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#+TITLE: Chameleon: A dense linear algebra software for heterogeneous architectures
#+LANGUAGE:  en
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Chameleon is a C library providing parallel algorithms to perform
BLAS/LAPACK operations exploiting fully modern architectures.

Chameleon dense linear algebra software relies on sequential
task-based algorithms where sub-tasks of the overall algorithms are
submitted to a Runtime system. Such a system is a layer between the
application and the hardware which handles the scheduling and the
effective execution of tasks on the processing units. A Runtime system
such as [[http://starpu.gforge.inria.fr/][StarPU]] is able to manage automatically data transfers between
not shared memory area (CPUs-GPUs, distributed nodes).

This kind of implementation paradigm allows to design high performing
linear algebra algorithms on very different type of architecture:
laptop, many-core nodes, CPUs-GPUs, multiple nodes. For example,
Chameleon is able to perform a Cholesky factorization
(double-precision) at 80 TFlop/s on a dense matrix of order 400 000
(i.e. 4 min). Chameleon is a sub-project of [[http://icl.cs.utk.edu/morse/][MORSE]] specifically
dedicated to dense linear algebra.

* Get Chameleon

  To use last development states of Chameleon, please clone the master
  branch. Note that Chameleon contains a ~git submodule~ *morse_cmake*.
  To get sources please use these commands:

  #+begin_src sh
    # if git version >= 1.9
    git clone --recursive git@gitlab.inria.fr:solverstack/chameleon.git
    cd chameleon
    # else
    git clone git@gitlab.inria.fr:solverstack/chameleon.git
    cd chameleon
    git submodule init
    git submodule update
  #+end_src

  Last releases of Chameleon are hosted on the [[https://gforge.inria.fr/frs/?group_id=2884][gforge.inria.fr]] for
  now. Future releases will be available on this gitlab project.

* Documentation

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** User guide
   The user guide is available directly in the sources as emacs
   orgmode files, see :
   1) [[file:doc/orgmode/chapters/introduction.org][Introduction]]
   2) [[file:doc/orgmode/chapters/installing.org][Installing]]
   3) [[file:doc/orgmode/chapters/using.org][Using]]

** Source code documentation (doxygen)
   There is no up-to-date documentation of Chameleon.  We would like to
   provide a doxygen documentation hosted on [[https://about.gitlab.com/2016/04/07/gitlab-pages-setup/][gitlab]] in the
   future. Please refer to the section 2.1 of [[file:READMEDEV.org][READMEDEV]] to get
   information about the documentation generation.
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** For developers
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   Please refer to the [[file:READMEDEV.org][READMEDEV]] page.
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* Installation
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  Please refer to the [[file:doc/orgmode/chapters/installing.org][Installing]] page.
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* Get involved!
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** Mailing list

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   To contact the developers send an email to
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   [[mailto:morse-devel@lists.gforge.inria.fr][morse-devel@lists.gforge.inria.fr]]

** Contributions

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  [[file:CONTRIBUTING.org][CONTRIBUTING]]
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* Authors

 First, since the Chameleon library started as an extension of the
 PLASMA library to support multiple runtime systems, all developpers
 of the PLASMA library are developpers of the Chameleon library.

 The following people contributed to the development of Chameleon:
 * Emmanuel Agullo, PI
 * Olivier Aumage
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 * Cedric Castagnede
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 * Terry Cojean
 * Mathieu Faverge, PI
 * Nathalie Furmento
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 * Reazul Hoque
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 * Hatem Ltaief
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 * Gregoire Pichon
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 * Florent Pruvost, PI
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 * Marc Sergent
 * Guillaume Sylvand
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 * Samuel Thibault
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 * Stanimire Tomov
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 * Omar Zenati

 If we forgot your name, please let us know that we can fix that mistake.

* Citing Chameleon

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Feel free to use the following publications to reference Chameleon:

  * Original paper that initiated Chameleon and the principles:
    - Agullo, Emmanuel and Augonnet, Cédric and Dongarra, Jack and
      Ltaief, Hatem and Namyst, Raymond and Thibault, Samuel and Tomov,
      Stanimire, *Faster, Cheaper, Better -- a Hybridization Methodology
      to Develop Linear Algebra Software for GPUs*, /GPU Computing Gems/,
      [[https://hal.inria.fr/inria-00547847][First Online: 17 December 2010]].
  * Design of the QR algorithms:
    - Agullo, Emmanuel and Augonnet, Cédric and Dongarra, Jack and
      Faverge, Mathieu and Ltaief, Hatem and Thibault, Samuel an
      Tomov, Stanimire, *QR Factorization on a Multicore Node Enhanced
      with Multiple GPU Accelerators*, /25th IEEE International Parallel
      & Distributed Processing Symposium/, [[https://hal.inria.fr/inria-00547614][First Online: 16 December
      2010]].
  * Design of the LU algorithms:
    - Agullo, Emmanuel and Augonnet, Cédric and Dongarra, Jack and
      Faverge, Mathieu and Langou, Julien and Ltaief, Hatem and Tomov,
      Stanimire, *LU Factorization for Accelerator-based Systems*,
      /9th ACS/IEEE International Conference on Computer Systems and
      Applications (AICCSA 11)/, [[https://hal.inria.fr/hal-00654193][First Online: 21 December 2011]].
  * Regarding distributed memory:
    - Agullo, Emmanuel and Aumage, Olivier and Faverge, Mathieu and
      Furmento, Nathalie and Pruvost, Florent and Sergent, Marc and
      Thibault, Samuel, *Achieving High Performance on Supercomputers
      with a Sequential Task-based Programming Model*, /Research Report/,
      [[https://hal.inria.fr/hal-01332774][First Online: 16 June 2016]].
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* Licence

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  [[file:LICENCE.txt][LICENCE]]