Alfredo Buttari
Table of Contents
CNRS researcher @ IRIT
2 rue Camichel, 31071 Toulouse, France (map)
telephone: +33 5 34 32 22 08
email: alfredo dot buttari at irit dot fr
Bio
I am currently a CNRS (Centre National de la Recherche Scientifique) researcher at the IRIT (Institut de Recherche en Informatique de Toulouse) laboratory in Toulouse (France) where I am a member of the APO (Algorithmes Parallèles et Optimisation). My interest are in High Performance Computing, parallel computing, computational linear algebra (numerical software in general). Here is my CV and a short bio:
- since 2021: CNRS research director @ IRIT
- 2008-2021: CNRS researcher @ IRIT
- 2018: Habilitation à Diriger des Recherches (manuscript, presentation).
- 2008: post-doc at INRIA Rhone-Alpes in Lyon (France) where I was a member of the Laboratoire de l'Informatique du Parallelisme (LIP).
- 2006-2007: post-doc in the Innovative Computing Laboratory (ICL) lead by Prof. Jack Dongarra at the University of Tennessee Knoxville.
- 2003-2006 Ph.D. at Dipartimento Informatica Sistemi e Produzione of University of Rome "Tor Vergata". (manuscript)
Research
My research activity focuses on Computational Linear Algebra. This discipline deals with the issues related to the efficient and numerically reliable computation of linear algebra operations arising in numerous scientific and industrial applications from a wide range of domains including physics, chemistry or data analysis. These applications commonly involve data of very large size, which makes the use of supercomputers unavoidable to cope with the resulting considerable computational and memory cost. As a result, my work is concerned with the development of reliable, efficient and scalable numerical linear algebra methods as well as their implementation on large-scale parallel supercomputers. Specifically my research is focused on the solution of systems of linear equations (both dense and sparse) on parallel, heterogeneous supercomputers in a reliable and scalable way where, by scalability, I mean the ability to solve systems of larger and larger size. This is achieved through the development and analysis of
- algorithms that improve parallelism and the use of efficient parallel programming paradigms that allows for achieving high efficiency and performance on large scale parallel computers;
- scheduling policies that keep the memory consumption under control in a parallel setting;
- methods that can reduce the complexity of the solution, both in terms of memory and number of operations, at the price of a controlled loss of accuracy.
Current projects
- 2019-2023: SOLHARIS I am the Principal Investigator of the SOLHARIS (ANR-19-CE46-0009) project funded by the ANR AAPG-2019 program. This project aims at developing algorithms, programming models and scheduling methods that improve the scalability of sparse linear algebra solvers and, in general, of scientific computing libraries, on large scale parallel hand heterogeneous supercomputers. This project gathers researchers from IRIT-CNRS, Inria Bordeaux Sud-Ouest, Inria Rhône-Alpes, CEA and Airbus.
- 2019-2023: ANITI Within the ANITI 3IA institute of Toulouse, I am co-chair of the ``Efficient algorithms and Data Assimilation for Computationally Efficient Constrained Advanced Learning'' chair lead by Prof Serge Gratton. This chair is structured around two main scientific subjects. The first is the hybridization of machine learning and data assimilation techniques. The second is related to the performance of deep learning methods at the large (i.e., on parallel supercomputers) and small (i.e., embedded systems with speed, memory and energy constraints) scale.
- 2015-2018, 2019-2021: EoCoE(-II) I was a member of the EoCoE project, funded by the H2020-EU.1.4.1.3 European program, that gathers numerous European acedemic and industrial partners. The project aims to establish an Energy Oriented Centre of Excellence for computing applications. A followup to this project was proposed in response to the H2020-INFRAEDI-2018-1 call and accepted; the project is set to start on January 1st 2019. I am the correspondent of the CNRS-IRIT partner of the project.
Past projects
- 2014-2019: SCEBF/PhD/SRFCP I was the PI of the ``Solveurs Couplés pour l'Électromagnétisme Basses Fréquences'' (SCEBF) and member of the ``Parallélisation d'un solveur $\mathcal{H}$-matrix pour la Diffraction d'ondes électromagnétiques'' (PhD) and ``Solveur Rapide pour Fibres à Cristaux Photoniques'' (SRFCP) projects funded by the Toulouse Tech Intel Labs (TTIL) program in collaboration with Dr Ronan Perrussel and Prof Jean-René Poirier of the LAPLACE laboratory of Toulouse.
