Model training system and method, and related device

A model training method, applied to a distributed training system, wherein the distributed training system comprises a plurality of nodes, and parameters required for training a model are distributed in the plurality of nodes:

• wherein a first node in the plurality of nodes comprises a first memory and a second memory, the first memory and the second memory respectively store some parameters of the model, and the first memory and the second memory communicate with a processor in the first node according to different protocols;
• and
• wherein the method comprises:
• sending, by a second node in the plurality of nodes, a plurality of parameter obtaining requests to the first node, wherein the plurality of parameter obtaining requests are used to obtain parameters required by the second node to train the model;
• determining, by the first node based on the plurality of parameter obtaining requests, that the parameters obtained based on the plurality of parameter obtaining requests are respectively stored in the first memory and the second memory;
• combining, by the first node, a parameter obtained from the first memory and a parameter obtained from the second memory to obtain a combined parameter;
• sending, by the first node, the combined parameter to the second node;
• receiving, by the second node, the combined parameter;
• and
• training, by the second node, the model based on the combined parameter.

A non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores instructions which, when run on a computing node, cause the computing node to perform operations comprising:

• sending, by a second node in a plurality of nodes of a distributed training system, a plurality of parameter obtaining requests to a first node in the plurality of nodes, wherein the plurality of parameter obtaining requests are used to obtain parameters required by the second node to train a model, the parameters are distributed in the plurality of nodes, the first node comprises a first memory and a second memory, the first memory and the second memory respectively store some parameters of the model, and the first memory and the second memory communicate with a processor in the first node according to different protocols;
• determining, by the first node based on the plurality of parameter obtaining requests, that the parameters obtained based on the plurality of parameter obtaining requests are respectively stored in the first memory and the second memory;
• combining, by the first node, a parameter obtained from the first memory and a parameter obtained from the second memory to obtain a combined parameter;
• sending, by the first node, the combined parameter to the second node;
• receiving, by the second node, the combined parameter;
• and
• training, by the second node, the model based on the combined parameter.