Abstract: The present disclosure relates to systems and methods for an interactive, intelligent hub built around the completion of a task. This hub brings together resources, information, suggested steps, and other automated assistance to facilitate the completion of the task. AI-based assistance may indicate which steps can be completed by automated processes, and dispatch those processes, or suggest resources to assist in the completion of other steps. The hub displays the current status of the task, and lives until the completion of the task, or abandonment by the user.

Abstract: A method is described. The method includes building a description of a workflow. The method also includes creating an embedded workflow description by embedding the description of the workflow with logical identifiers of different instances of services that are available over a network.

Abstract: A computer system may provide a plurality of load records for presentation in a user interface provided at a first plurality of user devices. The user interface may enable searching for a plurality of loads represented by the plurality of load records. The computer system may also determine, for a load record of the plurality of load records and based at least in part on inputting contextual information into a predictive model, an acceptance prediction indicating a probability that a load record of the plurality of load records will be accepted by a user. The computer system may also provide at least a portion of the plurality of load records for presentation in the user interface provided at a second plurality of user devices associated with a second plurality of users. The portion of the plurality of load records may include the load record including an updated value of an attribute of the load record that is dependent on the acceptance prediction.

Abstract: Customized root processes for groups of applications in a computing device. A computing device (e.g., a mobile device) can monitor usage of applications. The device can then store data related to the usage of the applications, and group the applications into groups according to the stored data. The device can customize and execute a root process for a group of applications according to usage common to each application in the group. The device can generate patterns of prior executions shared amongst the applications in the group based on the stored data common to each application in the group, and execute the root process of the group according to the patterns. The device can receive a request to start an application from the group from a user of the device, and start the application upon receiving the request and by using the root process of the group of applications.

Abstract: A method for managing computing resources on a vehicle with line-replaceable units (LRUs) including respective allocated system resources for tasks the LRUs are designed to perform and respective unallocated system resources that are available is provided. Implementations of the method include identifying the LRUs and applying a middleware layer across the LRUs to establish an edge computing infrastructure in which the LRUs operate as edge nodes. The middleware layer receives information from the edge nodes identifying the unallocated system resources and identifies data sources onboard the vehicle, data provided by those sources, and tasks to be performed using the data. The middleware further determines expected operational performance of the edge computing infrastructure and distributes the tasks to be performed across the edge nodes based on the expected operational performance of the edge computing infrastructure.

Abstract: Techniques for implementing an infrastructure orchestration service are described. A safety plan comprising a list of resources and operations based at least in part on a deployment configuration file can be received. Upon receiving approval of the safety plan, an operation corresponding to at least one of the list of resources can be prepared to be performed. The operation can be compared to the safety plan. If the operation is part of the safety plan, the operation can be performed. If the operation is not part of the safety plan, the deployment can be halted, and a notification that the deployment is not in compliance with the safety plan can be transmitted.

Abstract: This disclosure is directed to intelligent synchronization of computing users, and associated timing data, based on parameters or data received from computing systems connected via wireless, satellite, wire-based, optical-fiber based, etc., computing networks.

Abstract: A system comprises compute nodes distributed over a network and configured to perform a pipeline parallel process. The system also comprises an extended memory comprising a global virtual address space which is shared by the compute nodes. The extended memory is configured to enable the compute nodes to exchange data over the network when the compute nodes perform the pipeline parallel process.

Abstract: A system and method for performing autonomous analysis of computing resources of a particular entity across the open internet. In particular, a modularized system that is configured to distribute work to ephemeral worker nodes in order perform a blackbox analysis of a target entity and various computing resources under the control or administration of that entity. The blackbox analysis includes an evaluation of discovered resources and services based on appeal or threat actor temptation heuristic.

Abstract: The present disclosure relates to a 5th generation (5G) or pre-5G communication system for supporting a higher data transmission rate beyond a 4th generation (4G) communication system such as long term evolution (LTE). An operation method of a control device in a network function virtualization (NFV) environment according to various embodiments of the present disclosure comprises the steps of: determining a virtual compute node corresponding to a server device; identifying physical layer information related to the server device and virtual layer information related to the virtual compute node; and displaying the physical layer information and the virtual layer information. Therefore, various embodiments of the present disclosure enable a user to easily identify a virtual layer element and/or a physical layer element which causes malfunction, and enable the malfunction to be quickly resolved.