- 2013-2018: SOLHAR I was a member of the SOLHAR project (ANR-13-MONU-0007) in collaboration with the HiePACS, STORM, RealOPT Inria teams of Bordeaux, the ROMA Inria team of Lyon, Airbus CRT and CEA industrial partners. The objective of this project was to investigate algorithms, methods and programming models for the porting of linear system solvers on modern, heterogeneous architectures through the use of runtime systems. I was deeply involved in the writing of the project proposal and I was leader of Task~1 Linear Algebra.
- 2010-2013: FP3C I was a member of the Japanese-french FP3C (Framework and Programming for Post-Petascale Computing) Project ANR/JST-2010-JTIC-003 whose objective was to study the software technologies, languages and programming models on the road to Exascale computing.}
- 2009-2010: Multicomputing I was co-PI (the other co-PI being Prof Alexander Gefgat of the Tel Aviv University) of the ``Improving scalability of state-of-the-art computational fluid dynamics by state-of-the-art numerical linear algebra approaches'' project between funded by High Council for Scientific and Technological Cooperation between France-Israel (the French Ministère des Affaires Etrangères, the French Ministère de L'Education Nationale, de l'Enseignement Supérieur et de la Recherche and the Israeli Ministry of Science, Culture \& Sport).
Code
Current projects
- qr_mumps. I am the main developer of the qr_mumps software. qr_mumps is a software package for the solution of sparse, linear systems on multicore computers. It implements a direct solution method based on the QR factorization of the input matrix. Therefore, it is suited to solving sparse least-squares problems and to computing the minimum-norm solution of sparse, underdetermined problems. qr_mumps is a parallel, multithreaded software based on the OpenMP standard.Parallelism is achieved by dividing the workload into fine grained tasks that are arranged in a Direct Acyclic Graph (DAG). The execution of these tasks is guiged by an asynchronous and dynamic data-flow programming model which provides high efficiency and scalability. Here is a poster I presented at the 2011 Householder meeting. In this context I am currently working on the integration of runtime systems (such as StarPU or Parsec) and on the usage of GPUs.
- MUMPS. I am a member of the MUltifrontal Massively Parallel sparse direct Solver (MUMPS) project. The MUMPS package implements a multifrontal (direct) solver for sparse linear systems. It is an SPMD parallel code based on MPI and provides a wide range of features. Within this project I am principally involved in investigating the use of Low-Rank approximation techniques to reduce the execution time as well as the memory footprint.
- PSBLAS. I occasionally collaborate to the Parallel Sparse BLAS (PSBLAS) project. The PSBLAS software implements basic kernels for sparse computations as well as a bunch of iterative methods (CG, GMRES, BiCG,…) and preconditioners (Block-Jacobi, Additive-Schwarz, Multilevel,…) for the solution of sparse linear systems. It is an SPMD parallel code based on MPI and it is written in Fortran2003.
