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File Date Author Commit
 alexyacc 2014-03-31 pallamidessi pallamidessi [2fb93f] Fix some warning and merge windows change
 boost 2014-03-30 pallamidessi pallamidessi [0d2086] Easea now work again on window, although slowly...
 compiler 2014-05-21 pallamidessi pallamidessi [84a6ce] Fix a case where the generated deserialization ...
 dev 2011-09-14 Frédéric Krüger Frédéric Krüger [e89784] Revision
 doc 2014-05-14 pallamidessi pallamidessi [ab639b] Cont'd doc
 easeagrapher 2011-09-14 Frédéric Krüger Frédéric Krüger [93f13b] Ajout de grapher java
 examples 2014-06-03 pallamidessi pallamidessi [2b3730] Cigtab test (cmaes-test) now use correct compil...
 libeasea 2014-05-16 pallamidessi pallamidessi [f0ea30] Add openMP support
 old 2009-07-17 kruger kruger [39b21c] Nouvelle Version avec lib
 tpl 2014-06-03 Julien Gamba Julien Gamba [cdb0b9] Add back the globals variables OFFSPRING_SIZE, ...
 CMakeLists.txt 2014-05-16 pallamidessi pallamidessi [f0ea30] Add openMP support
 INSTALL.txt 2014-04-15 pallamidessi pallamidessi [232e56] Add software requirements to the README
 Makefile 2014-05-09 pallamidessi pallamidessi [541b0b] Clean a bit the directories and the compiler ha...
 Makefile.old 2014-05-09 pallamidessi pallamidessi [541b0b] Clean a bit the directories and the compiler ha...
 README.md 2014-06-03 pallamidessi pallamidessi [28e0aa] Add github mirroring instructions
 install.sh 2014-04-03 pallamidessi pallamidessi [b6a141] Minor aesthetic change to the install script an...

Read Me

The EASEA-CLOUD platform

Overview

EASEA and EASEA-CLOUD are Free Open Source Software (under GNU Affero v3 General Public License) developed by the SONIC (Stochastic Optimisation and Nature Inspired Computing) group of the BFO team at Université de Strasbourg. Through the Strasbourg Complex Systems Digital Campus, the platforms are shared with the UNESCO CS-DC UniTwin and E-laboratory on Complex Computational Ecosystems (ECCE).

EASEA (EAsy Specification of Evolutionary Algorithms) is an Artificial Evolution platform that allows scientists with only basic skills in computer science to implement evolutionary algorithms and to exploit the massive parallelism of many-core architectures in order to optimize virtually any real-world problems (continous, discrete, combinatorial, mixed and more (with Genetic Programming)), typically allowing for speedups up to x500 on a $3,000 machine, depending on the complexity of the evaluation function of the inverse problem to be solved.

Then, for very large problems, EASEA can also exploit computational ecosystems as it can parallelize (using an embedded island model) over loosely coupled heterogenous machines (Windows, Linux or Macintosh, with or without GPGPU cards, provided that they have internet access) a grid of computers or a Cloud.

Features

  • Runs can be distributed over cluster of homogeneous AND heterogeneous machines.
  • Distribution can be done locally on the same machine or over the internet (using a embedded island model).
  • Parallelization over GPGPU cards leading to massive speedup (x100 to x1000).
  • C++ description language.

Github mirror

To mirror this repositories on the github one, please add to .git/config:
[remote "github"]
url = git@github.com:EASEA/easea.git
mirror = true

Add after pushing, do "git push github" manually or add a hook.

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