Techniques related to scheduling and load balancing media tasks across heterogeneous hardware units are discussed. Such techniques include estimating completion times of received media tasks and, after submission of the media task to a selected hardware, only checking status of the media task after the estimated completion time.

A data processing apparatus includes a first chip and a second chip that are stacked-packaged. The first chip includes a general-purpose processor, a bus, and at least one first dedicated processing unit (DPU). The general-purpose processor and the at least one first dedicated processing unit are connected to the bus. The general-purpose processor is configured to generate a data processing task. The second chip includes a second dedicated processing unit. At least one of one or more units in the at least one first dedicated processing unit and the second dedicated processing unit can process at least a part of the data processing task based on a computing function.

The present disclosure includes systems, methods, and computer-readable mediums for discovering capabilities of a hardware (HW) accelerator card. A processor may communicate a request for a listing of acceleration services to a HW accelerator card connected to the processor via the communication interface. The HW accelerator card may retrieve the listing from memory and provide a response to the processor that includes a listing of the HW acceleration services provided by the HW accelerator card.

A method and system for distributing a compute model and data to process to heterogeneous and distributed compute devices. The compute model and a portion of the data is processed on a benchmark system and the timing used to make a job execution speed estimate for each compute device. Compute devices are selected and assigned data chunks based on the estimate so distributed processing is completed within a predefined time period. The compute model and data chunks can be sent to the respective compute devices using separate processes, such as a payload manager configured to transfer compute jobs to remote devices and a messaging engine configured to transfer data messages, and where the payload manager and messaging engine communicate with corresponding software engines on the compute devices.

A method, a device, and a computer program product for resource scheduling is disclosed. The method includes determining a job initiated by a virtual machine. The job requests to invoke at least one virtual function in a set of virtual functions associated with the virtual machine and each virtual function in the set of virtual functions is configured to utilize an accelerator resource to provide a single type of acceleration service. The method further includes determining, based on a job type of the job, a first accelerator resource allocated to the at least one virtual function. The accelerator resources required by the virtual functions invoked by the job may then be guaranteed, improving the execution efficiency of the job.

Job execution environment control techniques are described to manage policy selection and implementation to control use of job executors by a computing device, automatically and without user intervention. These techniques are usable to select a policy from a plurality of policies that is then used to control lifecycles of job executors of a job execution environment of a computing device. Further, these techniques are usable to respond dynamically to change the selected policy during runtime of the application in response to changes in the job execution environment.

In at least some embodiments, a store-type operation is received and buffered within a store queue entry of a store queue associated with a cache memory of a processor core capable of executing multiple simultaneous hardware threads. A thread identifier indicating a particular hardware thread among the multiple hardware threads that issued the store-type operation is recorded. An indication of whether the store queue entry is a most recently allocated store queue entry for buffering store-type operations of the hardware thread is also maintained. While the indication indicates the store queue entry is a most recently allocated store queue entry for buffering store-type operations of the particular hardware thread, the store queue extends a duration of a store gathering window applicable to the store queue entry. For example, the duration may be extended by decreasing a rate at which the store gathering window applicable to the store queue entry ends.

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform receiving item data for items from a catalog, assigning a task for evaluation of the item data, storing a plurality of task jobs to a task queue, repeatedly setting, in real time, a respective processor to perform a respective evaluation model, processing the plurality of task jobs stored to the task queue by determining, in real time, whether a first evaluation model set to be performed on a first processor is capable of meeting the first evaluation criteria of the first task data, performing, on the first processor, the first evaluation model on the first task data, and transmitting first first-evaluation-model-output instructions, and repeatedly updating, in real time, the task queue. Other embodiments are disclosed herein.

An apparatus comprises a processing device configured to obtain information associated with services hosted in an information technology infrastructure comprising a core data center hosting a first subset of the services and edge computing sites hosting a second subset of the services. The processing device is also configured to determine, based on the obtained information, values associated with parameters characterizing suitability of hosting respective ones of the services at the computing sites, and to generate, based on the determined values, scores for each of the services. The processing device is further configured to identify, based on the generated scores, at least a given one of the services to be migrated from the core data center to the edge computing devices or from the edge computing sites to the core data center. The processing device is further configured to migrate the given one of the services.

Techniques for routing a request based on a vulnerability in a processing node are disclosed. A vulnerability analyzer determines a set of detected vulnerabilities in each of a set of processing nodes. Based on the detected vulnerabilities, the vulnerability analyzer determines a respective vulnerability score for each processing node. A routing engine receives a request to be processed by at least one of the set of processing nodes. The routing engine selects a particular node for processing the request based on the detected vulnerabilities in one or more of the set of processing nodes. The routing engine may select the particular node based on the vulnerability scores of the set of processing nodes. Additionally or alternatively, the routing engine may select the particular node based on whether the particular node includes any vulnerability that may be exploited by the request.