scholarly journals High Performance Biological Pairwise Sequence Alignment: FPGA versus GPU versus Cell BE versus GPP

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Khaled Benkrid ◽  
Ali Akoglu ◽  
Cheng Ling ◽  
Yang Song ◽  
Ying Liu ◽  
...  
Keyword(s):  
Sequence Alignment ◽  
Reconfigurable Computing ◽  
High Performance ◽  
General Purpose ◽  
Alignment Algorithm ◽  
Pairwise Sequence Alignment ◽  
Performance Per Watt ◽  
Order Of Magnitude ◽  
Speed Up ◽  
General Purpose Processors

This paper explores the pros and cons of reconfigurable computing in the form of FPGAs for high performance efficient computing. In particular, the paper presents the results of a comparative study between three different acceleration technologies, namely, Field Programmable Gate Arrays (FPGAs), Graphics Processor Units (GPUs), and IBM’s Cell Broadband Engine (Cell BE), in the design and implementation of the widely-used Smith-Waterman pairwise sequence alignment algorithm, with general purpose processors as a base reference implementation. Comparison criteria include speed, energy consumption, and purchase and development costs. The study shows that FPGAs largely outperform all other implementation platforms on performance per watt criterion and perform better than all other platforms on performance per dollar criterion, although by a much smaller margin. Cell BE and GPU come second and third, respectively, on both performance per watt and performance per dollar criteria. In general, in order to outperform other technologies on performance per dollar criterion (using currently available hardware and development tools), FPGAs need to achieve at least two orders of magnitude speed-up compared to general-purpose processors and one order of magnitude speed-up compared to domain-specific technologies such as GPUs.

High-Performance Reconfigurable Computing

2019 ◽  
pp. 731-744
Author(s):  
Mário Pereira Vestias
Keyword(s):  
Power Consumption ◽  
Integrated Circuit ◽  
Reconfigurable Computing ◽  
High Performance ◽  
General Purpose ◽  
Reconfigurable Hardware ◽  
Coarse Grained ◽  
Lower Power ◽  
Fine Grained ◽  
Application Specific

High-performance reconfigurable computing systems integrate reconfigurable technology in the computing architecture to improve performance. Besides performance, reconfigurable hardware devices also achieve lower power consumption compared to general-purpose processors. Better performance and lower power consumption could be achieved using application-specific integrated circuit (ASIC) technology. However, ASICs are not reconfigurable, turning them application specific. Reconfigurable logic becomes a major advantage when hardware flexibility permits to speed up whatever the application with the same hardware module. The first and most common devices utilized for reconfigurable computing are fine-grained FPGAs with a large hardware flexibility. To reduce the performance and area overhead associated with the reconfigurability, coarse-grained reconfigurable solutions has been proposed as a way to achieve better performance and lower power consumption. In this chapter, the authors provide a description of reconfigurable hardware for high-performance computing.

High-Performance Reconfigurable Computing

2018 ◽  
pp. 4018-4029
Author(s):  
Mário Pereira Vestias
Keyword(s):  
Power Consumption ◽  
Integrated Circuit ◽  
Reconfigurable Computing ◽  
High Performance ◽  
General Purpose ◽  
Reconfigurable Hardware ◽  
Coarse Grained ◽  
Lower Power ◽  
Fine Grained ◽  
Application Specific

High-Performance Reconfigurable Computing systems integrate reconfigurable technology in the computing architecture to improve performance. Besides performance, reconfigurable hardware devices also achieve lower power consumption compared to General-Purpose Processors. Better performance and lower power consumption could be achieved using Application Specific Integrated Circuit (ASIC) technology. However, ASICs are not reconfigurable, turning them application specific. Reconfigurable logic becomes a major advantage when hardware flexibility permits to speed up whatever the application with the same hardware module. The first and most common devices utilized for reconfigurable computing are fine-grained FPGAs with a large hardware flexibility. To reduce the performance and area overhead associated with the reconfigurability, coarse-grained reconfigurable solutions has been proposed as a way to achieve better performance and lower power consumption. In this chapter we will provide a description of reconfigurable hardware for high performance computing.

