Dynamic and selective hardware acceleration

    公开(公告)号:US10719366B1

    公开(公告)日:2020-07-21

    申请号:US15658221

    申请日:2017-07-24

    Abstract: Methods, systems, and computer-readable media for dynamic and selective hardware acceleration are disclosed. An indirection layer receives a plurality of computation calls generated by an application. The application and the indirection layer are executed by at least one processor of a computing device, and the application links to the indirection layer. The indirection layer determines whether to execute individual computation calls using the at least one processor or using the hardware accelerator. The indirection layer sends one or more of the computation calls and associated data to the hardware accelerator. The one or more of the computation calls are executed using the hardware accelerator, and one or more results are returned from the hardware accelerator to the indirection layer.

    Configuring and deploying Monte Carlo simulation pipelines

    公开(公告)号:US11055454B1

    公开(公告)日:2021-07-06

    申请号:US16012420

    申请日:2018-06-19

    Abstract: Techniques for performing Monte Carlo simulations within a provider network are described. A request to perform a Monte Carlo simulation is received that specifies a template identifying input parameters to the simulation. The simulation is performed in one or more virtual machines (VMs) by sampling input values from an input data distribution stored at a first network location specified in the template and by processing the sampled input values using an input parameter specified in the template to form an output distribution that is stored at a second network location specified in the template. A statistic of the output distribution is generated and sent to an electronic device.

    System and method for storage volume compression

    公开(公告)号:US10824374B1

    公开(公告)日:2020-11-03

    申请号:US16017871

    申请日:2018-06-25

    Abstract: Intelligent compression of data storage volumes in a service provider system. For example, in one embodiment of a computer-implemented method, attachment metrics are compiled for block storage volumes coupled to a storage server. The attachment metrics may include temporal data related to block storage volume detachments and attachments in relation to a plurality of compute instances; and prioritizing compression of the block storage volumes based on the attachment metrics; and compressing the block storage volumes in accordance with the prioritization.

    Optimizing background tasks based on forecast data

    公开(公告)号:US11003491B1

    公开(公告)日:2021-05-11

    申请号:US16138413

    申请日:2018-09-21

    Abstract: Techniques for optimizing background tasks based on forecast data are described. Customer workloads may be monitored by a local monitor in a first time period. Future customer workloads in a second time period following the first time period may be forecast based at least on the customer workloads using a local model. A background availability may be determined based at least on the future customer workloads. Execution of at least one background workload may be scheduled to use the background availability during the second time period. The local monitor may then cause the execution of the at least one background workload.

    Monte Carlo simulation monitoring and optimization

    公开(公告)号:US11226885B1

    公开(公告)日:2022-01-18

    申请号:US16012407

    申请日:2018-06-19

    Abstract: Techniques for monitoring and optimizing Monte Carlo simulations within a provider network are described. A metric representing a similarity between a first data distribution associated with a Monte Carlo simulation template and a second data distribution associated with a data source is generated and evaluated against a condition based on a threshold. A new Monte Carlo simulation template is generated based on the Monte Carlo simulation template. A Monte Carlo simulation is run based on the new Monte Carlo simulation template using a plurality of virtual machines (VMs).

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