Parallel computing method and system of tensor protocol and computer equipment

By dynamically segmenting tensors on non-criterion dimensions and performing parallel configurations, the problems of low computational efficiency and unbalanced load in the prior art tensor criterion method in multi-core environments are solved, and efficient parallel processing and data consistency are achieved.

CN119718687AActive Publication Date: 2025-03-28青岛国实科技集团有限公司
9 Cites 2 Cited by

Patent Information

Application Number
CN202510227901.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-28
Publication Date
2025-03-28
Estimated Expiration
2045-02-28

AI Technical Summary

Technical Problem

The existing tensor regulation methods are ineffective in multi-core parallel computing environments, such as low computing efficiency, load imbalance, and data transmission bottlenecks, and cannot fully utilize the parallel capabilities of multi-core processors.

Method used

By performing dynamic tensor segmentation on a non-contractual dimension, multiple sub-tensors are obtained and dynamically allocated to multiple computing processing units based on the number of sub-tensors. The recursive algorithm is used to perform parallel regulation, and the final result of the regulation is written back to the main memory.

Benefits of technology

Improves computing efficiency, simplifies the synchronization mechanism, ensures data consistency when the result is written back, avoids potential write conflict problems, and improves the spatial and temporal locality of the data, reducing the number of interactions between the kernel group and memory.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention relates to the technical field of information processing, in particular to a parallel computing method and system for a tensor protocol and computer equipment, and the method comprises the following steps: a tensor segmentation step: dynamically segmenting a high-dimensional tensor based on a non-protocol dimension to obtain a plurality of sub-tensors; a sub-tensor distribution step: distributing a plurality of sub-tensors to a plurality of calculation processing units based on the number of the sub-tensors; a sub-tensor parallel reduction step: performing parallel reduction on the plurality of sub-tensors by the plurality of calculation processing units based on a recursive algorithm to obtain a reduction result tensor; and a reduction result tensor writing-back step: writing the reduction result tensor back to the main memory.
Need to check novelty before this filing date? Find Prior Art