High Level Synthesis of SPARQL Queries
Authors: Marco Minutoli (Pacific Northwest National Laboratory), Vito Giovanni Castellana (Pacific Northwest National Laboratory), Antonino Tumeo (Pacific Northwest National Laboratory)
Abstract: RDF databases naturally map to labeled, directed graphs.
SPARQL is a query language for RDF databases that expresses queries as graph pattern matching operations. GEMS
is a RDF database that, differently from other solutions, employs graph methods at all levels of its stack. Graph methods are inherently task parallel, but they exhibit an irregular
behavior. In this poster we discuss an approach to accelerate
GEMS with reconfigurable devices. The proposed approach
automatically generates parallel hardware implementations
of SPARQL queries using a customized High Level Synthesis (HLS) flow. The flow has been enhanced with solutions
to address limitations of graph methods with conventional
HLS methods, enhancing TLP extraction and management
of concurrent memory operations. We have validated our
approach by synthesizing and simulating seven queries from
LUBM. We show that that the proposed approach provides
an average speed up or 2.1 with respect to the serial version
of the hardware accelerators.
Poster: pdf
Two-page extended abstract: pdf
Poster Index