Teaching
High Performance Computing Algorithms
Calcul Réparti et Grid Computing
Large Scale Sparse Linear Algebra
OpenMP / Systèmes Concurrents
Publications
In preparation or submitted
[1] | Patrick Amestoy, Olivier Boiteau, Alfredo Buttari, Matthieu Gerest, Fabienne Jézéquel, Jean-Yves L'Excellent, and Théo Mary. Mixed Precision Low Rank Approximations and their Application to Block Low Rank LU Factorization, June 2021. working paper or preprint. [ eprint | .pdf ] |
[2] | Patrick Amestoy, Alfredo Buttari, Nicholas Higham, Jean-Yves L'Excellent, Théo Mary, and Bastien Vieuble. Five-Precision GMRES-based iterative refinement, April 2021. working paper or preprint. [ eprint ] |
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Journals
[1] | Alfredo Buttari, Markus Huber, Philippe Leleux, Theo Mary, Ulrich Rüde, and Barbara Wohlmuth. Block low-rank single precision coarse grid solvers for extreme scale multigrid methods. Numerical Linear Algebra with Applications, n/a(n/a):e2407, 2021. [ DOI | eprint ] |
[2] | Cleve Ashcraft, Alfredo Buttari, and Théo Mary. Block Low-Rank Matrices with Shared Bases: Potential and Limitations of the BLR2 Format. SIAM Journal on Matrix Analysis and Applications, 2021. [ eprint ] |
[3] | Alfredo Buttari, Søren Hauberg, and Costy Kodsi. Parallel qr factorization of block-tridiagonal matrices. SIAM Journal on Scientific Computing, 42(6):C313--C334, 2020. [ DOI | eprint ] |
[4] | Patrick R. Amestoy, Alfredo Buttari, Jean-Yves L'Excellent, and Theo Mary. Performance and scalability of the block low-rank multifrontal factorization on multicore architectures. ACM Trans. Math. Softw., 45(1):2:1--2:26, February 2019. [ DOI | eprint ] |
[5] | Alfredo. Buttari, Dominique. Orban, Daniel. Ruiz, and David. Titley-Peloquin. A tridiagonalization method for symmetric saddle-point systems. SIAM Journal on Scientific Computing, 41(5):S409--S432, 2019. [ DOI | eprint ] |
[6] | Patrick R. Amestoy, Alfredo. Buttari, Jean-Yves. L'Excellent, and Theo A. Mary. Bridging the gap between flat and hierarchical low-rank matrix formats: The multilevel block low-rank format. SIAM Journal on Scientific Computing, 41(3):A1414--A1442, 2019. [ DOI | eprint ] |
[7] | Daniil V. Shantsev, Piyoosh Jaysaval, Sebastien de la Kethulle de Ryhove, Patrick R. Amestoy, Alfredo Buttari, Jean-Yves L'Excellent, and Theo Mary. Large-scale 3D EM modeling with a Block Low-Rank multifrontal direct solver. Geophysical Journal International, March 2017. [ DOI | eprint ] |
[8] | Patrick Amestoy, Alfredo Buttari, Jean-Yves L'Excellent, and Theo Mary. On the complexity of the block low-rank multifrontal factorization. SIAM Journal on Scientific Computing, 39(4):A1710--A1740, 2017. [ DOI | eprint ] |
[9] | Emmanuel Agullo, Alfredo Buttari, Abdou Guermouche, and Florent Lopez. Implementing multifrontal sparse solvers for multicore architectures with sequential task flow runtime systems. ACM Trans. Math. Softw., 43(2):13:1--13:22, August 2016. [ DOI | eprint ] |
[10] | Patrick R. Amestoy, Romain Brossier, Alfredo Buttari, Jean-Yves L'Excellent, Théo Mary, Ludovic Métivier, Alain Miniussi, and Stéphane Operto. Fast 3D frequency-domain full waveform inversion with a parallel Block Low-Rank multifrontal direct solver: application to OBC data from the North Sea. Geophysics, 81(6):R363 -- R383, 2016. [ DOI | eprint ] |
[11] | Emmanuel Agullo, Patrick R. Amestoy, Alfredo Buttari, Abdou Guermouche, Jean-Yves L'Excellent, and François-Henry Rouet. Robust memory-aware mappings for parallel multifrontal factorizations. SIAM Journal on Scientific Computing, 38(3):C256--C279, 2016. [ DOI | eprint ] |
