The embodiment of the invention provides a
GPU cluster deep learning task parallelization method, a
GPU cluster deep learning task parallelization device and
electronic equipment, and relates to the technical field of internet. The method comprises the following steps: firstly, analyzing the similarity between a to-be-processed
deep learning task and each computing node of a
GPU cluster; determining a target computing node of the to-be-processed deep learning task in the GPU cluster, reducing the possibility of computing node
resource contention, and improving the
utilization rate and the execution efficiency of deep learning task
system resources; according to the number of GPUs required by the to-be-processed deep learning task, obtaining a to-be-processed deep learning task; dividing the to-be-processed deep learning task into a plurality of target sub-tasks, analyzing the interference level and the communication cost of the target subtask; determining the target GPU of the target sub-task in the target computing node, and avoiding unbalanced
resource allocation on the GPU in the computing node. The high parallelization of the deep learning task is realized. The
resource utilization rate of the GPU cluster is improved. Meanwhile, the execution efficiency of the deep learning task is improved.