Advancing Matrix Operations for High-Performance and Memory-Efficient Automata Processing on GPUs

Finite state automata are essential in various domains, such as pattern matching and data analytics, where high throughput is critical. Recent work has explored representing automata execution as matrix algebra and leveraging CPU Basic Linear Algebra Subprograms (BLAS) libraries. While promising, th...

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Bibliographic Details
Published in:	ACM transactions on architecture and code optimization 2025-12, Vol.22 (4), p.1-26, Article 156
Main Authors:	Wu, Zhenlin, Ge, Tianao, Li, Jiajia, Chen, Xinyu, Liu, Hongyuan
Format:	Article
Language:	English
Subjects:	Computer systems organization Computing methodologies Formal languages and automata theory Massively parallel algorithms Massively parallel systems Single instruction, multiple data Software and its engineering Theory of computation
Citations:	Items that this one cites
Online Access:	Get full text
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