A Scored Non-Deterministic Finite Automata Processor for Sequence Alignment
Ryan Karbowniczak Rasha Karakchi

TL;DR
This paper introduces NAPOLY+, an FPGA-based automata processor extension that scores sequence matches to identify optimal alignments, addressing memory and scalability challenges in pattern matching applications like DNA sequencing.
Contribution
It extends the NAPOLY automata processor with scoring capabilities, enabling optimal path identification in sequence alignment tasks on FPGA hardware.
Findings
High device utilization on FPGA
Performance varies with array size and fan-out
Preliminary results show potential for practical sequence alignment
Abstract
The rapid growth of symbolic data in areas like internet, biological, and financial data has increased the demand for efficient pattern matching and regular expression processing. Non-deterministic Finite Automata (NFA) are used for these tasks, but general-purpose platforms often face memory bottlenecks due to the concurrent nature of NFAs. To address this, Domain-Specific Architectures (DSAs) like FPGA and ASIC-based automata processors have been developed for improved efficiency. However, many modern applications require identifying the optimal match path, such as in DNA sequence alignment, which demands scoring methods to evaluate the best match. This work enhances the FPGA-based NAPOLY automata processor by integrating scoring capabilities, creating an extended version called NAPOLY+ that assigns weights to transitions, enabling the identification of the highest scoring path.…
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Taxonomy
TopicsAlgorithms and Data Compression · Software Testing and Debugging Techniques · semigroups and automata theory