[12] | Patrick Amestoy, Cleve Ashcraft, Olivier Boiteau, Alfredo Buttari, Jean-Yves L'Excellent, and Clément Weisbecker. Improving multifrontal methods by means of block low-rank representations. SIAM Journal on Scientific Computing, 37(3):A1451--A1474, 2015. [ DOI | eprint ] |
[13] | Patrick Amestoy, Alfredo Buttari, Guillaume Joslin, Jean-Yves L'Excellent, Mohamed Sid-Lakhdar, Clement Weisbecker, Michele Forzan, Christian Pozza, Remy Perrin, and Valene Pellissier. Shared-memory parallelism and low-rank approximation techniques applied to direct solvers in fem simulation. IEEE Transactions on Magnetics, 50(2):517--520, Feb 2014. [ DOI | eprint ] |
[14] | Laurent Bouchet, Patrick Amestoy, Alfredo Buttari, François-Henry Rouet, and Maxime Chauvin. INTEGRAL/SPI data segmentation to retrieve sources intensity variations. Astronomy & Astrophysics, A52:(on line), July 2013. [ DOI | eprint ] |
[15] | Alfredo Buttari. Fine-grained multithreading for the multifrontal QR factorization of sparse matrices. SIAM Journal on Scientific Computing, 35(4):C323--C345, 2013. [ DOI | eprint ] |
[16] | Laurent Bouchet, Patrick Amestoy, Alfredo Buttari, François-Henry Rouet, and Maxime Chauvin. Simultaneous analysis of large INTEGRAL/SPI datasets: optimizing the computation of the solution and its variance using sparse matrix algorithms. Astronomy and Computing, 1:59--69, 2013. [ DOI | eprint ] |
[17] | Salvatore Filippone and Alfredo Buttari. Object-oriented techniques for sparse matrix computations in Fortran 2003. ACM Transactions on Mathematical Software, 38(4):23:1--23:20, August 2012. [ DOI | eprint ] |
[18] | Alfredo Buttari, Julien Langou, Jakub Kurzak, and Jack Dongarra. A class of parallel tiled linear algebra algorithms for multicore architectures. Parallel Comput., 35:38--53, January 2009. [ DOI | eprint ] |
[19] | Mark Baboulin, Alfredo Buttari, Jack Dongarra, Jakub Kurzak, Julien Langou, Julie Langou, Piotr Luszczek, and Stanimire Tomov. Accelerating scientific computations with mixed precision algorithms. Computer Physics Communications, 180(12):2526--2533, 2009. [ DOI | eprint ] |
[20] | Jakub Kurzak, Alfredo Buttari, Piotr Luszczek, and Jack Dongarra. The playstation 3 for high-performance scientific computing. Computing in Science and Eng., 10(3):84--87, 2008. [ DOI | eprint ] |
[21] | Jakub Kurzak, Alfredo Buttari, and Jack Dongarra. Solving systems of linear equations on the cell processor using cholesky factorization. IEEE Trans. Parallel Distrib. Syst., 19(9):1175--1186, 2008. [ DOI | eprint ] |
[22] | Alfredo Buttari, Julien Langou, Jakub Kurzak, and Jack Dongarra. Parallel tiled QR factorization for multicore architectures. Concurr. Comput. : Pract. Exper., 20(13):1573--1590, 2008. [ DOI | eprint ] |
[23] | Alfredo Buttari, Jack Dongarra, Jakub Kurzak, Piotr Luszczek, and Stanimire Tomov. Using mixed precision for sparse matrix computations to enhance the performance while achieving 64-bit accuracy. ACM Trans. Math. Softw., 34(4):1--22, 2008. [ DOI | eprint ] |
[24] | Alfredo Buttari, V. Eijkhout, Julien Langou, and Salvatore Filippone. Performance optimization and modeling of blocked sparse kernels. Int. J. High Perform. Comput. Appl., 21(4):467--484, 2007. [ DOI | eprint ] |
[25] | Alfredo Buttari, Jack Dongarra, Julien Langou, Julie Langou, Piotr Luszczek, and Jakub Kurzak. Mixed precision iterative refinement techniques for the solution of dense linear systems. Int. J. High Perform. Comput. Appl., 21(4):457--466, 2007. [ DOI | eprint ] |
[26] | Alfredo Buttari, Pasqua D'Ambra, Daniela Di Serafino, and Salvatore Filippone. 2LEV-D2P4: a package of high-performance preconditioners for scientific and engineering applications. Appl. Algebra Eng., Commun. Comput., 18(3):223--239, 2007. [ DOI | eprint ] |
