WFA-FPGA: An efficient accelerator of the wavefront algorithm for short and long read genomics alignment

[1]  D. Soudris,et al.  GANDAFL: Dataflow Acceleration for Short Read Alignment on NGS Data , 2022, IEEE Transactions on Computers.

[2]  Jordan M. Eizenga,et al.  Optimal gap-affine alignment in O(s) space , 2022, bioRxiv.

[3]  Emanuele Del Sozzo,et al.  Surfing the Wavefront of Genome Alignment , 2022, 2022 IEEE International Symposium on Circuits and Systems (ISCAS).

[4]  Hsiang-Yun Cheng,et al.  RePAIR: A ReRAM-based Processing-in-Memory Accelerator for Indel Realignment , 2022, 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[5]  Jordan M. Eizenga,et al.  Improving the time and space complexity of the WFA algorithm and generalizing its scoring , 2022, bioRxiv.

[6]  Christoph Hagleitner,et al.  An FPGA Accelerator of the Wavefront Algorithm for Genomics Pairwise Alignment , 2021, 2021 31st International Conference on Field-Programmable Logic and Applications (FPL).

[7]  Yi-Chang Lu,et al.  A Memory-Efficient Accelerator for DNA Sequence Alignment with Two-Piece Affine Gap Tracebacks , 2021, 2021 IEEE International Symposium on Circuits and Systems (ISCAS).

[8]  Yun Sung Cho,et al.  Comparative analysis of 7 short-read sequencing platforms using the Korean Reference Genome: MGI and Illumina sequencing benchmark for whole-genome sequencing , 2021, GigaScience.

[9]  Ringo S. W. Chu,et al.  Acceleration of Short Read Alignment with Runtime Reconfiguration , 2020, 2020 International Conference on Field-Programmable Technology (ICFPT).

[10]  Alfredo Goldman,et al.  A CPU‐FPGA heterogeneous approach for biological sequence comparison using high‐level synthesis , 2020, Concurr. Comput. Pract. Exp..

[11]  David Blaauw,et al.  SeedEx: A Genome Sequencing Accelerator for Optimal Alignments in Subminimal Space , 2020, 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[12]  Rachata Ausavarungnirun,et al.  GenASM: A High-Performance, Low-Power Approximate String Matching Acceleration Framework for Genome Sequence Analysis , 2020, 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[13]  Miquel Moreto,et al.  Fast gap-affine pairwise alignment using the wavefront algorithm , 2020, Bioinformatics.

[14]  L. Yavits,et al.  BioSEAL , 2020, Proceedings of the 13th ACM International Systems and Storage Conference.

[15]  Sachin S. Sapatnekar,et al.  A DNA Read Alignment Accelerator Based on Computational RAM , 2020, IEEE Journal on Exploratory Solid-State Computational Devices and Circuits.

[16]  Dimitrios Soudris,et al.  Dataflow Acceleration of Smith-Waterman with Traceback for High Throughput Next Generation Sequencing , 2019, 2019 29th International Conference on Field Programmable Logic and Applications (FPL).

[17]  Mohsen Imani,et al.  RAPID: A ReRAM Processing in-Memory Architecture for DNA Sequence Alignment , 2019, 2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED).

[18]  Cuong Pham-Quoc,et al.  A high‐performance FPGA‐based BWA‐MEM DNA sequence alignment , 2019, Concurr. Comput. Pract. Exp..

[19]  Jason Cong,et al.  Hardware Acceleration of Long Read Pairwise Overlapping in Genome Sequencing: A Race Between FPGA and GPU , 2019, 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM).

[20]  William J. Dally,et al.  Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup , 2019, 2019 IEEE International Symposium on High Performance Computer Architecture (HPCA).

[21]  W. Dally,et al.  Darwin , 2018, ACM SIGPLAN Notices.

[22]  Armando De Giusti,et al.  SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences , 2018, BMC Systems Biology.

[23]  Hamid R. Zarandi,et al.  AligneR: A Process-in-Memory Architecture for Short Read Alignment in ReRAMs , 2018, IEEE Computer Architecture Letters.

[24]  Nae-Chyun Chen,et al.  Adaptively Banded Smith-Waterman Algorithm for Long Reads and Its Hardware Accelerator , 2018, 2018 IEEE 29th International Conference on Application-specific Systems, Architectures and Processors (ASAP).

[25]  David Blaauw,et al.  GenAx: A Genome Sequencing Accelerator , 2018, 2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture (ISCA).

[26]  Armando Eduardo De Giusti,et al.  OSWALD: OpenCL Smith–Waterman on Altera’s FPGA for Large Protein Databases , 2018 .

[27]  Subho Sankar Banerjee,et al.  ASAP: Accelerated Short-Read Alignment on Programmable Hardware , 2018, IEEE Trans. Computers.

[28]  Jan-Peter Nap,et al.  pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment , 2018, PloS one.

[29]  Ernst Houtgast,et al.  High Performance Streaming Smith-Waterman Implementation with Implicit Synchronization on Intel FPGA using OpenCL , 2017, 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE).

