A scheduler, a method of operating the scheduler, and an accelerator apparatus including the scheduler are disclosed. A method of operating a scheduler to perform scheduling on models to be executed in an accelerator, the method includes receiving at least one execution request for a first model and a second model that are executed independently from each other in the accelerator, and performing layer-unit scheduling on the first model and the second model based on workload characteristics of the first model and the second model.

A system and method of dynamically controlling a reservation of resources within a cluster environment to maximize a response time are disclosed. The method embodiment of the invention comprises receiving from a requestor a request for a reservation of resources in the cluster environment, reserving a first group of resources, evaluating resources within the cluster environment to determine if the response time can be improved and if the response time can be improved, then canceling the reservation for the first group of resources and reserving a second group of resources to process the request at the improved response time.

The present invention describes a system and a method for dynamically optimising the computing resources allocated to a client application in different data regions of one or more service providers. A number of monitoring modules are provided in each data regions, which are configured to collect operational information from each data region, which is communicated to the other data regions. As such, all data regions are aware of the operational environment of the other data regions.

In one embodiment, an apparatus comprises a storage device and a processor. The storage device stores a plurality of images captured by a camera. The processor: accesses visual data associated with an image captured by the camera; determines a tile size parameter for partitioning the visual data into a plurality of tiles; partitions the visual data into the plurality of tiles based on the tile size parameter, wherein the plurality of tiles corresponds to a plurality of regions within the image; compresses the plurality of tiles into a plurality of compressed tiles, wherein each tile is compressed independently; generates a tile-based representation of the image, wherein the tile-based representation comprises an array of the plurality of compressed tiles; and stores the tile-based representation of the image on the storage device.

A computer-implemented method and a computer program product for estimating attributes of running workloads on platforms in a system of multiple platforms as a service. A computer receives definitions of respective workloads and respective platforms that are eligible to run a set of the respective workloads. The computer maps the respective workloads and the respective platforms to attributes of running the respective workloads on the respective platforms. The computer estimates the attributes and storing the attributes in a matrix. The computer updates the attribute in the matrix, in response to a triggering event for modifying the matrix.

A computer-implemented method, a computer program product, and a computer system for optimizing workload placements in a system of multiple platforms as a service. A computer first places respective workloads on respective platforms that yield lowest costs for the respective workloads. The computer determines whether mandatory constraints are satisfied. The computer checks best effort constraints, in response to the mandatory constraints being satisfied. The computer determines a set of workloads for which the best effort constraints are not satisfied and determines a set of candidate platforms that yield the lowest costs and enable the best effort constraints to be satisfied. From the set of workloads, the computer selects a workload that has a lowest upgraded cost and updates the workload by setting an upgraded platform index.

A computer-implemented method, a computer program product, and a computer system for placements of workloads in a system of multiple platforms as a service. A computer detects a triggering event for modifying a matrix that pairs respective workloads on respective platforms and includes attributes of running respective workloads on respective platforms. The computer recalculates the attributes in the matrix, in response to the triggering event being detected. The computer determines optimal placements of the respective workloads on the respective platforms, based on information in the matrix. The computer places the respective workloads on the respective platforms, based on the optimal placements.

Approaches for managing how the passage of time is observed by a software execution environment, such as a virtual machine or a sandbox environment. A computer system maintains a set of physical time sources. A set of virtual time sources are computed based on the set of physical time sources. The virtual time sources operate independently of the set of physical time sources. For example, the virtual time sources may observe time passing faster or slower than the set of physical time sources. The set of virtual time sources are presented to the software execution environment as the set of time sources. Many benefits may be obtained such as higher utilization of allocated resources and avoidance of timeouts.

Disclosed in the present invention is a spontaneous edge application deployment and pricing method based on an incentive mechanism. The method comprises the following steps: building an edge end application oriented spontaneous deployment system architecture; then proposing an incentive mechanism aiming at spontaneous edge application deployment and prizing; solving the spontaneous edge application deployment and prizing problem based on a backward induction method, thereby obtaining an optimal deployment solution of an edge server and an optimal prizing strategy of an application provider.

The latency corresponding to a latency-sensitive event-based processor is evaluated to determine whether the latency-sensitive event-based processor (EBP) should be prioritized. If so, constraints on the number of events that the latency-sensitive EBP can process are relaxed and the frequency with which the latency-sensitive EBP can process events is increased. At a next latency evaluation, if the latency-sensitive EBP no longer meets criteria for prioritization, the constraint on the number of events is returned to a nominal level, as is the frequency with which the latency-sensitive EBP can process events.