Laiq Hasan

An optimized and low-cost FPGA-based DNA sequence alignment — A step towards personal genomics

DNA sequence alignment is a cardinal process in computational biology but also is much expensive computationally when performing through traditional computational platforms like CPU. Of many off the shelf platforms explored for speeding up the computation process, FPGA stands as the best candidate due to its performance per dollar spent and performance per watt. These two advantages make FPGA as the most appropriate choice for realizing the aim of personal genomics. The previous implementation of DNA sequence alignment did not take into consideration the price of the device on which optimization was performed. This paper presents optimization over previous FPGA implementation that increases the overall speed-up achieved as well as the price incurred by the platform that was optimized. The optimizations are (1) The array of processing elements is made to run on change in input value and not on clock, so eliminating the need for tight clock synchronization, (2) the implementation is unrestrained by the size of the sequences to be aligned, (3) the waiting time required for the sequences to load to FPGA is reduced to the minimum possible and (4) an efficient method is devised to store the output matrix that make possible to save the diagonal elements to be used in next pass, in parallel with the computation of output matrix. Implemented on Spartan3 FPGA, this implementation achieved 20 times performance improvement in terms of CUPS over GPP implementation.

A novel structure of the Smith-Waterman Algorithm for efficient sequence alignment

The emergence of bioinformatics has led to many new discoveries in living organisms. These discoveries would not have been possible without the developments made in the sequence alignment techniques. Many sequence alignment algorithms were developed to make the alignment process fast and accurate. However, the more precise algorithms take longer than their less precise counterparts. Researchers came with innovative approaches to combat the time consuming constraint. Their aim was to speed up the computational process by using more efficient implementations of the algorithms using state-of-the-art hardware platforms. Smith Waterman (SW) algorithm, being the most accurate in the alignment process, has been implemented on various high performance computing platforms for the same purpose. However, the intrinsic structure of the algorithm has got little attention. In this paper, we present a novel structure of the SW algorithm that takes less number of cycles at the cost of utilizing a minimal amount of extra hardware resources as compared to its existing form. The newly proposed architecture achieves up to 25% performance gain.

Optimized and Portable FPGA-Based Systolic Cell Architecture for Smith–Waterman-Based DNA Sequence Alignment

The alignment of DNA sequences is one of the important processes in the field of bioinformatics. The Smith–Waterman algorithm (SWA) performs optimally for aligning sequences but is computationally expensive. Field programmable gate array (FPGA) performs the best on parameters such as cost, speed-up, and ease of re-configurability to implement SWA. The performance of FPGA-based SWA is dependent on efficient cell-basic implementation-unit design. In this paper, we present an optimized systolic cell design while avoiding oversimplification, very large-scale integration (VLSI)-level design, and direct mapping of iterative equations such as previous cell designs. The proposed design makes efficient use of hardware resources and provides portability as the proposed design is not based on gate-level details. Our cell design implementing a linear gap penalty resulted in a performance improvement of 32× over a GPP platform and surpassed the hardware utilization of another implementation by a factor of 4.23.

Performance comparison & analysis of DivSufSort-based & SAIS-based FM-Index

FM-Index and Suffix Array are closely related to each other and are both extremely popular indexes for genomic sequences. They are used in several popular read alignment tools, including Bowtie, Bowtie 2, BWA, and GEM. In literature, there exist several Suffix Array Construction Algorithms (SACA). We have considered two popular SACA techniques: DivSufSort and SAIS. Both techniques construct suffix array in linear time. We have constructed FM-Index using both of these SACA algorithms. In this paper, we comprehensively describe our FM-Index construction approach and compare performance of these two indexes in terms of time for different string types in the Dataset. Our result shows that DivSufSort-based FM-Index performs 3.67% time efficient than SAIS-based FM-Index on 10 out of 11 strings in the Dataset.

Design and implementation of an intelligent energy saving system

The energy crisis is one of the major problems faced by Pakistan at the moment. It has adversely affected the industrial growth and restrained business nourishment which in turn has affected the overall economy of Pakistan. Proper energy saving measures need to be implemented in order to reduce the energy shortfall. The proper and efficient use of energy also helps in reducing different kinds of pollution. In this paper, we have presented an intelligent power saving system, capable of saving electricity, minimizing electricity risks in workplaces, all in an automated manner. The developed system is economical and easy to install. It can be used to reduce the energy consumption of every kind of electric device in residential as well commercial buildings.

PERFORMANCE ANALYSIS OF ROUTING PROTOCOLS FOR WIRELESS SENSOR NETWORKS

A Wireless Sensor Network (WSN) is a self-organizing, energy constrained ad hoc network consisting of specialized nodes called motes sensing some phenomenon in an area. WSN may use generic or specialized routing protocols with random node distribution and unpredictable sensing and transceiving patterns with the constraint of limited irreplaceable energy. This paper attempts to compare on-demand reactive routing protocol (AODV) against proactive routing protocol (DSDV). The performance is studied in terms of key performance metrics which include packet delivery fraction, normalized routing load, delay, maximum and average energy. The comparison and analysis is made using Network Simulator 2 (NS-2) with additional Mannasim capability using specialized energy models by varying area of node distribution and node density. The analysis unravels the specific applications for which each protocol is suited.