WG – Alba Cristina Magalhaes Alves de Melo: Parallel Sequence Alignment of Whole Chromosomes with Hundreds of GPUs and Pruning


Title: Parallel Sequence Alignment of Whole Chromosomes with Hundreds of
GPUs and Pruning

Speaker: Alba Cristina Magalhaes Alves de Melo

Abstract: Biological Sequence Alignment is a very basic operation in Bioinformatics used routinely worldwide. Smith-Waterman is the exact algorithm used to compare two sequences, obtaining the optimal alignment in quadratic time and space. In order to accelerate Smith-Waterman, many GPU-based strategies were proposed in the literature. However, aligning DNA sequences of millions of characters, or Base Pairs (MBP), is still a very challenging task. In this talk, we discuss related work in the area of parallel biological sequence alignment and present our multi-GPU strategy to align DNA sequences with up to 249 millions of characters in 384 GPUs. In order to achieve this, we propose an innovative speculation technique, which is able to parallelize a phase of the Smith-Waterman algorithm that is inherently sequential. We combined our speculation technique with sophisticated buffer management and fine-grain linear space matrix processing strategies to obtain our parallel algorithm. As far as we know, this is the first implementation of Smith-Waterman able to retrieve the optimal alignment between sequences with more than 50
millions of characters. We will also present a pruning technique for one GPU that is able to prune more than 50% of the Smith-Waterman matrix and still retrieve the optimal alignment. We will show the results obtained in the Keeneland cluster (USA), where we compared all the human x chimpanzee homologous chromosomes (ranging from 26 MBP to 249 MBP). The human_chimpanzee chromosome 5 comparison (180 MBP x 183 MBP) attained 10.35 TCUPS (Trillions of Cells Updated per Second) using 384 GPUs. In this case, we processed 45 petacells, being able to produce the optimal alignment in 53 minutes and 7 seconds, with a speculation hit ratio of 98.2%.

Speaker Bio:  Alba Cristina Magalhaes Alves de Melo obtained her PhD degree in Computer Science from the Institut National Polytechnique de Grenoble (INPG), France, in 1996. In 2008, she did a postdoc at the University of Ottawa, Canada; in 2011, she was invited as Guest Scientist at Université Paris-Sud, France; and in 2013 she did a sabbatical at the Universitat Polytecnica de Catalunya, Spain. Since 1997, she works at the Department of Computer Science at the University of Brasilia (UnB), Brazil, where she is now a Full Professor. She is also a CNPq Research Fellow level 1D in Brazil. She was the Coordinator of the Graduate Program in Informatics at UnB for several years (2000-2002, 2004-2006, 2008, 2010, 2014) and she coordinated international collaboration projects with the Universitat Politecnica de Catalunya, Spain (2012, 2014-2016) and with the University of Ottawa, Canada (2012-2015). In 2016, she received the Brazilian Capes Award on “Advisor of the Best PhD Thesis in Computer Science”. Her research interests are High Performance Computing, Bioinformatics and Cloud Computing. She advised 2 postdocs, 4 PhD Thesis and 22 MsC Dissertations. Currently, she advises 4 PhD students and 2 MsC students. She is Senior Member of the IEEE Society and Member of the Brazilian Computer Society. She gave invited talks at Universitat Karlshure, Germany, Université Paris-Sud, France, Universitat Polytecnica de Catalunya, Spain, University of Ottawa, Canada and at Universidad del Chile, Chile. She has currently 91 papers
listed at  DBLP (www.informatik.uni-trier.de/~ley/db/indices/a-tree/m/Melo:Alba_Cristina_Magalhaes_Alves_de.html).