An executor creation system and an executor creation method

Abstract

The invention discloses an executor creation system. The system comprises a task topological graph generation component used for decomposing a to-be-completed job into a series of tasks executed by an executor in a heterogeneous architecture and generating task relationship topological graphs while the job is decomposed based on the inherent relationship between the decomposed tasks, wherein task nodes of the task topological graph contain all node attributes required for executing corresponding tasks; wherein the task topological graph generation component comprises a specified group element node selection unit which is used for selecting a specific task node with a specified group element containing additional node attributes according to a specific task in a task relation topological graph generation process, and the additional node attributes change a mode that the specific task node executes a corresponding task; and an actuator creation assembly for creating a corresponding executor for each task node in the computing resource based on the task relationship topological graph and all node attributes of each task node or all node attributes containing the appointed group elements, and enabling the specific executor corresponding to the specific task node with the additional node attribute to execute the corresponding task according to the additional node attribute.

Description

technical field [0001] The present disclosure relates to a system and method for fine-grained management and hardware optimization of storage space in a data processing network, and more specifically, to an executive creation system and execution creation method in a data processing network. Background technique [0002] With the development of machine learning and the gradual deepening of artificial neural network research, the concept of deep learning has been widely concerned and applied. Deep learning is a special kind of machine learning. It uses a network hierarchical structure to express the learning objects, combines simple concepts into abstract concepts, and realizes abstract concept expression through simple concept calculations. At present, deep learning has made great progress in the fields of image recognition, speech recognition and natural language processing. Deep learning involves a large number of model parameters, resulting in a huge amount of calculatio...

AI Technical Summary

Problems solved by technology

This will lead to waste of resources during the processing of data blocks at some execution bodies, and even cause the operation process to be too slow due to the upstream and downstream relationship to empty data blocks and affect the operation of downstream execution bodies

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