High Performance Systolic Array Core Architecture Design for DNA Sequencer

MATEC Web of Conferences, Jan 2018

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 Smith-Waterman (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.

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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)


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Dayana Saiful Nurdin, Mohd. Nazrin Md. Isa, Rizalafande Che Ismail, Muhammad Imran Ahmad. High Performance Systolic Array Core Architecture Design for DNA Sequencer, MATEC Web of Conferences, 2018, 150, DOI: 10.1051/matecconf/201815006009