  Advances in life sciences over the last few decades have lead to the
generation of a huge amount of biological data. Computing research has become a
vital part in driving biological discovery where analysis and categorization of
biological data are involved. String matching algorithms can be applied for
protein/gene sequence matching and with the phenomenal increase in the size of
string databases to be analyzed, software implementations of these algorithms
seems to have hit a hard limit and hardware acceleration is increasingly being
sought. Several hardware platforms such as Field Programmable Gate Arrays
(FPGA), Graphics Processing Units (GPU) and Chip Multi Processors (CMP) are
being explored as hardware platforms. In this paper, we give a comprehensive
overview of the literature on hardware acceleration of string matching
algorithms, we take an FPGA hardware exploration and expedite the design time
by a design automation technique. Further, our design automation is also
optimized for better hardware utilization through optimizing the number of
peptides that can be represented in an FPGA tile. The results indicate
significant improvements in design time and hardware utilization which are
reported in this paper.
