RELATED APPLICATION(S)

The present application claims priority to Chinese Patent Application No. 201810359117.7, filed Apr. 20, 2018, and entitled “Method, Apparatus, and Computer Program Product for Processing Computing Task,” which is incorporated by reference herein in its entirety.

FIELD

Implementations of the present disclosure generally relate to a computing system comprising dedicated processing resources, and more specifically, to a method, apparatus and computer program product for processing a computing task.

BACKGROUND

Applications on the client can be designed to complete various processing or analyzing tasks using computing resources, such as processing and storage resources. As the requirement and complexity of the tasks such as machine learning, deep learning, and data mining continuously grow, it requires a large amount of and/or variable computing resources to satisfy operations of the corresponding application. This can be fulfilled by a machine or system having multiple dedicated processing resources, where the application can be scheduled to operate on one or more dedicated processing resources of the machine or system. For example, a cloud-based computing system has already been developed, and this computing system comprises a machine having one or more dedicated processing resources. Different clients can rent computing resources (for example, dedicated processing resources) of the system as required to operate their own applications.

With the development of computer technologies, there is an increasing variety of computing resources, which are no longer limited to traditional ones like central processing units. For example, currently the computing capacity of the graphic processing units (GPUs) gets growingly strong. GPUs are particularly suitable to execute computing tasks in deep learning, high performance computing, machine learning and so on by virtue of their distinctive properties. However, for ordinary client devices and conventional cloud computing devices, their graphic processing units are rather limited in performance and lack a high performance processing capacity. At this point, how to process a computing task using (e.g., remotely) the computing capacity of a graphic processing unit of other device becomes a focus of research.

However, some existing technical solutions fail to make sufficient and effective use of the processing capacity of remote computing resources (e.g., computing resources in a computing resource pool), but idleness or workload unbalance might arise in the resource pool. Therefore, it is desirable to provide a technical solution for easily and effectively processing a computing task using multiple computing resources in the resource pool.

SUMMARY

Implementations of the present disclosure provide a method, apparatus and corresponding computer program product for processing a computing task.

According to a first aspect of the present disclosure, there is provided a method for processing a computing task. The method comprises: obtaining status information of multiple computing resources; in response to receiving a neural network model-based computing task, determining configuration information of multiple layers associated with the neural network model; obtaining parameter data associated with at least one part of the multiple layers on the basis of the configuration information; and based on the status information and the parameter data, selecting from the multiple computing resources a group of computing resources for processing the computing task.

According to a second aspect of the present disclosure, there is provided an apparatus for processing a computing task. The apparatus comprises: at least one processor; and a memory coupled to the at least one processor, the memory having instructions stored thereon, the instructions, when executed by the at least one processor, causing the apparatus to perform acts comprising: obtaining status information of multiple computing resources; in response to receiving a neural network model-based computing task, determining configuration information of multiple layers associated with the neural network model; obtaining parameter data associated with at least one part of the multiple layers on the basis of the configuration information; and based on the status information and the parameter data, selecting from the multiple computing resources a group of computing resources for processing the computing task.

According to a third aspect of the present disclosure, there is provided a computer program product. The computer program product is tangibly stored on a computer readable medium and comprises machine executable instructions which, when executed, cause the machine to implement a method according to the first aspect.

The Summary is to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the present disclosure, nor is it intended to be used to limit the scope of the present disclosure.

