Abstract: A method for dynamically allocating computing resources to virtual computing machines in a shared system. An initial allocation is made for each computing resource. Current demand for each computing resource for each of the virtual computing machines is determined to identify changes in current demand. The system identifies a virtual computing machine for which usage of a first computing resource is approaching a first predetermined threshold allotted to the first virtual computing machine. The system identifies a second virtual computing machine in the system for which usage of the first computing resource is less than a second predetermined threshold of the first computing resource allotted to the second virtual computing machine. The server dynamically allocates at least part of the first computing resource from the second virtual computing machine to the first virtual computing machine to meet current demand for the first computing resource in the first virtual computing machine.

Abstract: A system program monitors a numerical controller executing a useful program controlling a machine. The numerical controller determines target values for position-controlled axes and controls the position-controlled axes in accordance with the target values. The numerical controller stores resources and determines whether, and optionally to which extent, the resources are enabled or disabled. Enabling or disabling the resources specifies how many processor cores are enabled for use, or how many processor threads are enabled for use, or to what extent a processor cache or a processor main memory are enabled for use, or which hardware components of the numerical controller are enabled for use, or to what extent use of external computing power is permitted. The numerical controller determines the target values for the position-controlled axes using only the enabled resources.

Abstract: An apparatus includes a processor to receive a request to provide a view of an object associated with a job flow, and in response to determining that the object is associated with a task type requiring access to a particular resource not accessible to a first interpretation routine: store, within a job queue, a job flow generation request message to cause generation of a job flow definition the defines another job flow for generating the requested view; within a task container in which a second interpretation routine that does have access to the particular resource is executed, generate the job flow definition; store, within a task queue, a job flow generation completion message that includes a copy of the job flow definition; use the job flow definition to perform the other job flow to generate the requested view; and transmit the requested view to the requesting device.

Abstract: A method and apparatus for scaling resources of a GPU in a cloud computing system are provided. The method includes receiving requests for services from a client device, queuing the received requests in a message bus based on a preset prioritization scheme; and scaling the resources of the GPU for the requests queued in the message bus according to a preset prioritization loop.

Abstract: An apparatus including a processor to: output a first request message onto a group sub-queue shared by multiple task containers to request execution of a first task routine; within a task container, respond to the first request message, by outputting a first task in-progress message onto an individual sub-queue not shared with other task containers to accede to executing the first task routine, followed by a task completion message; and respond to the task completion message by allowing the task completion message to remain on the individual sub-queue to keep the task container from executing another task routine from another request message on the group sub-queue, outputting a second request message onto the individual sub-queue to cause execution of a second task routine within the same task container to perform a second task, and responding to the second task in-progress message by de-queuing the task completion message.

Abstract: An apparatus including a processor to: within a kill container, in response to a set of error messages indicative of errors in executing multiple instances of a task routine to perform a task of a job flow with multiple data object blocks of a data object, and in response to the quantity of error messages reaching a threshold, output a kill tasks request message that identifies the job flow; within a task container, in response to the kill tasks request message, cease execution of the task routine and output a task cancelation message that identifies the task and the job flow; and within a performance container, in response to he task cancelation message, output a job cancelation message to cause the transmission of an indication of cancelation of the job flow, via a network, and to a requesting device that requested the performance of the job flow.

Abstract: A system for dynamically auto-scaling allocated capacity of a virtual desktop environment includes: base capacity resources and burst capacity resources and memory coupled to a controller; wherein, in response to executing program instructions, the controller is configured to: in response to receiving a log in request from a first user device, connect the first user device to a first host pool to which the first device user is assigned; execute a load-balancing module to determine a first session host virtual machine to which to connect the first user device; and execute an auto-scaling module comprising a user-selectable auto-scaling trigger and a user-selectable conditional auto-scaling action, wherein, in response to recognition of the conditional auto-scaling action, the controller powers on or powers off one or more base capacity resources or creates or destroys one or more burst capacity resources.

Abstract: An apparatus includes a processor to: output a request message to cause a first task to be performed; within a task container, in response to the request message and a data object not being divided, divide the data object into a set of data object blocks based on at least the sizes of the data object and the atomic unit of organization of data therein, as well as the storage resources allocated to task containers, and output a task completion message indicating that the first task has been performed, and including a set of data block identifiers indicating the location of the set of data object blocks within at least one federated area; and in response to the task completion message, output a set of request messages to cause a second task to be performed by executing multiple instances of a task routine within multiple task containers.

Abstract: Disclosed are a FAAS distributed computing method and apparatus. The method includes: decomposing a computation task into multiple steps with correlation and execution order, and constructing multiple mirror images and multiple method groups respectively; creating multiple dockers in a process and allocating hardware resources according to the mirror image corresponding to a specific step; transferring, according to a dynamic pointer of the corresponding method group, a data processing result to the method group corresponding to the next step, and simultaneously storing a generated intermediate result in a distributed memory file system; modifying dynamic pointers of the multiple method groups in real-time to dynamically adjust the correlation and execution order of the multiple steps; monitoring a running state of each method in the multiple method groups, restarting the docker of the method or loading latest docker snapshot of the method and expanding or reducing a capacity of the method groups.