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Conferences
[1] | Gabriel Hautreux, Alfredo Buttari, Arnaud Beck, Victor Cameo, Dimitri Lecas, Dominique Aubert, Emeric Brun, Eric Boyer, Fausto Malvagi, Gabriel Staffelbach, Isabelle d'Ast, Joeffrey Legaux, Ghislain Lartigue, Gilles Grasseau, Guillaume Latu, Juan Escobar, Julien Bigot, Julien Derouillat, Matthieu Haefele, Nicolas Renon, Philippe Parnaudeau, Philippe Wautelet, Pierre-Francois Lavallee, Pierre Kestener, Remi Lacroix, Stephane Requena, Anthony Scemama, Vincent Moureau, Jean-Matthieu Etancelin, and Yann Meurdesoif. Pre-exascale architectures: Openpower performance and usability assessment for french scientific community. In Julian M. Kunkel, Rio Yokota, Michela Taufer, and John Shalf, editors, High Performance Computing: ISC High Performance 2017 International Workshops, DRBSD, ExaComm, HCPM, HPC-IODC, IWOPH, IXPUG, P3MA, VHPC, Visualization at Scale, WOPSSS, Frankfurt, Germany, June 18-22, 2017, Revised Selected Papers, pages 309--324, Cham, 2017. Springer International Publishing. [ DOI | eprint ] |
[2] | Emmanuel Agullo, George Bosilca, Alfredo Buttari, Abdou Guermouche, and Florent Lopez. Exploiting a parametrized task graph model for the parallelization of a sparse direct multifrontal solver. In Frédéric Desprez, Pierre-François Dutot, Christos Kaklamanis, Loris Marchal, Korbinian Molitorisz, Laura Ricci, Vittorio Scarano, Miguel A. Vega-Rodríguez, Ana Lucia Varbanescu, Sascha Hunold, Stephen L. Scott, Stefan Lankes, and Josef Weidendorfer, editors, Euro-Par 2016: Parallel Processing Workshops: Euro-Par 2016 International Workshops, Grenoble, France, August 24-26, 2016, Revised Selected Papers, pages 175--186, Cham, 2017. Springer International Publishing. [ DOI | eprint ] |
[3] | Luka Stanisic, Emmanuel Agullo, Alfredo Buttari, Abdou Guermouche, Arnaud Legrand, Florent Lopez, and Brice Videau. Fast and accurate simulation of multithreaded sparse linear algebra solvers. In Parallel and Distributed Systems (ICPADS), 2015 IEEE 21st International Conference on, pages 481--490, Dec 2015. [ DOI ] |
[4] | Emmanuel Agullo, Alfredo Buttari, Abdou Guermouche, and Florent Lopez. Task-based multifrontal QR solver for GPU-accelerated multicore architectures. In HiPC, pages 54--63. IEEE Computer Society, 2015. Best paper award. [ DOI | eprint ] |
[5] | Patrick R. Amestoy, Romain Brossier, Alfredo Buttari, Jean-Yves L'Excellent, Théo Mary, Ludovic Métivier, Alain Miniussi, Stéphane Operto, Alessandra Ribodetti, Jean Virieux, and Clément Weisbecker. Efficient 3d frequency-domain full-waveform inversion of ocean-bottom cable data with sparse block low-rank direct solver: a real data case study from the north sea. In SEG Technical Program Expanded Abstracts 2015, pages 1303--1308, 2015. [ DOI | eprint ] |
[6] | Patrick R. Amestoy, Romain Brossier, Alfredo Buttari, Jean-Yves L'Excellent, Théo Mary, Ludovic Métivier, Alain Miniussi, Stéphane Operto, Jean Virieux, and Clément Weisbecker. 3D frequency-domain seismic modeling with a parallel blr multifrontal direct solver. In SEG Technical Program Expanded Abstracts 2015, pages 3606--3611, 2015. [ DOI | eprint ] |
[7] | Patrick Amestoy, Alfredo Buttari, Guillaume Joslin, Jean-Yves L'Excellent, Mohamed Sid-Lakhdar, Clement Weisbecker, Michele Forzan, Cristian Pozza, Remy Perrin, and Valene Pellissier. Shared memory parallelism and low-rank approximation techniques applied to direct solvers in FEM simulation. In IEEE International Conference on the Computation of Electromagnetic Fields (COMPUMAG), Budapest, Hungary, 30/06/2013-04/07/2013. IEEE, June 2013. [ DOI ] |
