  Huge amount of data in the form of strings are being handled in bio-computing
applications and searching algorithms are quite frequently used in them. Many
methods utilizing on both software and hardware are being proposed to
accelerate processing of such data. The typical hardware-based acceleration
techniques either require special hardware such as general purpose graphics
processing units (GPGPUs) or need building a new hardware such as an FPGA based
design. On the other hard, software-based acceleration techniques are easier
since they only require some changes in the software code or the software
architecture. Typical software-based techniques make use of computers connected
over a network, also known as a network grid to accelerate the processing. In
this paper, we test the hypothesis that multi-core architectures should provide
better performance in this kind of computation, but still it would depend on
the algorithm selected as well as the programming model being utilized. We
present the acceleration of a string-searching algorithm on a multi-core CPU
via a POSIX thread based implementation. Our implementation on an 8-core
processor (that supports 16-threads) resulted in 9x throughput improvement
compared to a single thread implementation.