Abstract: A method for determining a progress of an execution of a task, the method may include accessing only a portion of a shared task status data structure that (a) is associated with the task, wherein the task is executed by a first plurality of compute elements, and (b) comprises multiple hierarchical levels; wherein an entry of a certain hierarchical level represents an aggregate progress associated with multiple entries of the another hierarchical level; the certain hierarchical level is higher than the other hierarchical level; and determining the progress of the execution of the task based on a content of the portion.

Abstract: A system including a data plane including a first virtual machine designated as a primary node and a second virtual machine designated as a secondary node, and a lock service configured to control changes in designation of the primary node and the secondary node. The first virtual machine repeatedly issues requests to the second virtual machine or lock service extending designation as the primary node for a first duration. The request is repeatedly issued within a duration shorter than the first duration. The second virtual machine receives an indication of the designation of the first virtual machine as the primary node being extended, issues a request to the lock service to change the designation of the primary node after passage the first duration of time without further indication of first virtual machine being extended as primary node, and receives confirmation from the lock service of the change in designation.

Abstract: A method for managing threads in a manycore system is launched by one or more processors, and includes receiving, from a host processor, a job descriptor associated with one or more tasks according to an offloading request of the host processor, generating threads for each of the one or more tasks based on the job descriptor, and allocating the generated threads to one or more cores of a cluster that includes a plurality of cores.

Abstract: Methods, systems, and computer-readable storage media for receiving a first stream request, providing a first DAG representative of a data processing flow of the first stream request, comparing one or more DAGs representative of respective data processing flows of one or more running streams in a set of running streams to provide a set of comparison results, each running stream being processed by a computing machine of the stream computing system, and determining that the first stream request has a common portion with respect to a first running stream based on a first comparison result of the comparison results and, in response: providing the first stream request and the first comparison result to a computing machine that is processing the first running stream, the computing machine executing a stream merger that merges a non-common portion of the first stream request with the common portion within the first running stream.

Abstract: Migrating workloads among execution environments including storage systems includes: selecting a target execution environment for supporting a workload and migrating the workload to the target execution environment utilizing active disaster recovery. Migrating the workload can include: assigning storage resources of the workload to a first pod; linking for replication, the first pod to a second pod of the target execution environment; and replicating the storage resources of the workload to the second pod of the target execution environment.

Abstract: A method, computer program product, and computing system for: receiving an indication that a specific request has been completely processed on an IT computing device; analyzing a plurality of queued requests within a pending queue of the IT computing device to identify a target queued request for processing based, at least in part, upon: a root request limit of the IT computing device, a global request limit of the IT computing device, and a sibling status of the specific request.

Abstract: Workload placement based on carbon emissions, including: calculating, for each execution environment of a plurality of execution environments, a carbon emission cost associated with a workload; selecting, based on each carbon emission cost for the plurality of execution environments, a target execution environment; and executing the workload on the target execution environment.

Abstract: Implementations disclosed describe methods and systems to perform the methods of deploying and executing machine learning models on target-specific computational platforms. Optimization techniques include but are not limited to alignment of kernel operations with hardware instructions of a target processing device, reduction of kernel dimensions near boundaries of data, efficient reuse of a small number of memory components during neural network operations, run-time quantization of data and neural network parameters, and other methods.

Abstract: A method of partitioning a graph for processing may include sorting two or more vertices of the graph based on incoming edges and outgoing edges, placing a first one of the vertices with fewer incoming edges in a first partition, and placing a second one of the vertices with fewer outgoing edges in a second partition. The first one of the vertices may have a lowest number of incoming edges, and the first one of the vertices may be placed in a first available partition. The second one of the vertices may have a lowest number of outgoing edges, and the second one of the vertices may be placed in a second available partition. A method for updating vertices of a graph may include storing a first update in a first buffer, storing a second update in a second buffer, and transferring the first and second updates to a memory using different threads.

Abstract: Virtual machine configuration information and physical machine IDs are collected from physical machines in association with each other. In addition, among information stored in a management table which stores them, a physical machine ID corresponding to the collected virtual machine configuration information, and it is determined whether or not the detected physical machine ID matches with the collected physical machine ID. Herein, in a case of determining not-matching, a physical machine of a source of the collected information is requested to change the virtual machine configuration information.