In-Memory Automata Processing Accelerator

Apr 27, 2016

Accelerating finite automata processing is critical for advancing real-time analytic in pattern matching, data mining, bioinformatics, intrusion detection, and machine learning. Recent in-memory automata accelerators leveraging SRAMs and DRAMs have shown exciting improvements over conventional digital designs.

Software-Hardware Codesign for Efficient In-Memory Regular Pattern Matching [PLDI2022]

CAMA: Energy and Memory Efficient Automata Processing in Content-Addressable Memories [HPCA2022]

Mixed-Signal Computing

Related

Publications

Qiufeng Rui, Noah Elzner, Qiang Zhou, Ziyuan Wen, Yan He, Kaiyuan Yang. Lightweight Machine Learning and Embedded Security Engine for Physical-Layer Identification of Wireless IoT Nodes. ICC 2024-IEEE International Conference on Communications, 2024.

Project DOI

Ziyuan Wen, Lingkun Kong, Alexis Le Glaunec, Konstantinos Mamouras, Kaiyuan Yang. BVAP: Energy and Memory Efficient Automata Processing for Regular Expressions with Bounded Repetitions. Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024.

Project DOI

Lingkun Kong, Qixuan Yu, Agnishom Chattopadhyay, Alexis Le Glaunec, Yi Huang, Konstantinos Mamouras, Kaiyuan Yang. Software-hardware codesign for efficient in-memory regular pattern matching. ACM SIGPLAN International Conference on Programming Language Design and Implementation (PLDI), 2022.

PDF Project DOI

Yi Huang, Zhiyu Chen, Dai Li, Kaiyuan Yang. CAMA: Energy and Memory Efficient Automata Processing in Content-Addressable Memories. IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2022.

PDF Project DOI