High Performance Systolic Array Core Architecture Design for DNA Sequencer
MATEC Web of Conferences
High Performance Systolic Array Core Architecture Design for DNA Sequencer
Dayana Saiful Nurdin 1
Mohd. Nazrin Md. Isa 1
Rizalafande Che Ismail 1
Muhammad Imran Ahmad 0
0 School of Computer and Communication Engineering , Universiti Malaysia Perlis, Pauh Putra Campus, 02600, Arau, Perlis , Malaysia
1 The Integrated Circuits and Systems Design Group (ICASe),School of Microelectronic Engineering , Universiti Malaysia Perlis, Pauh Putra Campus, 02600, Arau, Perlis , Malaysia
This paper presents a high performance systolic array (SA) core architecture design for Deoxyribonucleic Acid (DNA) sequencer. The core implements the affine gap penalty score SmithWaterman (SW) algorithm. This time-consuming local alignment algorithm guarantees optimal alignment between DNA sequences, but it requires quadratic computation time when performed on standard desktop computers. The use of linear SA decreases the time complexity from quadratic to linear. In addition, with the exponential growth of DNA databases, the SA architecture is used to overcome the timing issue. In this work, the SW algorithm has been captured using Verilog Hardware Description Language (HDL) and simulated using Xilinx ISIM simulator. The proposed design has been implemented in Xilinx Virtex -6 Field Programmable Gate Array (FPGA) and improved in the core area by 90% reduction.
1 Introduction
DNA is made up of thymine (T), guanine (G), cytosine
(C) and adenine (A) nucleotides (NTs)[
1
]. Biological
processes such as mutation produce unknown DNA
sequences as it alters the natural DNA sequences [2].
Therefore, sequence alignment is important as it
facilitates the mutated DNA sequences detection by
finding the similarities NT region.
Aligning DNA sequence is an operation that
computationally intensive. The task time execution
cannot be achieved realistically by desktop computer
systems as sequence databases growing exponentially as
shown in Fig. 1. Hence, a faster computation platform is
needed to overcome the aforementioned problem.
Currently, reconfigurable hardware FPGAs has been
suggested to enhance the DNA sequence alignment
performance [3]. Certainly, FPGAs are attractive
platforms to speed up DNA sequence alignment
computation compared to General Purpose Processor
(GPP).
SA architecture has been introduced by researchers to
further improve the DNA sequence alignment process.
SA is a pipeline network arrangement where the process
task is divided among several processors. It is a build-up
of row data processing units called cell or Processing
Element (PE). One of the advantages of using SA
architecture is that the data is streamed across the array
due to the presence of local connection between the cells
[
4
]. The sequence alignment algorithms can take
advantage of SA to realize the parallelism on FPGAs.
Fig. 1. Database growth from 1989 to 2015 [
5
].
SW algorithm, a type of Dynamic Programming (DP)
algorithm is used in aligning DNA sequence where the
common regions between two or more subsequence of
DNA sequences represent the optimal sequence
alignment [
6-7
]. DP-based algorithms usually exhaustive
due to the accurate analysis. Unlike heuristic sequence
alignment such as FASTA, give sub-optimal alignments
that help to reduce the computational burden in DP
algorithm analysis with uncertain accuracy of the result
[8]. Thus, the sequence alignment algorithm can be
implemented in SA to speed up its computation time and
uses FPGA to improve the DNA sequencer computation
process.
The implementation of FPGA related to DNA
sequence alignment architectures are extensively
reported in [9], [
10
], [
11
], [
12
], [
13
] and [
14
]. All of
these architectures are designed based on SA with
realization of the SW algorithm with linear gap penalty.
The architectures are differentiated based on penalty gap
used and also additional features that are included in
their designs such additional algorithm for trace back
(TB) step. For further information of the related works,
please refer to [
13
].
The remainder of this paper will present the general
information of SW algorithm with affine gap, SA and
FPGA. Next, comparative timing performance
evaluation of the proposed design against other FPGA
platforms. Finally, conclusion of this work.
2 Sequence Alignment Algorithms
Pairwise Sequence Alignment (PSA) is one of the
alignment analyses to align DNA sequence. It
investigates the relationship between a newly discover
query sequence and subject sequences that are taken
from databases. T. F. Smith and M. S. Waterman have
introduce an algorithm in 1981 known as SW algorithm
to find the best local alignment between the
aforementioned sequences [
15
]. There are two ways in
penalizing insertions and deletions gaps; linear and
affine.
A more complex SW algorithm was introduced by
Gotoh which is suitable for the affine gaps due to
mutation in DNA sequence [
16
] as shown in (1).
Implementation of this algorithm in (...truncated)