Work

Trie Compression for GPU Accelerated Multi-Pattern Matching

Year: 2017

Type: conference-paper

Abstract: Graphics Processing Units allow for running massively parallel applications offloading the CPU from computationally intensive resources, however GPUs have a limited amount of memory. In this paper a trie compression algorithm for massively parallel pattern matching is presented demonstrating 85% less space requirements than the original highly efficient parallel failure-less aho-corasick, whilst demonstrating over 22 Gbps throughput. The algorithm presented takes advantage of compressed row storage matrices as well as shared and texture memory on the GPU.

Source: Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)

DOI: 10.48550/arxiv.1702.03657

Authors: Bellekens, Xavier, Seeam, Amar, Tachtatzis, Christos, Atkinson, Robert

Institutions: Abertay University, Middlesex University Mauritius

Language: English

Topic: Algorithms and Data Compression

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2588930463

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