[8] | Clement Weisbecker, Patrick Amestoy, Olivier Boiteau, Romain Brossier, Alfredo Buttari, Jean-Yves L'Excellent, Stephane Operto, and Jean Virieux. 3d frequency-domain seismic modeling with a block low-rank algebraic multifrontal direct solver. In SEG Technical Program Expanded Abstracts 2013, pages 3411--3416, 2013. [ DOI ] |
[9] | Laurent Bouchet, Patrick Amestoy, Alfredo Buttari, François-Henry Rouet, and Maxime Chauvin. INTEGRAL/SPI data segmentation to retrieve sources intensity variations (regular paper). In A. Goldwurm, F. Lebrun, and C. Winkler, editors, An INTEGRAL view of the high-energy sky (the first 10 years), Paris, France, 15/10/2012-19/10/2012, 2013. [ DOI ] |
[10] | Emmanuel Agullo, Alfredo Buttari, Abdou Guermouche, and Florent Lopez. Multifrontal QR factorization for multicore architectures over runtime systems. In Euro-Par 2013 Parallel Processing, pages 521--532. Springer Berlin Heidelberg, 2013. [ DOI ] |
[11] | G. Antoniu, T. Boku, A. Buttari, C. Calvin, P. Codognet, M. Daydé, N. Emad, Y. Ishikawa, G. Joslin, S. Matsuoka, K. Nakajima, H. Nakashima, R. Namyst, S. Petiton, T. Sakurai, and M. Sato. Towards exascale with the anr-jst japanese-french project fp3c. In Ninth International Conference on Computer Science and Information Technologies Revised Selected Papers, pages 1--10, Sept 2013. [ DOI ] |
[12] | Emmanuel Agullo, Patrick R Amestoy, Alfredo Buttari, Abdou Guermouche, Guillaume Joslin, Jean-Yves L'Excellent, Xiaoye S Li, Artem Napov, François-Henry Rouet, Mohamed Sid-Lakhdar, et al. Recent advances in sparse direct solvers. In Conference on Structural Mechanicsin Reactor Technology, 2013. |
[13] | Alfredo Buttari. Fine granularity sparse QR factorization for multicore based systems. In Proceedings of the 10th international conference on Applied Parallel and Scientific Computing - Volume 2, PARA'10, pages 226--236, Berlin, Heidelberg, 2012. Springer-Verlag. [ DOI ] |
[14] | Alfredo Buttari, Julien Langou, Jakub Kurzak, and Jack Dongarra. Parallel tiled QR factorization for multicore architectures. In PPAM'07: Proceedings of the 7th international conference on Parallel processing and applied mathematics, pages 639--648, Berlin, Heidelberg, 2008. Springer-Verlag. [ DOI ] |
[15] | J. Kurzak and A. Buttari. Introduction to programming high performance applications on the cell broadband engine. In 15th Annual IEEE Symposium on High-Performance Interconnects (HOTI 2007), pages 11--11, Aug 2007. [ DOI ] |
[16] | Alfredo Buttari, Jack Dongarra, Jakub Kurzak, Julien Langou, Piotr Luszczek, and Stanimire Tomov. The impact of multicore on math software. In Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing, PARA'06, pages 1--10, Berlin, Heidelberg, 2007. Springer-Verlag. [ DOI ] |
[17] | Alfredo Buttari, Jack Dongarra, Parry Husbands, Jakub Kurzak, and Katherine Yelick. Multithreading for synchronization tolerance in matrix factorization. In Proceedings of the SciDAC 2007 Conference, volume 78, page 012028, Boston, Massachusetts, 2007. Journal of Physics: Conference Series. [ DOI ] |
[18] | Jim Demmel, Jack Dongarra, Beresford Parlett, William Kahan, Ming Gu, Bindel Bindel, Yozo Hida, Xiaoye Sherry Li, Osni Marques, Jason Riedy, Christof Vomel, Julien Langou, Piotr Luszczek, Jakub Kurzak, Alfredo Buttari, Julie Langou, and Stanimire Tomov. Prospectus for the next lapack and scalapack libraries. In PARA'06: State-of-the-Art in Scientific and Parallel Computing, Umeå, Sweden, June 2006. High Performance Computing Center North (HPC2N) and the Department of Computing Science, UmeåUniversity, Springer. [ DOI ] |
