Cluster task resource allocation method and device, computer device and storage medium

Abstract

The invention relates to a cluster task resource allocation method and device, a computer device and a storage medium. The method comprises the steps of obtaining task feature information of a to-be-processed cluster task; determining a task category of the to-be-processed cluster task based on the task feature information, and determining a resource prediction model corresponding to the task category of the to-be-processed cluster task; based on the task feature information and the corresponding resource prediction model, obtaining resource demand information of the to-be-processed cluster task; and performing resource allocation for the to-be-processed cluster task according to the resource demand information. According to the method provided by the embodiment of the invention, requiredresources can be accurately allocated to each cluster task.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a cluster task resource allocation method and device, a computer device and a storage medium. Background technique [0002] With the increase of computing demand, more and more computing centers provide cluster services. Developers can remotely submit cluster tasks to cluster computing centers that provide cluster services, so that the cluster computing centers can perform calculations and obtain the final calculation results. . [0003] For the cluster computing center, it usually faces a large number of developers and receives a large number of cluster tasks, and the resources required for different types of cluster tasks vary greatly, such as stand-alone Computing-intensive tasks in the network basically do not rely heavily on network resources, while multi-machine distributed machine learning tasks may have a very large demand on network resources, and the use of r...

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Problems solved by technology

[0004] A processing method provided in the prior art is to set the required resources by the developer who submits the cluster task. However, the developer usually does not have a clear understanding of the specific resource requirements, and the resource setting information provided by him is often different from the The actual situation is quite different

[0005] Therefore, in the prior art, there is a problem that it is impossible to accurately predict the resource requirements of the cluster tasks submitted by developers, and it is easy to cause uneven resource allocation in the cluster computing center, and the problem that the cluster tasks cannot be executed due to insufficient resources.

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