Number of documents

72


Journal articles11 documents

  • Roman Iakymchuk, Stef Graillat, David Defour, Enrique Quintana-Ortí. Hierarchical approach for deriving a reproducible unblocked LU factorization. International Journal of High Performance Computing Applications, SAGE Publications, 2019, pp.#1094342019832968. ⟨10.1177/1094342019832968⟩. ⟨hal-01419813v4⟩
  • Hugues de Lassus Saint-Geniès, David Defour, Guillaume Revy. Exact Lookup Tables for the Evaluation of Trigonometric and Hyperbolic Functions. IEEE Transactions on Computers, Institute of Electrical and Electronics Engineers, 2017, 66 (12), pp.2058-2071. ⟨10.1109/TC.2017.2703870⟩. ⟨lirmm-01844332⟩
  • Manuel Marin, Federico Milano, David Defour. Midpoint-Radius Interval-based Method to Deal with Uncertainty in Power Flow Analysis. Electric Power Systems Research, Elsevier, 2017, 147, pp.81-87. ⟨10.1016/j.epsr.2017.02.017⟩. ⟨lirmm-01475577⟩
  • Manuel Marin, David Defour, Federico Milano. An efficient representation format for fuzzy intervals based on symmetric membership functions. ACM Transactions on Mathematical Software, Association for Computing Machinery, 2016, 43 (3), pp.23:1--23:22. ⟨10.1145/2939364⟩. ⟨lirmm-01385459⟩
  • David Defour, Eric Petit. A software scheduling solution to avoid corrupted units on GPUs. Journal of Parallel and Distributed Computing, Elsevier, 2016, 90-91, pp.1--8. ⟨10.1016/j.jpdc.2016.01.001⟩. ⟨lirmm-01267742⟩
  • Sylvain Collange, David Defour, Stef Graillat, Roman Iakymchuk. Numerical Reproducibility for the Parallel Reduction on Multi- and Many-Core Architectures. Parallel Computing, Elsevier, 2015, 49, pp.83-97. ⟨10.1016/j.parco.2015.09.001⟩. ⟨lirmm-01206348⟩
  • Michael François, David Defour, Christophe Negre. A Fast Chaos-Based Pseudo-Random Bit Generator Using Binary64 Floating-Point Arithmetic. Informatica, Slovene Society Informatika, Ljubljana, 2014, 38 (2), pp.115-124. ⟨http://www.informatica.si/index.php/informatica/article/view/691⟩. ⟨hal-01024689⟩
  • Sylvain Collange, Marc Daumas, David Defour. Line-by-line spectroscopic simulations on graphics processing units. Computer Physics Communications, Elsevier, 2008, 178 (2), pp.135-143. ⟨10.1016/j.cpc.2007.08.013⟩. ⟨lirmm-01206361⟩
  • Bernard Goossens, David Defour. The instruction register file micro-architecture. Future Generation Computer Systems, Elsevier, 2005, Parallel computing technologies, 21 (5), pp.767-773. ⟨10.1016/j.future.2004.05.017⟩. ⟨lirmm-01206362⟩
  • Jean-Michel Muller, Nicolas Brisebarre, Peter Kornerup, David Defour, Nathalie Revol. A new range-reduction algorithm. IEEE Transactions on Computers, Institute of Electrical and Electronics Engineers, 2005, 54 (3), pp.331- 339. ⟨10.1109/TC.2005.36⟩. ⟨ensl-00086904⟩
  • David Defour, Guillaume Hanrot, Vincent Lefèvre, Jean-Michel Muller, Nathalie Revol, et al.. Proposal for a Standardization of Mathematical Function Implementation in Floating-Point Arithmetic. Numerical Algorithms, Springer Verlag, 2004, 37 (1-4), pp.367-375. ⟨inria-00099967⟩