Multiple Sequence Alignment Optimization Using Meta-Heuristic Techniques

2020 ◽  
pp. 565-579 ◽  
Author(s):  
Mohamed Issa ◽  
Aboul Ella Hassanien
Keyword(s):  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Phylogenetic Trees ◽  
Pairwise Alignment ◽  
Accurate Method ◽  
Alignment Algorithm ◽  
Bacterial Foraging Optimization ◽  
Multiple Sequence ◽  
Speed Up ◽  
Dna Fragment Assembly

Sequence alignment is a vital process in many biological applications such as Phylogenetic trees construction, DNA fragment assembly and structure/function prediction. Two kinds of alignment are pairwise alignment which align two sequences and Multiple Sequence alignment (MSA) that align sequences more than two. The accurate method of alignment is based on Dynamic Programming (DP) approach which suffering from increasing time exponentially with increasing the length and the number of the aligned sequences. Stochastic or meta-heuristics techniques speed up alignment algorithm but with near optimal alignment accuracy not as that of DP. Hence, This chapter aims to review the recent development of MSA using meta-heuristics algorithms. In addition, two recent techniques are focused in more deep: the first is Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO). The second is Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm (MO-BFO).

MX2 Processor Module: Twice the Processors in Half the Volume

2005 ◽  
Author(s):  
Christian Belady ◽  
Gary Williams ◽  
Shaun Harris
Keyword(s):  
High Performance ◽  
Power Converter ◽  
Case Scenario ◽  
Worst Case ◽  
Physical Volume ◽  
Performance Per Watt ◽  
Innovative Solution ◽  
Order Of Magnitude ◽  
Processor Module ◽  
Better Than

Computer manufacturer’s are constantly trying to tweek more performance out of their existing products by using the highest performing processors. Typically, manufacturers upgrade the platforms by simply replacing the old processor with the latest speed processor. Like other manufacturers, HP generally follows this practice with the exception ot HP’s innovative mx2 module. This unique module used two Itanium-2 “Madison” processors packaged in the same physical volume as a single Itanium-2 processor. In addition, the module plugs into a standard Itanium-2 motherboard socket and requires no additional power capacity. As a result, the development team was able get 50% more performance [1] from a socket without increasing power by actively managing the power to the two processors. Thus, the performance per watt was substantially improved. This paper will provide an overview of some of the key packaging and power innovations that made the processor module a reality such as: 1) mezzanine power for space savings. The standard Itanium 2 processor has a power converter adjacent to the processor. HP engineers chose to put power on top of the processor which provided more room but made cooling the processors a challenge. 2) high performance mechnical gap filler. One of the biggest issues in the module was to develop a thermal gap filler that absorbed 0.060” of tolerance between the two processors. The thermal resistance of this technology was an order of magnitude better than anything commercially available in the industry. 3) Power Aware Architecture. This newly developed power mangement technology actively controls power to the processors. When system (thermal and power) extremes were exceeded by worst case abnormal code, the performance was throttled down until the worst case scenario had past. The combination of these advancements has delivered an innovative solution for a highly challenging design problem. This module is now shipping as the mx2 processor module in HP’s Integrity Servers and has been viewed as an engineering marvel by HP executives.

scholarly journals Efficient Multiple Sequences Alignment Algorithm Generation via Components Assembly Under PAR Framework

2021 ◽  
Vol 11 ◽  
Author(s):  
Haipeng Shi ◽  
Haihe Shi ◽  
Shenghua Xu
Keyword(s):  
Sequence Alignment ◽  
Multiple Sequence Alignment ◽  
Sequence Similarity ◽  
Alignment Algorithm ◽  
Pairwise Sequence Alignment ◽  
Multiple Sequence ◽  
Sequence Alignment Algorithm ◽  
Alignment Algorithms ◽  
Sequence Similarity Analysis ◽  
High Level

As a key algorithm in bioinformatics, sequence alignment algorithm is widely used in sequence similarity analysis and genome sequence database search. Existing research focuses mainly on the specific steps of the algorithm or is for specific problems, lack of high-level abstract domain algorithm framework. Multiple sequence alignment algorithms are more complex, redundant, and difficult to understand, and it is not easy for users to select the appropriate algorithm; some computing errors may occur. Based on our constructed pairwise sequence alignment algorithm component library and the convenient software platform PAR, a few expansion domain components are developed for multiple sequence alignment application domain, and specific multiple sequence alignment algorithm can be designed, and its corresponding program, i.e., C++/Java/Python program, can be generated efficiently and thus enables the improvement of the development efficiency of complex algorithms, as well as accuracy of sequence alignment calculation. A star alignment algorithm is designed and generated to demonstrate the development process.

