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.