Conference papers35 documents

  • Yohan Chatelain, Pablo de Oliveira Castro, Eric Petit, David Defour, Jordan Bieder, et al.. VeriTracer: Context-enriched tracer for floating-point arithmetic analysis. 2018 IEEE 25th Symposium on Computer Arithmetic (ARITH), Jun 2018, Amherst, United States. pp.61-68. ⟨hal-01989607⟩
  • Roman Iakymchuk, Stef Graillat, David Defour, Erwin Laure, Enrique Quintana-Ortí. Towards a Reproducible Solution of Linear Systems. Supercomputing Conference 2017-Computational Reproducibility at Exascale Workshop, Nov 2017, Denver, United States. ⟨hal-01633980⟩
  • Manuel Marin, David Defour, Federico Milano. Asynchronous Power Flow on Graphic Processing Units. PDP: Parallel, Distributed and network-Based Processing, Mar 2017, St Petersburg, Russia. ⟨lirmm-01475578⟩
  • Roman Iakymchuk, Stef Graillat, David Defour, Enrique Quintana-Ortí. Hierarchical Approach for Deriving a Reproducible LU factorization on GPUs. The Numerical Reproducibility at Exascale (NRE16) workshop held as part of the Supercomputing Conference (SC16), Nov 2016, Salt Lake City, UT, United States. ⟨hal-01382645⟩
  • Roman Iakymchuk, David Defour, Stef Graillat. Towards Fast, Accurate and Reproducible LU Factorization. SCAN 2016, 17th international symposium on Scientific Computing, Computer Arithmetic and Validated Numerics, Sep 2016, Uppsala, Sweden. pp.59-60. ⟨hal-01539343⟩
  • Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat. Reproducible and Accurate Algorithms for Numerical Linear Algebra. PP: Parallel Processing for Scientific Computing, Apr 2016, Paris, France. ⟨lirmm-01268048⟩
  • Manuel Marin, David Defour, Federico Milano. An efficient midpoint-radius implementation to handle symmetric fuzzy intervals. RAIM: Rencontres Arithmétiques de l’Informatique Mathématique, Apr 2015, Rennes, France. ⟨hal-01140504⟩
  • Roman Iakymchuk, Sylvain Collange, David Defour, Stef Graillat. ExBLAS: Reproducible and Accurate BLAS Library. NRE: Numerical Reproducibility at Exascale, Nov 2015, Austin, TX, United States. ⟨hal-01202396v3⟩
  • Hugues de Lassus Saint-Geniès, David Defour, Guillaume Revy. Range Reduction Based on Pythagorean Triples for Trigonometric Function Evaluation. ASAP: Application-specific Systems, Architectures and Processors, Jul 2015, Toronto, Canada. pp.74-81, ⟨10.1109/ASAP.2015.7245712⟩. ⟨hal-01134232v2⟩
  • Hugues de Lassus Saint-Geniès, David Defour, Guillaume Revy. Réduction d'argument basée sur les triplets pythagoriciens pour l'évaluation de fonctions trigonométriques. ComPAS: Conférence en Parallélisme, Architecture et Système, Jun 2015, Lille, France. ⟨lirmm-01136772⟩
  • Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat. Reproducible Triangular Solvers for High-Performance Computing. ITNG: Information Technology - New Generations, Apr 2015, Las Vegas, NV, United States. pp.353-358, ⟨10.1109/ITNG.2015.63⟩. ⟨lirmm-01206371⟩