[19] | Alfredo Buttari, Pasqua D'Ambra, Di Serafino Di Serafino, and Salvatore Filippone. Extending PSBLAS to Build Parallel Schwarz Preconditioners. In Springer, editor, Applied Parallel Computing. State of the Art in Scientific Computing: 7th International Conference, PARA 2004, Lyngby, Denmark, June 20-23, 2004., volume 3732 of Lecture Notes in Computer Science, pages 593--602, February 2006. [ DOI ] |
[20] | Julien Langou, Julie Langou, Piotr Luszczek, Jakub Kurzak, Alfredo Buttari, and Jack Dongarra. Exploiting the performance of 32 bit floating point arithmetic in obtaining 64 bit accuracy (revisiting iterative refinement for linear systems). In SC '06: Proceedings of the 2006 ACM/IEEE conference on Supercomputing, page 113, New York, NY, USA, 2006. ACM. [ DOI ] |
[21] | Gino Bella, Alfredo Buttari, Alessandro De Maio, Francesco Del Citto, Salvatore Filippone, and Fabiano Gasperini. FAST-EVP: an engine simulation tool. In Springer, editor, High Perfromance Computing and Communications. First International Conference, HPCC 2005, Proceedings, volume 3726 of Lecture Notes in Computer Science, pages 976--986, September 2005. . [ DOI ] |
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Book Chapters
[1] | Patrick Amestoy, Alfredo Buttari, Iain Duff, Abdou Guermouche, Jean-Yves L'Excellent, and Bora Uçar. The Multifrontal Method. In David Padua, editor, Encyclopedia of Parallel Computing. Springer Verlag, 2011. |
[2] | Patrick Amestoy, Alfredo Buttari, I. Duff, A. Guermouche, Jean-Yves L'Excellent, and Bora Uçar. MUMPS. In David Padua, editor, Encyclopedia of Parallel Computing. Springer Verlag, 2011. |
[3] | Jim Demmel, Jack Dongarra, Beresford Parlett, William Kahan, Ming Gu, Bindel Bindel, Yozo Hida, Xiaoye Sherry Li, Osni Marques, Jason Riedy, Christof Vomel, Julien Langou, Piotr Luszczek, Jakub Kurzak, Alfredo Buttari, Julie Langou, and Stanimire Tomov. Prospectus for a linear algebra software library for dense matrix problems. In Sanguthevar Rajasekaran and John Reif, editors, Handbook of Parallel Computing: Models, Algorithms and Applications, volume 17 of Chapman & HallCRC Computer & Information Science. CRC Press, 1 edition, December 2007. ISBN: 9781584886235. |
[4] | Alfredo Buttari, Jack Dongarra, Jakub Kurzak, and Julien Langou. Parallel dense linear algebra software in the multicore era. In Junwei Cao, editor, Cyberinfrastructure Technologies and Applications. Nova Science Publishers, 2007. |
[5] | Alfredo Buttari, Jack Dongarra, Jakub Kurzak, Julien Langou, Julie Langou, Piotr Luszczek, and Stanimire Tomov. Exploiting mixed precision floating point hardware in scientific computations. In L. Grandinetti, editor, High Performance Computing and Grids in Action. IOS Press, 2007. |
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Technical reports
[1] | Emmanuel Agullo, Alfredo Buttari, Mikko Byckling, Abdou Guermouche, and Ian Masliah. Achieving high-performance with a sparse direct solver on Intel KNL. Research Report RR-9035, Inria Bordeaux Sud-Ouest ; CNRS-IRIT ; Intel corporation ; Université Bordeaux, February 2017. |
[2] | Alfredo Buttari, Piotr Luszczek, Jakub Kurzak, Jack Dongarra, and George Bosilca. SCOP3: A rough guide to scientific computing on the PlayStation 3. version 0.1. Technical Report UT-CS-07-595, Innovative Computing Laboratory, University of Tennessee Knoxville, April 2007. |
[3] | Alfredo Buttari, Jakub Kurzak, and Jack Dongarra. Limitations of the PlayStation 3 for High Performance Cluster Computing. Technical Report UT-CS-07-597, Innovative Computing Laboratory, University of Tennessee Knoxville, April 2007. LAPACK Working Note 185. |
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