chapitres.bib

@inbook{ViCo14,
  author = {Vialle, S. and Contassot-Vivier, S.},
  chapter = {Optimization methodology for Parallel Programming of Homogeneous or Hybrid Clusters},
  year = {2014},
  title = {Patterns for parallel programming on GPUs},
  publisher = {Saxe-Coburg Publications, Stirling, UK},
  optmonth = {},
  editor = {F. Magoules},
  isbn = {978-1-874672-57-9},
  url = {http://www.saxe-coburg.co.uk/pubs/future.htm},
  keywords = {deployment. ; message passing ; multithreading on multicore ; vectorization on GPU ; communication-computation overlapping ; computing kernel optimization},
  abstract = {This chapter proposes a study of the optimization process of parallel applications to be run on modern architectures (multi-core CPU nodes with GPUs). Different
                  optimization schemes are proposed for overlapping computations with communications, and for computation kernels. Development methodologies are introduced to
                  obtain different optimization degrees and specific criteria are defined to help developers find the most suited degree of optimization according to the considered
                  application and parallel system. According to our experience in industrial collaborations, we analyze both performance and code complexity increase. This last
                  point is an important issue, especially in the industry, as it directly impacts development and maintenance costs. Complete experiments are performed to evaluate
                  the different variants of a benchmark application that consists in a dense matrix product. In those experiments, different runtime parameters and cluster
                  configurations are tested. Then, the results are analyzed to evaluate the interest of the different optimization degrees as well as to validate the interest of
                  the proposed optimization methodology.}
}

@inbook{CoViGu13,
  url = {http://www.crcpress.com/product/isbn/9781466571624},
  chapter = {{Development methodologies for GPU and cluster of GPUs}},
  author = {Contassot-Vivier, Sylvain and Vialle, St{\'e}phane and Gustedt, Jens},
  abstract = {{This book chapter proposes to draw several development methodologies to obtain efficient codes in classical scientific applications. Those methodologies are based on the feedback from several research works involving GPUs, either alone in a single machine or in a cluster of machines. Indeed, our past collaborations with industries have allowed us to point out that in their economical context, they can adopt a parallel technology only if its implementation and maintenance costs are small according to the potential benefits (performance, accuracy,...). So, in such contexts, GPU programming is still regarded with some distance according to its specific field of applicability (SIMD/SIMT model) and its still higher programming complexity and maintenance. In the academic domain, things are a bit different but studies for efficiently integrating GPU computations in multi-core clusters with maximal overlapping of computations with communications and/or other computations, are still rare. For these reasons, the major aim of that chapter is to propose as simple as possible general programming patterns that can be followed or adapted in practical implementations of parallel scientific applications. Also, we propose in a third part, a prospect analysis together with a particular programming tool that is intended to ease multi-core GPU cluster programming.}},
  language = {Anglais},
  affiliation = {ALGORILLE - INRIA Nancy - Grand Est / LORIA , Georgia Tech - CNRS - UMI2958 , Laboratoire des sciences de l'ing{\'e}nieur, de l'informatique et de l'imagerie - ICube},
  title = {{Designing Scientific Applications on GPUs}},
  publisher = {Chapman \& Hall/CRC},
  editor = {Rapha{\"e}l Couturier },
  audience = {internationale },
  isbn = {978-1-4665-7162-4 },
  year = {2013},
  pages = {105-149}
}

@inbook{ChapNRJ2011,
  author = {Vialle, S. and Contassot-Vivier, S. and Jost, T.},
  editor = {Sanjay Ranka and Ishfag Ahmad},
  title = {Handbook of Energy-Aware and Green Computing},
  chapter = {Optimizing Computing and Energy Performances in Heterogeneous Clusters of CPUs and GPUs},
  publisher = {Chapman and Hall/CRC},
  year = {2012},
  url = {http://www.crcpress.com/product/isbn/9781466501164#},
  isbn = {9781466501164},
  series = {Computer \& Information Science Series},
  month = {Jan},
  pages = {761-793}
}

@inbook{ChapRNA2011,
  author = {Sauget, M. and Contassot-Vivier, S. and Salomon, M.},
  title = {Horizons in Computer Science Research},
  chapter = {Parallelization of neural network building and training: an original decomposition method},
  publisher = {Nova publishers},
  year = {2011},
  volume = {7},
  url = {https://www.novapublishers.com/catalog/product_info.php?products_id=31585},
  isbn = {978-1-61942-774-7},
  pages = {193-223}
}