Optimization strategy generation method and operator construction method
CN114253550BActive Publication Date: 2025-04-04SHANGHAI BIREN TECH CO LTD
Patent Information
- Application Number
- CN202111511431.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2021-12-02
- Publication Date
- 2025-04-04
- Estimated Expiration
- 2041-12-02
AI Technical Summary
Technical Problem
In the prior art, there are problems such as high complexity, low efficiency and high cost in model development.
Method used
Through an optimization strategy generation method, an abstract description of the strategy is determined, a fusion operator is built based on this, and the performance optimization of the fusion operator is optimized, and finally a general optimization strategy is determined to reduce the complexity and cost of model development.
Benefits of technology
It realizes reducing the complexity of model development, decoupling the complexity of hardware and algorithms, and generates a general optimization strategy suitable for various models, which improves the parallelism of kernel development.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN114253550B_ABST
Abstract
The present invention provides an optimization strategy generation method and an operator construction method, wherein the optimization strategy generation method comprises: determining a strategy abstract description; constructing a fusion operator based on the strategy abstract description; optimizing the performance of the fusion operator, and determining a general optimization strategy based on the strategy abstract description under the fusion operator after performance optimization, thereby overcoming the defects of low efficiency and high cost of developing models using the development method in traditional solutions, reducing the complexity of model development, decoupling hardware complexity and algorithm complexity, generating a general optimization strategy applicable to various models, and realizing the improvement of the parallelism of the entire kernel development.
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Citation Information
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