With slowing technology scaling, specialized accelerators are increasingly attractive
solutions to continue expected generational scaling of performance. However, in order to …

Taking advantage of recently released hybrid multicore architectures, such as the Intel's
Xeon+ FPGA machine, where the FPGA has coherent access to the main memory through …

Innovations in genome sequencing techniques are enabling remarkably fast and low cost
production of raw genome data. As Moore's law tapers off, bottlenecks in genome …

Finite State Automata are widely used to accelerate pattern matching in many emerging
application domains like DNA sequencing and XML parsing. Conventional CPUs and …

We present Fleet, a framework that offers a massively parallel streaming model for FPGAs
and is effective in a number of domains well-suited for FPGA acceleration, including parsing …

High-performance automata-processing engines are traditionally evaluated using a limited
set of regular expression-rulesets. While regular expression rulesets are valid real-world …

Rapidly processing text data is critical for many technical and business applications.
Traditional software-based tools for processing large text corpora use memory bandwidth …

Big data analytic applications give rise to large-scale extract-transform-load (ETL) as a
fundamental step to transform new data into a native representation. ETL workloads pose …

High-throughput and concurrent processing of thousands of patterns on each byte of an
input stream is critical for many applications with real-time processing needs, such as …

Many established and emerging applications perform at their core some form of pattern
matching, a computation that maps naturally onto finite automata abstractions. As a …