Compiling Text Analytics Queries to FPGAs

Extracting information from unstructured text data is a compute-intensive task. The performance of general-purpose processors cannot keep up with the rapid growth of textual data. Therefore we discuss the use of FPGAs to perform large-scale text analytics. We present a framework consisting of a compiler and an operator library capable of generating a Verilog processing pipeline from a text analytics query specified in the annotation query language AQL. The operator library comprises a set of configurable modules capable of performing relational and extraction tasks which can be assembled by the compiler to represent a full annotation operator graph. Leveraging the nature of text processing, we show that most tasks can be performed in an efficient streaming fashion.

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By: Raphael Polig, Kubilay Atasu, Heiner Giefers and Laura Chiticariu

Published in: RZ3864 in 2014

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