  • David Defour. Measuring predictability of Nvidia’s GPU warp and block schedulers: Application to the summation problem. MCSoC: Embedded Multicore/Many-core Systems-on-Chip, Sep 2015, Turin, Italy. pp.17-24, ⟨10.1109/MCSoC.2015.9⟩. ⟨hal-01267747⟩
  • David Defour, Sylvain Collange. Reproducible floating-point atomic addition in data-parallel environment. ACSIS, Sep 2015, Lodz, Poland. pp.721-728, ⟨10.15439/2015F86⟩. ⟨hal-01267755⟩
  • Roman Iakymchuk, Sylvain Collange, David Defour, Stef Graillat. Reproducibility and Accuracy for High-Performance Computing. RAIM: Rencontres Arithmétiques de l’Informatique Mathématique, Apr 2015, Rennes, France. ⟨hal-01140531⟩
  • Sylvain Collange, David Defour, Stef Graillat, Roman Iakymchuk. Reproducible and Accurate Matrix Multiplication for High-Performance Computing. SCAN: Scientific Computing, Computer Arithmetic and Validated Numerics, Sep 2014, Wuerzburg, Germany. pp.42-43. ⟨hal-01215627⟩
  • Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat. Reproducible and Accurate Matrix Multiplication. SCAN: Scientific Computing, Computer Arithmetic and Validated Numerics, Sep 2014, Wurzburg, Germany. pp.126-137, ⟨10.1007/978-3-319-31769-4_11⟩. ⟨hal-01539180⟩
  • Michael François, David Defour, Pascal Berthomé. A Pseudo-Random Bit Generator Based on Three Chaotic Logistic Maps and IEEE 754-2008 Floating-Point Arithmetic. Theory and Applications of Models of Computation, Apr 2014, Chennai, India. pp.229-247, ⟨10.1007/978-3-319-06089-7_16⟩. ⟨hal-00985357⟩
  • Manuel Marin, David Defour, Federico Milano. Power Flow Analysis under Uncertainty using Symmetric Fuzzy Arithmetic. PES General Meeting 2014 | Conference & Exposition, Jul 2014, National Harbor, MD, United States. pp.1-5, ⟨10.1109/PESGM.2014.6939274⟩. ⟨lirmm-01206373⟩
  • Manuel Marin, David Defour. FuzzyGPU : a fuzzy arithmetic library for GPU. PDP: Parallel, Distributed and Network-Based Processing, Feb 2014, Torino, Italy. pp.624-631, ⟨10.1109/PDP.2014.16⟩. ⟨lirmm-01206375⟩
  • Sylvain Collange, David Defour, Stef Graillat, Roman Iakymchuk. A Reproducible Accurate Summation Algorithm for High-Performance Computing. EX: Exascale Applied Mathematics Challenges and Opportunities, Jul 2014, Chicago, United States. ⟨hal-01267825⟩
  • David Defour. Impact des schedulers sur la prédictibilité dans les GPU. ComPAS: Conférence en Parallélisme, Architecture et Système, Apr 2014, Neuchâtel, Suisse. ⟨hal-00951916⟩
  • David Defour, Manuel Marin. Regularity versus Load-Balancing on GPU for treefix computations. ICCS: International Conference on Computational Science, Jun 2013, Barcelone, Spain. pp.309-318. ⟨hal-00768293⟩
  • David Defour, Eric Petit. Températures, erreurs matérielles et GPU. ComPAS: Conférence en Parallélisme, Architecture et Système, Jan 2013, Grenoble, France. pp.1-11. ⟨hal-00785386⟩