Abstract: An apparatus includes a processor to: receive a request to perform a job flow; within a performance container, based on the data dependencies among a set of tasks of the job flow, derive an order of performance of the set of tasks that includes a subset able to be performed in parallel, and derive a quantity of task containers to enable the parallel performance of the subset; based on the derived quantity of task containers, derive a quantity of virtual machines (VMs) to enable the parallel performance of the subset; provide, to a VM allocation routine, an indication of a need for provision of the quantity of VMs; and store, within a task queue, multiple task routine execution request messages to enable parallel execution of task routines within the quantity of task containers to cause the parallel performance of the subset.

Abstract: In a general aspect, user requests for access distributed quantum computing resources in a distributed quantum computing system are managed. In a general aspect, a job request for accessing a quantum computing resource is received. The job request includes a user id and a program. On authentication of a user associated with the job request, a job identifier is assigned to the job request, and a particular quantum computing resource is selected for the job request. The job request is individualized based on user permissions and pushed onto a queue to be processed for execution by the quantum computing resource.

Abstract: A computing system is provided, including a processor configured to identify a plurality of measurement sequences that implement a logic gate. Each measurement sequence may include a plurality of measurements of a quantum state of a topological quantum computing device. The processor may be further configured to determine a respective estimated total resource cost of each measurement sequence of the plurality of measurement sequences. The processor may be further configured to determine a first measurement sequence that has a lowest estimated total resource cost of the plurality of measurement sequences. The topological quantum computing device may be configured to implement the logic gate by applying the first measurement sequence to the quantum state.

Abstract: Transaction-enabling systems and methods are disclosed. A system may include a fleet of machines each having a task resource requirement. A controller may include a resource requirement circuit to determine an amount of a resource required for each of the machines to service the task and a resource distribution circuit structured to adaptively improve a utilization of the resource for each of the fleet of machines.

Abstract: Generic Concurrency Restriction (GCR) may divide a set of threads waiting to acquire a lock into two sets: an active set currently able to contend for the lock, and a passive set waiting for an opportunity to join the active set and contend for the lock. The number of threads in the active set may be limited to a predefined maximum or even a single thread. Generic Concurrency Restriction may be implemented as a wrapper around an existing lock implementation. Generic Concurrency Restriction may, in some embodiments, be unfair (e.g., to some threads) over the short term, but may improve the overall throughput of the underlying multithreaded application via passivation of a portion of the waiting threads.

Abstract: An electronic device includes a master processor, and processors operatively coupled to the master processor. The master processor processes a task including subtasks using the processors. Each processor is assigned to at least one subtask of the subtasks to process at least one subtask. The master processor groups the subtasks into groups in consideration of execution dependencies among the subtasks, regardless of which processor of the processors is to process at least one subtask, compare a number of the groups and a number of the processors to generate a comparison result, generate worker threads, wherein a number of the worker threads depends on the comparison result, and process the subtasks using the processors through the worker threads.

Abstract: A method (400) of maintaining availability of service instances (362) on a distributed system (200) includes executing a pool of primary virtual machine (VM) instances (350P), each primary VM instance executing a corresponding individual service instance and including a rate of unavailability. The method also includes determining a number of secondary VM instances (350S) required to maintain availability of the individual service instances when one or more of the primary VM instances are unavailable based on the number of primary VM instances in the pool of primary VM instances and the rate of unavailability. The method also includes instantiating a pool of secondary VM instances based on the number of secondary VM instances required to maintain availability of the individual service instances.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying a set of resources in response to crawling multiple webpages that use at least one resource in the set. For each resource in the set, a system determines an age of the resource using a timestamp for the resource. The system determines a pre-fetch measure of the resource based on the age of the resource and usage information that describes use of the resource at a webpage. The system selects a first resource from the set based on the pre-fetch measure and determines whether a respective age of the selected first resource exceeds a threshold age. The system generates an index entry for a pre-fetch index. The index entry includes a command to pre-fetch the first resource based on a determination that the respective age of the first resource exceeds the threshold age.

Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for allocating computing resources for a data object. The system obtains a plurality of characteristics of a data object, and estimates, from the obtained characteristics, one or more cumulative sustainability metrics characterizing one or more categories of energy consumption during a life-cycle of the data object. The system further determines, from the cumulative sustainability metrics, allocations of one or more computing resources to the data object to optimize one or more objectives including minimizing a cumulative carbon cost during the life-cycle of the data object.

Abstract: The present disclosure describes apparatuses and methods for automatically mapping virtual functions to storage media to enable single root input output virtualization. A storage media switch manages access to virtual functions that execute behind a storage media interface managed by the switch. The switch includes a host interface through which the switch receives host commands. The switch determines virtual function identifiers associated with the host commands and automatically selects the virtual functions of the storage media based on the virtual function identifiers. The switch executes the host commands over the storage media interface using the virtual functions, and after execution, responds via the host interface to each of the host commands. By automatically mapping virtual functions in this way, the switch automatically enables single root input output virtualization of storage media, including storage media that is without native support for input output virtualization.

Abstract: A processor-implemented method is disclosed.