Block method for performance-aware block sparse lu decomposition on gpu platforms
By constructing a GPU computing kernel performance function and a greedy heuristic strategy, the universality problem of irregular block division in sparse LU decomposition is solved, realizing high-performance sparse LU decomposition on heterogeneous platforms. It is applicable to heterogeneous platforms with multi-core CPUs and GPUs, improving the performance of the numerical decomposition stage.
CN122111645APending Publication Date: 2026-05-29ZHEJIANG UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG UNIV
- Filing Date
- 2026-01-06
- Publication Date
- 2026-05-29
Smart Images
Figure CN122111645A_ABST
Abstract
The present application belongs to the technical field of sparse matrix decomposition, and relates to a block method of performance-aware block sparse LU decomposition for a GPU platform, comprising the following steps: S1, constructing a performance function of a GPU computing kernel based on statistical data; S2, based on the performance function, designing a decision method for deciding whether to block a sparse matrix at a specified position; and S3, decomposing the overall block problem of a large-scale sparse matrix into multiple sub-problems decided in sequence, solving each sub-problem one by one based on a greedy heuristic strategy and using the decision method, and obtaining a final specific block scheme. Compared with existing methods, the method of the present application is more excellent in performance in the numerical decomposition stage, and is not only suitable for a heterogeneous platform of multi-core CPU and GPU, but also suitable for a pure CPU architecture.
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