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STAP: An Architecture and Design Tool for Automata Processing on Memristor TCAMs by João Paulo Cardoso de Lima; Marcelo Brandalero; Michael Hübner; Luigi Carro is a Engineering article available to read on EtoBox.

What is STAP: An Architecture and Design Tool for Automata Processing on Memristor TCAMs about?

Accelerating finite-state automata benefits several emerging application domains that are built on pattern matching. In-memory architectures, such as the Automata Processor (AP), are efficient to speed them up, at least for outperforming traditional von-Neumann architectures. In spite of the AP’s massive parallelism, current APs suffer from poor memory density, inefficient routing architectures, and limited capabilities. Although these limitations can be lessened by emerging memory technologies, its architecture is still the major source of huge communication demands and lack of scalability. To address these issues, we present STAP , a Scalable TCAM-based architecture for Automata Processing . STAP adopts a reconfigurable array of processing elements, which are based on memristive Ternary CAMs (TCAMs), to efficiently implement Non-deterministic finite automata (NFAs) through proper encoding and mapping methods. The CAD tool for STAP integrates the design flow of automata applications, a specific mapping algorithm, and place and route tools for connecting processing elements by RRAM-based programmable interconnects. Results showed 1.47× higher throughput when processing 16-bit input

Who reads STAP: An Architecture and Design Tool for Automata Processing on Memristor TCAMs?

Author

João Paulo Cardoso de Lima; Marcelo Brandalero; Michael Hübner; Luigi Carro

Publisher

ACM

Published

2021

Language

EN

Field

Engineering (Physical Sciences)