ALVEARE: a Domain-Specific Framework for Regular Expressions
Filippo Carloni, Davide Conficconi, Marco D. Santambrogio
Abstract
Regular Expression (RE) matching enables the identification of patterns in datastreams of heterogeneous fields ranging from proteomics to computer security. These scenarios require massive data analysis that, combined with the high data dependency of the REs, leads to long computational times and high energy consumption. Currently, RE engines rely on either (1) flexibility in run-time RE changes and broad operators support impairing performance or (2) fixed high-performing accelerators implementing few simple RE operators. To overcome these limitations, we propose ALVEARE: a hardware-software approach combining a Domain-Specific Language (DSL) with an embedded Domain-Specific Architecture. We exploit REs as a DSL by translating them into flexible executables through our RISC-based Instruction Set Architecture that expresses from simple to advanced primitives. Then, we design a speculation-based microarchitecture to execute real benchmarks efficiently. ALVEARE provides RE-domain flexibility and broad operators' support and achieves up to 34× speedup and 57× energy efficiency improvements against the state-of-the-art RE2 and Bluefield DPU 2 with its RE accelerator.
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