Distributed training method for ai model and related device

A computing device, comprising:

• a processor;
• and
• a memory coupled to the processor to store instructions, which when executed by the processor, cause the computing device to perform operations, the operations comprising:
• performing fault isolation on a first computing node, wherein the first computing node is a faulty computing node in a plurality of computing nodes, wherein an artificial intelligence (AI) platform is deployed on the computing device, the AI platform is associated with a computing resource pool, the computing resource pool comprises the plurality of computing nodes for distributed training of an AI model, and each of the plurality of computing nodes performs a training task for the distributed training of the AI model;
• determining a second computing node other than the plurality of computing nodes in the computing resource pool;
• and
• configuring the second computing node that replaces the first computing node to execute the training task.

A non-transitory machine-readable storage medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations, the operations comprising:

• performing fault isolation on a first computing node, wherein the first computing node is a faulty computing node in a plurality of computing nodes, wherein an artificial intelligence (AI) platform is deployed on a computing device, the AI platform is associated with a computing resource pool, the computing resource pool comprises the plurality of computing nodes for distributed training of an AI model, and each of the plurality of computing nodes performs a training task for the distributed training of the AI model;
• determining a second computing node other than the plurality of computing nodes in the computing resource pool;
• and
• configuring the second computing node that replaces the first computing node to execute the training task.