  • Eric Petit, David Defour. GPUburn: A System to Test and Mitigate GPU Hardware Failures. Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS), Jul 2013, Samos, Greece. pp.263-270, ⟨10.1109/SAMOS.2013.6621133⟩. ⟨hal-00827588⟩
  • Mark Arnold, Sylvain Collange, David Defour. Implementing LNS using filtering units of GPUs. International Conference on Acoustics Speech and Signal Processing (ICASSP), Mar 2010, Dallas, TX, United States. pp.1542--1545, ⟨10.1109/ICASSP.2010.5495516⟩. ⟨hal-00423434⟩
  • Sylvain Collange, Yoginder Dandass, Marc Daumas, David Defour. Using Graphics Processors for Parallelizing Hash-based Data Carving. 42nd Hawaii International Conference on System Sciences, Jan 2009, Waikoloa, United States. 10 p. ⟨hal-00350962⟩
  • Sylvain Collange, David Defour, Yao Zhang. Dynamic detection of uniform and affine vectors in GPGPU computations. Euro-Par 2009, Aug 2009, Delft, Netherlands. pp.46-55, ⟨10.1007/978-3-642-14122-5_8⟩. ⟨hal-00396719⟩
  • Sylvain Collange, Marc Daumas, David Defour, David Parello. Étude comparée et simulation d'algorithmes de branchements pour le GPGPU. Toulouse'2009, Sep 2009, Toulouse, France. pp.10. ⟨hal-00397697v2⟩
  • Sylvain Collange, David Defour, Arnaud Tisserand. Power Consumption of GPUs from a Software Perspective. 9th International Conference on Computational Science, May 2009, Baton Rouge, Louisiana, United States. pp.914-923, ⟨10.1007/978-3-642-01970-8_92⟩. ⟨hal-00348672v2⟩
  • Sylvain Collange, Marc Daumas, David Defour, Régis Olivès. Fonctions élémentaires sur GPU exploitant la localité de valeurs. SYMPosium en Architectures nouvelles de machines, 2008, Fribourg, Suisse. 12p. ⟨hal-00202906⟩
  • Sylvain Collange, Jorge Flórez, David Defour. A GPU interval library based on Boost.Interval. 8th Conference on Real Numbers and Computers, Jul 2008, Santiago de Compostela, Spain. pp.61-71. ⟨hal-00263670v2⟩
  • Sylvain Collange, Marc Daumas, David Defour. Graphic processors to speed-up simulations for the design of high performance solar receptors. IEEE 18th International Conference Application-specific Systems, Architectures and Processors, 2007, Montréal, Canada. pp.377-382. ⟨hal-00135126v3⟩
  • Marc Daumas, Guillaume Da Graça, David Defour. Caractéristiques arithmétiques des processeurs graphiques. SympA: Symposium en Architecture de Machines, Oct 2006, Perpignan, France. pp.86-95. ⟨hal-00069622⟩
  • Marc Daumas, Guillaume Da Graça, David Defour. Caractéristiques Arithmétiques des Processeurs Graphiques. RenPar'17/SympA'2006/CFSE'5/JC'2006, 2006, Canet en Roussillon, France. pp.86-95. ⟨lirmm-00107323⟩
  • Guillaume Da Graçca, David Defour. Implementation of float-float operators on graphics hardware. Real Numbers and Computers 7, Jul 2006, Nancy, France. pp.23-32. ⟨hal-00021443⟩

