Operator generation methods, apparatus, electronic devices and media

By acquiring structured operator description information and using automated methods for generating large language models, the problems of high development cost and low performance of BLAS operators are solved. High-performance BLAS operator generation across multiple hardware architectures is achieved, reducing the technical threshold and improving the reliability of the generated code.

CN122308835APending Publication Date: 2026-06-30INST OF SOFTWARE - CHINESE ACAD OF SCI
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
INST OF SOFTWARE - CHINESE ACAD OF SCI
Filing Date
2026-02-06
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

In existing technologies, BLAS operators have high development costs, high technical barriers, rely on experts and cannot be generated efficiently and automatically. Furthermore, the assembly code generated by LLM has low performance and is difficult to optimize across various hardware architectures.

Method used

By acquiring structured operator description information, including algorithm-level and register-level descriptions, it is decomposed into multiple functional blocks, generating kernel-level code, which is then combined with a runtime framework. Automated code generation is achieved using a large language model, and optimization is performed by combining compilation testing and runtime testing, ultimately generating a high-performance BLAS operator.

Benefits of technology

It achieves high-performance BLAS operator generation across multiple hardware architectures, significantly reducing development costs and time. Its performance is superior to direct generation by LLM and manual optimization by experts, and it has excellent cross-architecture capabilities and code generation reliability.

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Abstract

This invention relates to the fields of computer and software engineering technology, and provides an operator generation method, apparatus, electronic device, and medium, comprising: acquiring structured operator description information, wherein the structured operator description information includes algorithm-level description and register-level description, wherein the algorithm-level description is generated based on operator decomposition results, the operator decomposition results decompose the target operator to be generated into multiple functional blocks, and the register-level description indicates the data flow and register usage strategy of each functional block; performing a kernel-level generation process based on the structured operator description information to obtain kernel-level code, wherein the kernel-level code includes microkernel code and data packaging code; and performing a driver-level generation process based on the kernel-level code to obtain target operator code, wherein the driver-level generation process includes combining the kernel-level code with a runtime framework. Thus, high-performance operators across multiple hardware architectures can be generated systematically and automatically.
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