Abstract: A method for detecting comprehensive GPU-related factors of a distributed cluster, the method including: (1): checking whether there is a configuration file content of an operating node; (2): reading a mode parameter in an environment variable of the operating node, and correspondingly switching an operating mode according to the mode parameter; (3): reading a timer frequency value from the environment variable of the operating node so as to set a time period for reading a GPU information parameter according to the timer frequency value; (4): calculating the maximum value of the GPU information parameter of the operating node, and storing the maximum value into the GPU information list cache; and (5): initializing the transmitted information; determining whether there is a GPU in the GPU information list cache of the operating node.

Abstract: The present disclosure discloses a workflow scheduling method and system based on a multi-target particle swarm algorithm, and a storage medium. The method comprises the following steps that first, the difference between the frequency reduction characteristic and the execution time of each server in a cluster is considered; a multi-target comprehensive evaluation model covering workflow execution overhead, execution time and cluster load balance is constructed on the basis of a traditional model; second, a multi-target particle swarm algorithm is provided for workflow scheduling, and an efficient solving method is provided. The method alleviates the defects of premature convergence and low species diversity of the particle swarm algorithm, reduces the execution overhead and execution time of the workflow on the cluster server, and better balances the load of the cluster server.

Abstract: A method for detecting comprehensive GPU-related factors of a distributed cluster, the method including: (1): checking whether there is a configuration file content of an operating node; (2): reading a mode parameter in an environment variable of the operating node, and correspondingly switching an operating mode according to the mode parameter; (3): reading a timer frequency value from the environment variable of the operating node so as to set a time period for reading a GPU information parameter according to the timer frequency value; (4): calculating the maximum value of the GPU information parameter of the operating node, and storing the maximum value into the GPU information list cache; and (5): initializing the transmitted information; determining whether there is a GPU in the GPU information list cache of the operating node.