Poster communications2 documents

  • Roman Iakymchuk, Stef Graillat, Sylvain Collange, David Defour. ExBLAS: Reproducible and Accurate BLAS Library. RAIM: Rencontres Arithmétiques de l’Informatique Mathématique, Apr 2015, Rennes, France. 7ème Rencontre Arithmétique de l'Informatique Mathématique, 2015, ⟨https://raim2015.inria.fr⟩. ⟨hal-01140280⟩
  • Hugues de Lassus Saint-Geniès, David Defour, Guillaume Revy. Error-free Tables for Trigonometric Function Evaluation. ARCHI: Architecture des systèmes matériels et logiciels embarqués, et méthodes de conception associées, Jun 2015, Lille, France. 8e édition de l’école thématique Archi, 2015, ⟨http://www.cristal.univ-lille.fr/archi15/⟩. ⟨lirmm-01273490⟩

Book sections3 documents

Preprints, Working Papers, ...6 documents

  • David Defour. FP-ANR: A representation format to handle floating-point cancellation at run-time. 2017. ⟨lirmm-01549601v3⟩
  • Sylvain Collange, David Defour, Stef Graillat, Roman Iakymchuk. Numerical Reproducibility for the Parallel Reduction on Multi- and Many-Core Architectures. 2015. ⟨hal-00949355v4⟩
  • Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat. Reproducible and Accurate Matrix Multiplication for GPU Accelerators. 2015. ⟨hal-01102877⟩
  • Manuel Marin, David Defour, Federico Milano. Linear circuit analysis based on parallel asynchronous fixed-point method. 2015. ⟨hal-01142496⟩
  • Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat. Reproducible Triangular Solvers for High-Performance Computing. 2015. ⟨hal-01116588v2⟩
  • Sylvain Collange, David Defour, David Parello. Barra, a Parallel Functional GPGPU Simulator. 2009. ⟨hal-00359342v4⟩

Reports13 documents

  • Manuel Marin, David Defour, Federico Milano. An efficient midpoint-radius representation format to deal with symmetric fuzzy numbers. [Research Report] DALI - UPVD/LIRMM, UCD. 2015. ⟨hal-01140485⟩
  • David Defour. Impacting predictability of GPU's. 2014. ⟨hal-00951920v2⟩
  • David Defour, Manuel Marin. FuzzyGPU: a fuzzy arithmetic library for GPU. [Research Report] LIRMM. 2013. ⟨hal-00856617v2⟩
  • Michael François, David Defour. A Pseudo-Random Bit Generator Using Three Chaotic Logistic Maps. [Research Report] LIRMM (UM, CNRS). 2013. ⟨hal-00785380⟩
  • David Defour. Accuracy of a Maximum Likelihood Phylogeny Reconstruction. [Research Report] 010030, LIRMM. 2010. ⟨hal-00726409⟩
  • Catherine Daramy-Loirat, David Defour, Florent de Dinechin, Matthieu Gallet, Nicolas Gast, et al.. CR-LIBM A library of correctly rounded elementary functions in double-precision. [Research Report] LIP,. 2006. ⟨ensl-01529804⟩
  • Florent de Dinechin, David Defour, Christoph Lauter. Fast correct rounding of elementary functions in double precision using double-extended arithmetic. [Research Report] RR-5137, LIP RR-2004-10, INRIA, LIP. 2004. ⟨inria-00071446⟩
  • David Defour, Guillaume Hanrot, Vincent Lefèvre, Jean-Michel Muller, Nathalie Revol, et al.. Proposal for a Standardization of Mathematical Function Implementation in Floating-Point Arithmetic. [Research Report] RR-5406, INRIA. 2004. ⟨inria-00071249⟩
  • David Defour, Bernard Goossens. Implémentation de l'opérateur ADD2. 2004. ⟨hal-00662684⟩
  • David Defour. Collapsing floating-point operations. 2004. ⟨hal-00662679⟩
  • David Defour, Florent de Dinechin, Jean-Michel Muller. A new scheme for table-based evaluation of functions. [Research Report] RR-4637, LIP RR-2002-45, INRIA, LIP. 2002. ⟨inria-00071948⟩
  • David Defour, Florent de Dinechin, Jean-Michel Muller. Correctly Rounded Exponential Function in Double Precision Arithmetic. [Research Report] RR-4231, INRIA. 2001. ⟨inria-00072387⟩
  • David Defour, Peter Kornerup, Jean-Michel Muller, Nathalie Revol. A New Range Reduction Algorithm. [Research Report] RR-4267, LIP RR-2001-33, INRIA, LIP. 2001. ⟨inria-00072320⟩

Theses1 document

  • David Defour. Fonctions élémentaires : algorithmes et implémentations efficaces pour l'arrondi correct en double précision. Modélisation et simulation. Ecole normale supérieure de lyon - ENS LYON, 2003. Français. ⟨tel-00006022⟩

Habilitation à diriger des recherches1 document

  • David Defour. Contribution au calcul sur GPU: considérations arithmétiques et architecturales. Architectures Matérielles [cs.AR]. Université de Perpignan, 2014. ⟨tel-01206379⟩