a plurality of forwarding tables. The method can configure, each of the plurality of switches with a forwarding table of the plurality of forwarding tables calculated by the routing engine.

Abstract: Techniques for generating text content arranged in a consistent read order from a source document including text corresponding to different read orders are disclosed. A system parses a binary file representing an electronic document to identify characters and metadata associated with the characters. The system pre-sorts a character order of characters in each line of the electronic document to generate an ordered list of characters arranged according to the right-to-left reading order. The system performs a layout-mirroring operation to change a position of characters within the modified document relative to a right edge of the document and a left edge of the document. Subsequent to performing layout-mirroring, the system identifies native left-to-right reading-order text in-line with the native right-to-left reading-order text.

Abstract: Techniques for managing a software build using a machine learning model are disclosed. A system obtains historical data associated with historical software builds. The historical data includes attribute data for a plurality of development stages associated with a historical software build and labels indicating success or failure for the plurality of development stages. The system trains a machine learning model using the historical data associated with the historical software builds to generate predictions of success or failure of the plurality of development stages. The system receives attributes of a target software build and a selection of a first target development stage of the target software build. The system applies the machine learning model to the target software build to generate a first prediction of success or failure of the first target development stage.

Abstract: The present disclosure relates to systems and methods that use an artificial intelligence (AI) model to generate outputs that can be evaluated to predict which logged entry items match entry request record line items of an entry request record. Additionally, the present disclosure relates to systems and methods for intelligently detecting anomalies within data sets.

Abstract: Systems that determine relationships between network components of a cluster using packet filters are disclosed. A system can identify objects that implement services of a cluster and network connections associated with respective pairs of the objects. The system can also filter out network connections from the identified network connections. The filtering can remove connections between source objects and destination objects based on the destination objects lacking any components that implement a service in cluster. The filtering can also retain network connections between source objects and destination objects based on the source objects including components that each implement at least one service, and based on the second destination object including components that each implement at least one service. Additionally, the system can generate relationship maps and network topologies using the determined relationships.

Abstract: Systems, devices, and methods of the present invention involve discourse trees. In an example, a method involves generating a discourse tree. The method includes identifying, from the discourse tree, a central entity that is associated with a rhetorical relation of type elaboration and corresponds to a topic node that identifies a central entity of the text. The method includes determining a subset of elementary discourse units of the discourse tree that are associated with the central entity. The method includes forming generalized phrases from the subset of elementary discourse units. The method includes forming tuples from the generalized phrases, where a tuple is an ordered set of words in normal form. The method involves responsive to successfully converting an elementary discourse unit associated with an identified tuple into a logical representation, updating the ontology with an entity from the identified tuple.

Abstract: The present disclosure relates generally to determining intent based upon speech input using a dialog system. More particularly, techniques are described using matching-based machine learning techniques to identify an intent corresponding to speech input in a dialog system. These procedures do not require training when intents are added or removed from the set of possible intents.

Abstract: A computer comprising one or more processors and memory may implement multiple threads that perform a lock operation using a data structure comprising an allocation field and a grant field. Upon entry to a lock operation, a thread allocates a ticket by atomically copying a ticket value contained in the allocation field and incrementing the allocation field. The thread compares the allocated ticket to the grant field. If they are unequal, the thread determines a number of waiting threads. If the number is above the threshold, the thread enters a long term wait operation comprising determining a location for long term wait value and waiting on changes to that value. If the number is below the threshold or the long term wait operation is complete, the thread waits for the grant value to equal the ticket to indicate that the lock is allocated.