1 research outputs found
Giving Text Analytics a Boost
The amount of textual data has reached a new scale and continues to grow at
an unprecedented rate. IBM's SystemT software is a powerful text analytics
system, which offers a query-based interface to reveal the valuable information
that lies within these mounds of data. However, traditional server
architectures are not capable of analyzing the so-called "Big Data" in an
efficient way, despite the high memory bandwidth that is available. We show
that by using a streaming hardware accelerator implemented in reconfigurable
logic, the throughput rates of the SystemT's information extraction queries can
be improved by an order of magnitude. We present how such a system can be
deployed by extending SystemT's existing compilation flow and by using a
multi-threaded communication interface that can efficiently use the bandwidth
of the accelerator