Construction method and device of deep learning development environment, equipment and medium

Abstract

The invention discloses a construction method and device of a deep learning development environment, electronic equipment and a computer readable storage medium. The construction method of the deep learning development environment comprises the steps of receiving input hardware resource setting parameters and a deep learning training framework type; based on a preset development environment scheduling system, allocating hardware resources to the deep learning development environment according to the hardware resource setting parameters, and obtaining and loading a corresponding type of deep learning training framework container mirror image; and based on a development environment scheduling system, loading a driver matched with hardware resources, and starting a deep learning development environment. Based on a preset development environment scheduling system, the deep learning development environment can be quickly and effectively built in a large-scale GPU cluster in a container deployment mode, the workload of developers is reduced, the limitation in the development environment building process is effectively improved, the flexible allocation of users is improved, the user operation is greatly facilitated, and the building efficiency and quality of the development environment are improved.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, in particular to a construction method, device, electronic equipment and computer-readable storage medium of a deep learning development environment. Background technique [0002] With the vigorous development of the artificial intelligence (AI) industry, the computing resources and data resources required for AI applications are becoming larger and larger. Usually, AI applications are built based on GPU clusters, but with the expansion of the cluster size, how to quickly allocate GPU computing resources to build an AI training environment has become an urgent problem to be solved. [0003] Currently in the industry, it is common for cluster administrators to manually allocate resources and manually create a deep learning development environment. As the scale of GPU clusters becomes larger and larger, manual allocation becomes more and more complex and difficult; and in...

AI Technical Summary

Problems solved by technology

As the scale of GPU clusters is getting larger and larger, the complexity and difficulty of manual allocation is increasing; and the existing technology relies on virtual machines to build AI environments with more restrictions, resulting in heavy manual operations, cumbersome processes, and poor flexibility

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