CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011

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LIST OF MEMBERS OF HIEPACS 2010] JÉRÔME SOUMAGNE [CSCS, funding from Europe FP7/ICT/FET NextMuSE STREP, since Apr. 2009] CLÉMENT VUCHENER [University of Bordeaux, funding from French Research Ministry, since Sept. 2010] MAWUSSI ZOUNON [Inria, funding from ANR-RESCUE, since Oct. 2011] Post-Doctoral Fellows MIKKO BYCKLING [CERFACS, ALGO Project, since Oct. 2010] YAN-FEI JING [Inria, since Oct. 2011] Administrative Assistants BARTA BENEDDINE [Inria, ended June 2011] MARIE SANCHEZ [Inria, July-Oct. 2011] CHRYSTEL PLUMEJEAU [Inria, since Nov. 2011] BRIGITTE YZEL [CERFACS] 10 Jan. 2010 – Dec. 2011
4 Dense and Sparse Matrix Computations 4.1 Analysis of the solution phase of a parallel multifrontal approach. P. Amestoy : ENSEEIHT-IRIT, UNIVERSITY OF TOULOUSE, France ; I. S. Duff : RUTHERFORD APPLETON LABORATORY AND CERFACS, UK and France ; A. Guermouche : LABRI, UNIV. BORDEAUX 1 / INRIA BORDEAUX SUD-OUEST, France ; Tz. Slavova : CERFACS, France In [ALG9], we study the forward and backward substitution phases of a sparse multifrontal factorization. These phases are often neglected in papers on sparse direct factorization but, in many applications, they can be the bottleneck so it is crucial to implement them efficiently. In this work, we assume that the factors have been written on disk during the factorization phase, and we discuss the design of an efficient solution phase. We will look at the issues involved when we are solving the sparse systems on parallel computers and will consider in particular their solution in a limited memory environment when out-of-core working is required. Two different approaches are presented to read data from the disk, with a discussion on the advantages and the drawbacks of each. We present some experiments on realistic test problems using an out-of-core version of a sparse multifrontal code called MUMPS (MUltifrontal Massively Parallel Solver). 4.2 On computing inverse entries of a sparse matrix in an out-of-core environment. P. Amestoy : INPT(ENSEEIHT)-IRIT, UNIVERSITY OF TOULOUSE, France ; I. S. Duff : RUTHERFORD APPLETON LABORATORY AND CERFACS, UK and France ; Y. Robert : CERFACS, France ; F.- H. Rouet : INPT(ENSEEIHT)-IRIT, France ; B. Uçar : ENS LYON AND CNRS, France The inverse of an irreducible sparse matrix is structurally full, so that it is impractical to think of computing or storing it. However, there are several applications where a subset of the entries of the inverse is required. Given a factorization of the sparse matrix held in out-of-core storage, we show how to compute such a subset efficiently, by accessing only parts of the factors. When there are many inverse entries to compute, we need to guarantee that the overall computation scheme has reasonable memory requirements, while minimizing the cost of loading the factors. This leads to a partitioning problem that we prove is NP-complete. We also show that we cannot get a close approximation to the optimal solution in polynomial time. We thus need to develop heuristic algorithms, and we propose : (i) a lower bound on the cost of an optimum solution ; (ii) an exact algorithm for a particular case ; (iii) two other heuristics for a more general case ; and (iv) hypergraph partitioning models for the most general setting. We illustrate the performance of our algorithms in practice using the MUMPS software package on a set of real-life problems as well as some standard test matrices. We show that our techniques can improve the execution time by a factor of 50. For more details, see [ALG33]. CERFACS ACTIVITY REPORT 11
Page 1 and 2: CERFACS Scientific Activity Report
Page 3 and 4: Table des matières 1 Foreword xiii
Page 5 and 6: 9 Publications 40 9.1 Books . . . .
Page 7 and 8: 3 The OpenPALM coupler 104 3.1 Intr
Page 9 and 10: Table des figures CERFACS chart as
Page 11 and 12: TABLE DES FIGURES 6 Computational F
Page 13 and 14: Foreword Welcome to the 2010-2011 S
Page 15 and 16: CERFACS STRUCTURE CERFACS organizat
Page 17 and 18: CERFACS STAFF NAME POSITION PERIOD
Page 19 and 20: CERFACS STAFF SILVA GARZON Ph.D stu
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Page 23: CERFACS Wide-Interest Seminars Pete
Page 27 and 28: 1 Introduction 1.1 Introduction The
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Page 33: 3 List of Members of HiePACS HiePAC
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Page 57 and 58: 8 Conferences and Seminars 8.1 Conf
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Page 71 and 72: 1 Overview presentation The main ex
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ELECTROMAGNETISM AND ACOUSTICS TEAM
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1 Introduction Data assimilation is
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DATA ASSIMILATION 2.3 Calibrating o
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3 Data assimilation for atmospheric
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DATA ASSIMILATION BECM using or not
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DATA ASSIMILATION the potential vor
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DATA ASSIMILATION A two years simul
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DATA ASSIMILATION FIG. 4.1: Reducti
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DATA ASSIMILATION FIG. 4.3: April 2
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DATA ASSIMILATION by a surface mode
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6 Data assimilation with EDF neutro
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DATA ASSIMILATION demonstrate that
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DATA ASSIMILATION [DA13] S. Massart
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4 Coupling tools and HPC Climate Mo
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2 The OASIS coupler The OASIS coupl
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THE OASIS COUPLER 2.3 OASIS4 Since
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3 The OpenPALM coupler 3.1 Introduc
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THE OPENPALM COUPLER In the NitroEu
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4 HPC Climate modelling 4.1 General
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5 Publications 5.1 Conference Proce
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5 Climate Variability and Global Ch
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2 Climate variability and predictab
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CLIMATE VARIABILITY AND PREDICTABIL
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CLIMATE VARIABILITY AND PREDICTABIL
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CLIMATE CHANGE AND IMPACT STUDIES a
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CLIMATE CHANGE AND IMPACT STUDIES b
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PUBLICATIONS [CM15] Y. Kwon, C. Des
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1 Introduction The CFD (Computation
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2 Combustion The research activity
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COMPUTATIONAL FLUID DYNAMICS rate-o
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COMPUTATIONAL FLUID DYNAMICS FIG. 2
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COMPUTATIONAL FLUID DYNAMICS an iss
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COMPUTATIONAL FLUID DYNAMICS TU Ber
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COMPUTATIONAL FLUID DYNAMICS design
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COMPUTATIONAL FLUID DYNAMICS (a) (b
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COMPUTATIONAL FLUID DYNAMICS 3.1.5
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COMPUTATIONAL FLUID DYNAMICS (a) Ve
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COMPUTATIONAL FLUID DYNAMICS The cl
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COMPUTATIONAL FLUID DYNAMICS (a) Do
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5 Publications 5.1 Conferences Proc
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COMPUTATIONAL FLUID DYNAMICS [CFD34
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7 Aviation and Environment
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INTRODUCTION instead of regular ker
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SIMULATIONS OF AIRCRAFT WAKES AND R
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LARGE SCALE ATMOSPHERIC COMPOSITION
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LARGE SCALE ATMOSPHERIC COMPOSITION
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PUBLICATIONS 4.2 Technical Reports
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CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011

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CERFACS CERFACS Scientific Activity Report Jan. 2010 â Dec. 2011