An Efficient Scheduling Technique for Biological Sequence Alignment

2015 ◽  
Vol 754-755 ◽  
pp. 1087-1092
Author(s):  
Mohd Nazrin Md Isa ◽  
Sohiful Anuar Zainol Murad ◽  
Mohamad Imran Ahmad ◽  
Muhammad M. Ramli ◽  
Rizalafande Che Ismail
Keyword(s):  
Sequence Alignment ◽  
Substitution Matrix ◽  
Processing Element ◽  
Biological Sequence ◽  
Matrix Computation ◽  
Logic Block ◽  
Order Of Magnitude ◽  
Speed Up ◽  
A New Technique ◽  
Protein Sequencer

Computing alignment matrix score to search for regions of homology between biological sequences is time consuming task. This is due to the recursive nature of the dynamic programming-based algorithms such as the Smith-Waterman and the Needleman-Wunsch algorithmns. Typical FPGA-based protein sequencer comprises of two main logic blocks. One for computing alignment scores i.e. the processing element (PE), while another logic block for configuring the PE with coefficients. During alignment matrix computation, the logic block for configuring the PE are left unused until the time consuming alignment matrix computation finished. Therefore, a new technique, known as overlap computation and configuration (OCC) is proposed to minimize the time overhead for performing biological sequence alignment. The OCC technique simultaneously updating substitution matrix in a processing element (PE) systolic array, while computing alignment matrix scores. Results showed that, the sequencer achieves more than two order of magnitude speed-up higher compared to the state of the art, at negligible area overhead, if any.

scholarly journals Graphics card processing: accelerating profile-profile alignment

2012 ◽  
Vol 2 (4) ◽  
Author(s):  
Muhammad Hanif ◽  
Karl-Heinz Zimmermann
Keyword(s):  
Molecular Biology ◽  
General Purpose ◽  
Matrix Product ◽  
Fundamental Operation ◽  
Computational Power ◽  
Multiple Sequence ◽  
Average Speed ◽  
Order Of Magnitude ◽  
Speed Up ◽  
Profile Alignment

AbstractAlignment is the fundamental operation in molecular biology for comparing biomolecular sequences. The most widely used method for aligning groups of alignments is based on the alignment of the profiles corresponding to the groups. We show that profile-profile alignment can be significantly speeded up by general purpose computing on a modern commodity graphics card. Wavefront and matrix-matrix product approaches for implementing profile-profile alignment onto graphics processor are analyzed. The average speed-up obtained is one order of magnitude even when overheads are considered. Thus the computational power of graphics cards can be exploited to develop improved solutions for multiple sequence alignment.

scholarly journals CRISPR-SE: a brute force search engine for CRISPR design

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Bin Li ◽  
Poshen B Chen ◽  
Yarui Diao
Keyword(s):  
Search Engine ◽  
Sequence Alignment ◽  
Search Engines ◽  
High Performance ◽  
Design Tools ◽  
Brute Force ◽  
Guide Rnas ◽  
Speed Up ◽  
Brute Force Approach

Abstract CRISPR is a revolutionary genome-editing tool that has been broadly used and integrated within novel biotechnologies. A major component of existing CRISPR design tools is the search engines that find the off-targets up to a predefined number of mismatches. Many CRISPR design tools adapted sequence alignment tools as the search engines to speed up the process. These commonly used alignment tools include BLAST, BLAT, Bowtie, Bowtie2 and BWA. Alignment tools use heuristic algorithm to align large amount of sequences with high performance. However, due to the seed-and-extend algorithms implemented in the sequence alignment tools, these methods are likely to provide incomplete off-targets information for ultra-short sequences, such as 20-bp guide RNAs (gRNA). An incomplete list of off-targets sites may lead to erroneous CRISPR design. To address this problem, we derived four sets of gRNAs to evaluate the accuracy of existing search engines; further, we introduce a search engine, namely CRISPR-SE. CRISPR-SE is an accurate and fast search engine using a brute force approach. In CRISPR-SE, all gRNAs are virtually compared with query gRNA, therefore, the accuracies are guaranteed. We performed the accuracy benchmark with multiple search engines. The results show that as expected, alignment tools reported an incomplete and varied list of off-target sites. CRISPR-SE performs well in both accuracy and speed. CRISPR-SE will improve the quality of CRISPR design as an accurate high-performance search engine.

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