[30]  Heng Li,et al.  Minimap2: pairwise alignment for nucleotide sequences , 2017, Bioinform..

[31]  Kemal Sönmez,et al.  Precision medicine and FPGA technology: Challenges and opportunities , 2017, 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS).

[32]  Charles Lefurgy,et al.  Power/Performance Controlling Techniques in OpenPOWER , 2017, ISC Workshops.

[33]  Zou Dan,et al.  FPGASW: Accelerating Large-Scale Smith–Waterman Sequence Alignment Application with Backtracking on FPGA Linear Systolic Array , 2017, Interdisciplinary Sciences Computational Life Sciences.

[34]  O. P. Gupta,et al.  CLUS_GPU-BLASTP: accelerated protein sequence alignment using GPU-enabled cluster , 2017, The Journal of Supercomputing.

[35]  Mahmoud Al-Ayyoub,et al.  A hybrid CPU-GPU implementation to accelerate multiple pairwise protein sequence alignment , 2017, 2017 8th International Conference on Information and Communication Systems (ICICS).

[36]  William J. Dally,et al.  Darwin: A Hardware-acceleration Framework for Genomic Sequence Alignment , 2017, bioRxiv.

[37]  Ran Ginosar,et al.  A Resistive CAM Processing-in-Storage Architecture for DNA Sequence Alignment , 2017, IEEE Micro.

[38]  D. S. Nurdin,et al.  DNA sequence alignment: A review of hardware accelerators and a new core architecture , 2016, 2016 3rd International Conference on Electronic Design (ICED).

[39]  Liang-Tsung Huang,et al.  Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs , 2015, BioMed research international.

[40]  Ernst Houtgast,et al.  An FPGA-based systolic array to accelerate the BWA-MEM genomic mapping algorithm , 2015, 2015 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS).

[41]  Paolo Ribeca,et al.  Efficient Alignment of Illumina‐Like High‐Throughput Sequencing Reads with the GEnomic Multi‐tool (GEM) Mapper , 2015, Current protocols in bioinformatics.

[42]  Chao Wang,et al.  Accelerating the Next Generation Long Read Mapping with the FPGA-Based System , 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[43]  Jaime Velasco-Medina,et al.  Hardware implementation of the Smith-Waterman algorithm using a systolic architecture , 2014, 2014 IEEE 5th Latin American Symposium on Circuits and Systems.

[44]  Yongchao Liu,et al.  CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions , 2013, BMC Bioinformatics.

[45]  Nuno A. Fonseca,et al.  Tools for mapping high-throughput sequencing data , 2012, Bioinform..

[46]  Roderic Guigó,et al.  The GEM mapper: fast, accurate and versatile alignment by filtration , 2012, Nature Methods.

[47]  Zaid Al-Ars,et al.  An Overview of Hardware-Based Acceleration of Biological Sequence Alignment , 2011 .

[48]  Jacek Blazewicz,et al.  Protein alignment algorithms with an efficient backtracking routine on multiple GPUs , 2011, BMC Bioinformatics.

[49]  M. DePristo,et al.  A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.

[50]  Wayne Luk,et al.  FPGA-Based Smith-Waterman Algorithm: Analysis and Novel Design , 2011, ARC.

[51]  William Lynch,et al.  Smith-Waterman implementation on a FSB-FPGA module using the Intel Accelerator Abstraction Layer , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.

[52]  Ying Liu,et al.  A Highly Parameterized and Efficient FPGA-Based Skeleton for Pairwise Biological Sequence Alignment , 2009, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[53]  Xianyang Jiang,et al.  A Reconfigurable Accelerator for Smith–Waterman Algorithm , 2007, IEEE Transactions on Circuits and Systems II: Express Briefs.

[54]  Guang R. Gao,et al.  Implementation of the Smith-Waterman algorithm on a reconfigurable supercomputing platform , 2007, HPRCTA.

[55]  Philip Heng Wai Leong,et al.  A Smith-Waterman Systolic Cell , 2003, FPL.

[56]  Peter M. Athanas,et al.  A run-time reconfigurable system for gene-sequence searching , 2003, 16th International Conference on VLSI Design, 2003. Proceedings..

[57]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[58]  O. Gotoh.  An improved algorithm for matching biological sequences. , 1982, Journal of molecular biology.

[59]  M S Waterman,et al.  Identification of common molecular subsequences. , 1981, Journal of molecular biology.

[60]  Miquel Moretó,et al.  Accelerating Edit-Distance Sequence Alignment on GPU using the Wavefront Algorithm , 2022, IEEE Access.

[61]  Lars Wienbrandt,et al.  Bioinformatics Applications on the FPGA-Based High-Performance Computer RIVYERA , 2013 .

[62]  Quinn Snell,et al.  Hardware Accelerated Sequence Alignment with Traceback , 2009, Int. J. Reconfigurable Comput..

[63]  Kevin Truong,et al.  160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA) , 2007, BMC Bioinformatics.