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Bibliography

Major publications by the team in recent years
  • 1F. Courty, A. Dervieux, B. Koobus, L. Hascoët.

    Reverse automatic differentiation for optimum design: from adjoint state assembly to gradient computation, in: Optimization Methods and Software, 2003, vol. 18, no 5, pp. 615-627.
  • 2B. Dauvergne, L. Hascoët.

    The Data-Flow Equations of Checkpointing in reverse Automatic Differentiation, in: International Conference on Computational Science, ICCS 2006, Reading, UK, 2006.
  • 3D. Goldberg, S. H. K. Narayanan, L. Hascoët, J. Utke.

    An optimized treatment for algorithmic differentiation of an important glaciological fixed-point problem, in: Geoscientific Model Development, 2016, vol. 9, no 5, 27 p.

    https://hal.inria.fr/hal-01413295
  • 4L. Hascoët.

    Adjoints by Automatic Differentiation, in: Advanced data assimilation for geosciences, Oxford University Press, 2014.

    https://hal.inria.fr/hal-01109881
  • 5L. Hascoët, U. Naumann, V. Pascual.

    “To Be Recorded” Analysis in Reverse-Mode Automatic Differentiation, in: Future Generation Computer Systems, 2004, vol. 21, no 8.
  • 6L. Hascoët, J. Utke, U. Naumann.

    Cheaper Adjoints by Reversing Address Computations, in: Scientific Programming, 2008, vol. 16, no 1, pp. 81–92.
  • 7L. Hascoët, M. Vázquez, B. Koobus, A. Dervieux.

    A Framework for Adjoint-based Shape Design and Error Control, in: Computational Fluid Dynamics Journal, 2008, vol. 16, no 4, pp. 454-464.
  • 8L. Hascoët, V. Pascual.

    The Tapenade Automatic Differentiation tool: Principles, Model, and Specification, in: ACM Transactions On Mathematical Software, 2013, vol. 39, no 3.

    http://dx.doi.org/10.1145/2450153.2450158
  • 9L. Hascoët, J. Utke.

    Programming language features, usage patterns, and the efficiency of generated adjoint code, in: Optimization Methods and Software, 2016, vol. 31, pp. 885–903. [ DOI : 10.1080/10556788.2016.1146269 ]

    https://hal.inria.fr/hal-01413332
  • 10J. C. Hueckelheim, L. Hascoët, J.-D. Müller.

    Algorithmic differentiation of code with multiple context-specific activities, in: ACM Transactions on Mathematical Software, 2016.

    https://hal.inria.fr/hal-01413321
Publications of the year

Articles in International Peer-Reviewed Journals

  • 11E. Itam, S. F. Wornom, B. Koobus, A. Dervieux.

    A Volume-agglomeration multirate time advancing for high Reynolds number flow simulation, in: International Journal for Numerical Methods in Fluids, 2019, vol. 89, no 8, pp. 326-341. [ DOI : 10.1002/fld.4702 ]

    https://hal.inria.fr/hal-01928223
  • 12P. Mohanamuraly, L. Hascoët, J.-D. Müller.

    Seeding and adjoining zero-halo partitioned parallel scientific codes, in: Optimization Methods and Software, April 2019, pp. 1-20. [ DOI : 10.1080/10556788.2019.1591404 ]

    https://hal.inria.fr/hal-02368107

International Conferences with Proceedings

  • 13E. Itam, S. F. Wornom, B. Koobus, A. Dervieux.

    Hybrid versus pure-les models comparison for subcritical cylinder flows, in: DLES11 2017 - ERCOFTAC Workshop Direct and Large-Eddy Simulation 11, Pisa, Italy, M. Salvetti, V. Armenio, J. Fröhlich, B. Geurts, H. Kuerten (editors), ERCOFTAC Series, Springer, Cham, 2019, vol. 25, pp. 445-451. [ DOI : 10.1007/978-3-030-04915-7_59 ]

    https://hal.inria.fr/hal-01655171
References in notes
  • 14A. Aho, R. Sethi, J. Ullman.

    Compilers: Principles, Techniques and Tools, Addison-Wesley, 1986.
  • 15I. Attali, V. Pascual, C. Roudet.

    A language and an integrated environment for program transformations, Inria, 1997, no 3313.

    http://hal.inria.fr/inria-00073376
  • 16A. Belme, F. Alauzet, A. Dervieux.

