In the present disclosure, analytics are applied to work items while the work items are waiting in a work queue in order to optimize the routing and allocation of work items to agents in the most efficient manner possible, while optimizing agents being assigned to work items they are most qualified to handle. By performing a look ahead at more than the initial work item, the system assesses the agent skills required by imminent work items in the work queue. This is then compared to a skillset of each available and/or soon to be available agent in order to achieve the optimal allocation of the work items to maximize the work item being assigned the best qualified agent. The work items are then routed to the agents accordingly.

A computer-implemented resource allocation method is provided, which comprises, in a computing environment comprising a resource management unit and a cluster comprising a cluster management node and a cluster node running an application program: receiving, by the resource management unit, a request for allocating one or more system resources to the application program; retrieving, by the resource management unit, from the cluster management node, an identifier of the cluster node running the application program; dynamically updating system physical resources allocated to the cluster node by updating a resource allocation file managed by an operating system of a computing machine on which the cluster is running, based on the identifier of the cluster node and the received request.

Systems and techniques that facilitate backend quantum runtimes are provided. In various embodiments, a system can comprise a backend receiver component that can access a computer program provided by a client device, wherein the computer program is configured to indicate a quantum computation. In various aspects, the system can further comprise a backend runtime manager component that can host the computer program by instantiating a backend classical computing resource. In various instances, the backend classical computing resource can orchestrate both classical execution of the computer program and quantum execution of the quantum computation indicated by the computer program.

Methods are provided. A method includes announcing to a network meta information describing each of a plurality of distributed data sources. The method further includes propagating the meta information amongst routing elements in the network. The method also includes inserting into the network a description of distributed datasets that match a set of requirements of the analytics task. The method additionally includes delivering, by the routing elements, a copy of the analytics task to locations of respective ones of the plurality of distributed data sources that include the distributed datasets that match the set of requirements of the analytics task.

The present invention relates to the technical field of high performance computing (HPC). In particular, the invention relates to a heterogeneous computing system, particularly a computing system including different modules, which can freely be assigned to jointly process a computation tasks. A control entity, referred to as module computing abstraction layer (MCAL), is provided which allows dynamic assignment of various resources provided by the different modules. Due to its flexibility in adjusting to varying demands in computing, the present invention is also applicable as an underlying system for providing cloud computing services, which provides shared computer processing resources and data to computers and other devices on demand, mostly via the Internet.

Aspects of the disclosure provide for mechanisms for resource allocation in computer systems. A method of the disclosure may include running, on a plurality of nodes of a computer system, a benchmark workload utilizing a plurality of compute resources, and generating, by a processing device, a plurality of benchmarking results representing performance of the computer system utilizing the plurality of compute resources. The method may further include creating, by the processing device, a resource definition for the compute system in view of the benchmarking results, wherein the resource definition comprises a first resource allocation unit indicative of a first computing capacity of the computer system utilizing a first compute resource and a second resource allocation unit indicative of a second computing capacity of the computer system utilizing a second compute resource, and wherein the plurality of compute resources comprises the first compute resource and the second compute resource.

Technologies for switching network traffic include a network switch. The network switch includes one or more processors and communication circuitry coupled to the one or more processors. The communication circuity is capable of switching network traffic of multiple link layer protocols. Additionally, the network switch includes one or more memory devices storing instructions that, when executed, cause the network switch to receive, with the communication circuitry through an optical connection, network traffic to be forwarded, and determine a link layer protocol of the received network traffic. The instructions additionally cause the network switch to forward the network traffic as a function of the determined link layer protocol. Other embodiments are also described and claimed.

Example systems and methods for cloning catalog objects are described. In one implementation, a method identifies an original catalog object associated with data and creates a duplicate copy of the original catalog object without copying the data itself. The method allows access to the data using the duplicate catalog object and supports modifying the data associated with the original catalog object independently of the duplicate catalog object. The duplicate catalog object can be deleted upon completion of modifying the data associated with the original catalog object.

Methods and systems are provided for assigning nodes to execute functions in a serverless computing environment. In one embodiment, a method is provided that includes receiving a function for execution in a serverless computing environment and identifying a storage pool needed during execution of the function. The serverless computing environment may include nodes for executing functions and a first set of nodes may be identified that implement the storage pool. Colocation measures may be determined between the first set of nodes and a second set of nodes. Available computing resources may be determined for the second set of nodes, such as available processing cores and available memory. The second set of nodes may be ranked according to the colocation measures and the available computing resources and a first node may be selected based on the ranking. The first node may be assigned to execute the function.

Providing multi-device services using a network application programming interface. The server obtains the accessibility in-ormation which indicates the plurality of devices and their capabilities. The plurality of devices have a same user identity. In this way, the server can take control on devices of participate for MuD services.