Events in January–February 2018
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Keynote
Keynote
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January 11, 2018 -
Predicting the Energy-Consumption of MPI Applications at Scale Using Only a Single Node, by Christian Heinrich (Polaris)
Predicting the Energy-Consumption of MPI Applications at Scale Using Only a Single Node, by Christian Heinrich (Polaris)
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January 18, 2018Monitoring and assessing the energy efficiency of supercomputers and
data centers is crucial in order to limit and reduce their energy
consumption. Applications from the domain of High Performance Computing
(HPC), such as MPI applications, account for a significant fraction of
the overall energy consumed by HPC centers. Simulation is a popular
approach for studying the behavior of these applications in a variety of
scenarios, and it is therefore advantageous to be able to study their
energy consumption in a cost-efficient, controllable, and also
reproducible simulation environment. Alas, simulators supporting HPC
applications commonly lack the capability of predicting the energy
consumption, particularly when target platforms consist of multi-core
nodes. In this work, we aim to accurately predict the energy consumption
of MPI applications via simulation. Firstly, we introduce the models
required for meaningful simulations: The computation model, the
communication model, and the energy model of the target platform.
Secondly, we demonstrate that by carefully calibrating these models on a
single node, the predicted energy consumption of HPC applications at a
larger scale is very close (within a few percents) to real experiments.
We further show how to integrate such models into the SimGrid simulation
toolkit. In order to obtain good execution time predictions on
multi-core architectures, we also establish that it is vital to
correctly account for memory effects in simulation. The proposed
simulator is validated through an extensive set of experiments with
well-known HPC benchmarks. Lastly, we show the simulator can be used to
study applications at scale, which allows researchers to save both time
and resources compared to real experimentsBâtiment IMAG (442) -
Keynote
Keynote
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February 1, 2018 -
Datamove workshop
Datamove workshop
N/A
February 8, 2018 -
Untitled Event
Untitled Event
N/A
February 15, 2018Parallel Sequence Alignment of Whole Chromosomes with Hundreds of GPUs and Pruning (by Alba Cristina Magalhaes Alves de Melo, University of Brasilia )Parallel Sequence Alignment of Whole Chromosomes with Hundreds of GPUs and Pruning (by Alba Cristina Magalhaes Alves de Melo, University of Brasilia )
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February 15, 2018Biological 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%.Short 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). -
Seminar recess (vacation)
Seminar recess (vacation)
N/A
February 22, 2018
