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Search-based regular expression inference on a GPU

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conference contribution
posted on 2023-07-07, 09:47 authored by Mojtaba Valizadeh, Martin BergerMartin Berger
Regular expression inference (REI) is a supervised machine learning and program synthesis problem that takes a cost metric for regular expressions, and positive and negative examples of strings as input. It outputs a regular expression that is precise (i.e., accepts all positive and rejects all negative examples), and minimal w.r.t.To the cost metric. We present a novel algorithm for REI over arbitrary alphabets that is enumerative and trades off time for space. Our main algorithmic idea is to implement the search space of regular expressions succinctly as a contiguous matrix of bitvectors. Collectively, the bitvectors represent, as characteristic sequences, all sub-languages of the infix-closure of the union of positive and negative examples. Mathematically, this is a semiring of (a variant of) formal power series. Infix-closure enables bottom-up compositional construction of larger from smaller regular expressions using the operations of our semiring. This minimises data movement and data-dependent branching, hence maximises data-parallelism. In addition, the infix-closure remains unchanged during the search, hence search can be staged: first pre-compute various expensive operations, and then run the compute intensive search process. We provide two C++ implementations, one for general purpose CPUs and one for Nvidia GPUs (using CUDA). We benchmark both on Google Colab Pro: The GPU implementation is on average over 1000x faster than the CPU implementation on the hardest benchmarks.

History

Publication status

  • Published

File Version

  • Published version

Journal

Proceedings of the ACM on Programming Languages

ISSN

2475-1421

Publisher

Association for Computing Machinery (ACM)

Volume

7

Page range

1317-1339

Event name

44th ACM SIGPLAN Conference on Programming Language Design and Implementation

Event location

Orlando, Florida, United States

Event type

Conference

Event date

Sat 17 - Wed 21 June 2023

Department affiliated with

  • Informatics Publications

Peer reviewed?

  • Yes

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