Data processing method and device, computer equipment and storage medium

Abstract

The invention relates to a data processing method and device, computer equipment and a storage medium. The method comprises the steps: obtaining a target task, and obtaining more than one data set corresponding to the target task in parallel; determining an instruction stream corresponding to the target task, wherein the instruction stream comprises more than one target instruction determined by atriggering sequence; and circularly triggering various target instructions according to the triggering sequence, and when each target instruction is triggered, sequentially taking each data set in the more than one data set as a triggering object until each triggered target instruction is executed to obtain an operation result corresponding to the target task. By adopting the method, the data processing efficiency can be improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a data processing method, device, computer equipment and storage medium. Background technique [0002] With the development of computer technology, machine learning technology has emerged. Various machine learning models based on machine learning technology can improve the accuracy of the model through a large number of calculations. In practical applications, machine learning models can be used to deploy rich online services. . A machine learning model usually includes multiple operators. If the calculation time of each operator is too long, the service response will be too slow. For example, for the BERT model (Bidirectional Encoder Representation from Transformers, a general pre-trained language representation model) in the field of natural language, in actual application scenarios, rich online service scenarios can be deployed based on the BERT model. In this sc...

AI Technical Summary

Problems solved by technology

When processing the smallest unit, if multiple instructions need to be issued, and the operands of different instructions have dependencies, then the issuance of the subsequent instructions must wait for the execution of the previous instructions to be completed before they can be issued, which may easily cause the instruction to be stuck.

In this way, the overall time consumption of processing multiple minimum processing units is very large, and there is a problem of low efficiency in batch processing a large amount of data

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