Abstract
M.Ing. (Electrical And Electronic Engineering)
Bioinformatics is one of the most rapidly advancing sciences today. It is a scienti c
domain that attempts to apply modern computing and information technologies to the
eld of biology, the study of life itself and involves documenting and analysing genetics,
proteins, viruses, bacteria and cancer as well as hereditary traits and diseases, as well as researching cures and treatments for whole ranges of health threats.
The growth of bioinformatics and developments, both theoretical and experimental
in biology, can largely be linked to the IT explosion which gives the eld more powerful
processing options with much cheaper solutions, limited only by the steady yet signi cant
improvements as promised by Moore's Law [3].
This IT explosion has also caused signi cant advances due to the high consumer demand
region of computer graphics hardware, or GPUs (Graphics Processing Units). The
consumer demand has actually managed to advance GPUs far faster than classical CPUs
(Central Processing Units), outpacing CPU performance improvements by a large margin.
As of early 2010, the fastest available PC processor(Intel Core i7 980 XE) has a theoretical
performance of 107.55 GFLOPS [4], while GPUs with TFLOPS (1000 GFLOPS) of
performance have been commercially available since 2008 (ATI HD4800).
While typically used only for graphical rendering, modern innovations have greatly
increased GPU
exibility and has given rise to the eld of GPGPU (General Purpose
GPU) which allows graphics processors to be applied to non-graphics applications.
By utilizing GPU processing power to solve bioinformatics problems, the eld can theoretically
be boosted once again, increasing the amount of computational power available
to scientists by an order of magnitude or more...