    An a priori anisotropic Goal-Oriented Error Estimate for Viscous Compressible Flow and Application to Mesh Adaptation, in: J. Comp. Phys., 2019, pp. 1051-1088.

    https://hal.inria.fr/hal-01927113
  • 17B. Christianson.

    Reverse accumulation and implicit functions, in: Optimization Methods and Software, 1998, vol. 9, no 4, pp. 307–322.
  • 18D. Clément, J. Despeyroux, L. Hascoët, G. Kahn.

    Natural semantics on the computer, in: Proceedings, France-Japan AI and CS Symposium, ICOT, 1986, pp. 49-89, Also, Information Processing Society of Japan, Technical Memorandum PL-86-6. Also Inria research report # 416.

    http://hal.inria.fr/inria-00076140
  • 19P. Cousot.

    Abstract Interpretation, in: ACM Computing Surveys, 1996, vol. 28, no 1, pp. 324-328.
  • 20B. Creusillet, F. Irigoin.

    Interprocedural Array Region Analyses, in: International Journal of Parallel Programming, 1996, vol. 24, no 6, pp. 513–546.
  • 21A. Dervieux, E. Gauci, L. Frazza, A. Belme, A. Carabias, A. Loseille, F. Alauzet.

    Mesh adaptation for k-exact CFD approximations, in: Numerical Methods for Flows, FEF 2017 Selected Contributions, 2020, Lecture Notes in Computational Science and Engineering, Springer.

    https://hal.inria.fr/hal-01927145
  • 22L. Frazza, A. Loseille, F. Alauzet, A. Dervieux.

    Nonlinear corrector for RANS equations, in: Int. J. Numer. Meth. Fluids, 2019, no 11, pp. 567-586.

    https://hal.inria.fr/hal-01962171
  • 23E. Gauci, A. Belme, A. Carabias, A. Loseille, F. Alauzet, A. Dervieux.

    A priori error-based mesh adaptation in CFD, International Press, 2019, Methods and Applications of Analysis.

    https://hal.inria.fr/hal-01928249
  • 24J. Gilbert.

    Automatic differentiation and iterative processes, in: Optimization Methods and Software, 1992, vol. 1, pp. 13–21.
  • 25M.-B. Giles.

    Adjoint methods for aeronautical design, in: Proceedings of the ECCOMAS CFD Conference, 2001.
  • 26A. Griewank, C. Faure.

    Reduced Gradients and Hessians from Fixed Point Iteration for State Equations, in: Numerical Algorithms, 2002, vol. 30(2), pp. 113–139.
  • 27A. Griewank, A. Walther.

    Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation, 2nd, SIAM, Other Titles in Applied Mathematics, 2008.
  • 28L. Hascoët.

    Transformations automatiques de spécifications sémantiques: application: Un vérificateur de types incremental, Université de Nice Sophia-Antipolis, 1987.
  • 29P. Hovland, B. Mohammadi, C. Bischof.

    Automatic Differentiation of Navier-Stokes computations, Argonne National Laboratory, 1997, no MCS-P687-0997.
  • 30E. Larour, J. Utke, B. Csatho, A. Schenk, H. Seroussi, M. Morlighem, E. Rignot, N. Schlegel, A. Khazendar.

    Inferred basal friction and surface mass balance of the Northeast Greenland Ice Stream using data assimilation of ICESat (Ice Cloud and land Elevation Satellite) surface altimetry and ISSM (Ice Sheet System Model), in: Cryosphere, 2014, vol. 8, no 6, pp. 2335-2351. [ DOI : 10.5194/tc-8-2335-2014 ]

    http://www.the-cryosphere.net/8/2335/2014/
  • 31F.-X. Le Dimet, O. Talagrand.

    Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects, in: Tellus, 1986, vol. 38A, pp. 97-110.
  • 32B. Mohammadi.

    Practical application to fluid flows of automatic differentiation for design problems, in: Von Karman Lecture Series, 1997.
  • 33N. Rostaing.

    Différentiation Automatique: application à un problème d'optimisation en météorologie, université de Nice Sophia-Antipolis, 1993.
  • 34R. Rugina, M. Rinard.

    Symbolic Bounds Analysis of Pointers, Array Indices, and Accessed Memory Regions, in: Proceedings of the ACM SIGPLAN'00 Conference on Programming Language Design and Implementation, ACM, 2000.


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