A method for a first set of processors and a second set of processors comprises, the first set of processors processing a set of queries, as a result of a change in utilization of the first set of processors, processing the set of queries using the second set of processors. The change in processors is independent of a change in storage resources, the storage resources shared by the first set of processors and the second set of processors.

Various techniques for emulating edge locations in cloud-based networks are described. An example method includes generating an emulated edge location in a region. The emulated edge location can include one or more first computing resources in the region. A host in the region may launch a virtualized resource a portion of the one or more first computing resources. Output data that was output by the virtualized resource in response to input data can be received and reported to a user device, which may provide a request to migrate the virtualized resource to a non-emulated edge location. The non-emulated edge location may include one or more second computing resources that are connected to the region by an intermediary network. The virtualized resource can be migrated from the first computing resources to at least one second computing resource in the non-emulated edge location.

Cloud migration may be performed by identifying applications that are currently operating in the enterprise and performing certain determinations as to whether those applications are proper candidates for the migration to the cloud. One example method of operation may provide identifying at least one application operating on an enterprise network, retrieving current usage data of the at least one application, comparing the current usage data of the at least one application to a threshold amount of usage data to determine whether the application has exceeded the threshold amount of usage data. Next, the creation of an instance process may be performed on an entity operating outside the enterprise network and the application may be operated via the instance process and otherwise terminated in the enterprise network to alleviate resources.

Disclosed are aspects of virtual graphics processing unit (vGPU) scheduling-aware virtual machine migration. Graphics processing units (GPUs) that are compatible with a current virtual GPU (vGPU) profile for a virtual machine are identified. A scheduling policy matching order for a migration of the virtual machine is determined based on a current vGPU scheduling policy for the virtual machine. A destination GPU is selected based on a vGPU scheduling policy of the destination GPU being identified as a best available vGPU scheduling policy according to the scheduling policy matching order. The virtual machine is migrated to the destination GPU.

Techniques are disclosed for scheduling artificial intelligence model partitions for execution in an information processing system. For example, a method comprises the following steps. An intermediate representation of an artificial intelligence model is obtained. A reversed computation graph corresponding to a computation graph generated based on the intermediate representation is obtained. Nodes in the reversed computation graph represent functions related to the artificial intelligence model, and one or more directed edges in the reversed computation graph represent one or more dependencies between the functions. The reversed computation graph is partitioned into sequential partitions, such that the partitions are executed sequentially and functions corresponding to nodes in each partition are executed in parallel.

To more properly size resources in a destination to which IT resources will be migrated, a system for appraising a resource configuration estimates a source's load model representing a load of first resources in a first computer system which is the source of migration and estimates a destination's load model representing a load of second resources to be built by migrating the first resources to a second computer system based on the source's load model. The system compares performance requirements of the first resources against the destination's load model and finds the destination's load model that is conformable to the performance requirements. When determining design values of the second resources' configuration, the system corrects those design values based on the destination's load model estimated conformable to the performance requirements to decrease design margins of the resource configuration using a design correction value defined to meet a service level requested.

Embodiments of the invention may improve the performance of multi-processor systems in processing information received via a network. For example, some embodiments may enable configuration of a system such that information received via a network may be distributed among multiple processors for efficient processing. A user (e.g., system administrator) may select from among multiple configuration options, each configuration option being associated with a particular mode of processing information received via a network. By selecting a configuration option, the user may specify how information received via the network is processed to capitalize on the system's characteristics, such as by aligning processors on the system with certain NICs. As such, the processor(s) aligned with a NIC may perform networking-related tasks associated with information received by that NIC. If initial alignment causes one or more processors to become over-burdened, processing tasks may be dynamically re-distributed to other processors so as to achieve a more even distribution of the overall processing burden across the system.

This disclosure describes systems, devices, and techniques for migrating virtualized resources between the main region and edge locations. Live migration enables virtualized resources to remain operational during migration. Edge locations are typically separated from secure data centers via the Internet, a direct connection, or some other intermediate network. Accordingly, to place virtualized resources within an edge location, the virtualized resources must be migrated over a secure communication tunnel that can protect virtualized resource data during transmission over the intermediate network. The secure communication tunnel may have limited data throughput. To efficiently utilize resources of the secure communication tunnel, and to reduce the impact of migrations on virtualized resource operations, virtualized resource migrations may be carefully scheduled in advance. For instance, virtualized resources may be selectively migrated at times-of-day in which they are likely to be relatively idle, or at times when the communication tunnel is predicted to have sufficient bandwidth.

Embodiments include an asymmetric multiprocessing (AMP) system having a first central processing unit (CPU) cluster comprising a first core type, and a second CPU cluster comprising a second core type, where the AMP system can update a thread metric for a first thread running on the first CPU cluster based at least on: a past shared resource overloaded metric of the first CPU cluster, and on-core metrics of the first thread. The on-core metrics of the first thread can indicate that first thread contributes to contention of the same shared resource corresponding to the past shared resource overloaded metric of the first CPU cluster. The AMP system can assign the first thread to a different CPU cluster while other threads of the same thread group remain assigned to the first CPU cluster. The thread metric can include a Matrix Extension (MX) thread flag or a Bus Interface Unit (BIU) thread flag.

Techniques discussed herein relate to providing composable edge devices. In some embodiments, a user request specifying a set of services to be executed at a cloud-computing edge device may be received by a computing device operated by a cloud computing provider. A manifest may be generated in accordance with the user request. The manifest may specify a configuration for the cloud-computing edge device. Another request can be received specifying the same or a different set of services to be executed at another edge device. Another manifest which specifies the configuration for that edge device may be generated and subsequently used to provision the request set of services on that device. In this manner, manifests can be used to compose the platform to be utilized at any given edge device.