The invention discloses a distributed
artificial intelligence label training supporting method and
system, and belongs to the technical field of
artificial intelligence multi-task training scheduling, and the
system comprises a
user management module which is used for managing user authority and recording user operation; the
data management module is used for uploading, storing, labeling and version control of the data; the
task management module is used for managing hardware resources, creating training, quantifying a model, converting a model format, encrypting a model task and scheduling the task; the
algorithm management module comprises an
algorithm, a model storage, a docker
mirror image server and a
database table for recording
algorithm information; the model publishing module is used for publishing a model and providing a model reasoning capability; and the front-end module is used for providing a user
interaction interface. According to the method, the computing power resources of different GPU servers can be integrated, the steps of
data labeling, training and deployment are opened, heterogeneous distributed training tasks are flexibly scheduled, the
server resources are fully utilized, and the algorithm development difficulty is reduced.