X-Git-Url: http://info.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/1e23f483facad7896791e5428ab9e6c9e3dad01a..8d9f9aaf15fb6376d19932bee8adf9dd53151a1c:/doc/publis.doc diff --git a/doc/publis.doc b/doc/publis.doc index 5b2958b13b..c9a8f100a0 100644 --- a/doc/publis.doc +++ b/doc/publis.doc @@ -1,51 +1,37 @@ /*! \page publis Reference publications about SimGrid -When citing SimGrid, the prefered reference paper is Scheduling -Distributed Applications: the SimGrid Simulation Framework, even if it's -a bit old now. We are actively working on improving this. +When citing SimGrid, the prefered reference paper is SimGrid: a +Generic Framework for Large-Scale Distributed Experimentations. -\li Scheduling Distributed Applications: the - SimGrid Simulation Framework\n - by Henri Casanova and Arnaud Legrand and Loris Marchal\n - Proceedings of the third IEEE International Symposium - on Cluster Computing and the Grid (CCGrid'03)\n - Since the advent of distributed computer systems an active field - of research has been the investigation of scheduling strategies - for parallel applications. The common approach is to employ - scheduling heuristics that approximate an optimal - schedule. Unfortunately, it is often impossible to obtain - analytical results to compare the efficacy of these heuristics. - One possibility is to conducts large numbers of back-to-back - experiments on real platforms. While this is possible on - tightly-coupled platforms, it is infeasible on modern distributed - platforms (i.e. Grids) as it is labor-intensive and does not - enable repeatable results. The solution is to resort to - simulations. Simulations not only enables repeatable results but - also make it possible to explore wide ranges of platform and +\li SimGrid: a Generic Framework for Large-Scale Distributed + Experimentations\n + by Henri Casanova, Arnaud Legrand and Martin Quinson\n + Proceedings of the 10th IEEE International Conference on Computer + Modelling and Simulation (UKSIM/EUROSIM'08)\n + Distributed computing is a very broad and active research area + comprising fields such as cluster computing, computational + grids, desktop grids and peer-to-peer (P2P) systems. + Unfortunately, it is often impossible to obtain theoretical or + analytical results to compare the performance of algorithms + targeting such systems. One possibility is to conduct large + numbers of back-to-back experiments on real platforms. While + this is possible on tightly-coupled platforms, it is infeasible + on modern distributed platforms as experiments are labor-intensive + and results typically not reproducible. Consequently, one must + resort to simulations, which enable reproducible results and also + make it possible to explore wide ranges of platform and application scenarios.\n - In this paper we present the SimGrid framework which enables the - simulation of distributed applications in distributed computing - environments for the specific purpose of developing and evaluating - scheduling algorithms. This paper focuses on SimGrid v2, which - greatly improves on the first version of the software with more - realistic network models and topologies. SimGrid v2 also enables - the simulation of distributed scheduling agents, which has become - critical for current scheduling research in large-scale platforms. - After describing and validating these features, we present a case - study by which we demonstrate the usefulness of SimGrid for - conducting scheduling research.\n - http://www-id.imag.fr/Laboratoire/Membres/Legrand_Arnaud/articles/simgrid2_CCgrid03.pdf - -Previous publication do not cover the GRAS part of the framework. So, if you -want to cite GRAS, please use this publication instead: - -\li Gras: A Research & Development Framework for Grid and P2P - Infrastructures\n - by Martin Quinson\n - Best paper of the 18th IASTED International Conference on - Parallel and Distributed Computing and Systems (PDCS 2006)\n - http://www.loria.fr/~quinson/articles/gras-iasted06.pdf + In this paper we describe the SimGrid framework, a + simulation-based framework for evaluating cluster, grid and P2P + algorithms and heuristics. This paper focuses on SimGrid v3, which + greatly improves on previous versions thanks to a novel and + validated modular simulation engine that achieves higher + simulation speed without hindering simulation accuracy. Also, two + new user interfaces were added to broaden the targeted research + community. After surveying existing tools and methodologies we + describe the key features and benefits of SimGrid.\n + http://www.loria.fr/~quinson/articles/SimGrid-uksim08.pdf \section publis_others Other publications @@ -67,11 +53,14 @@ splited in 3 pages (also accessible from the navbar on top of this page):
Year | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | ||
Year | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | +2008 | Total |
Amount of papers external to the core team | -- | - | - | 3 | 6 | 3 | 8 | 3 | - | - | - | 3 | 6 | 3 | 8 | 5 | +1 | 26 |
Amount of papers co-signed by one team member | -1 | 1 | 1 | 2 | 2 | - | 4 | 4 | 1 | 1 | 1 | 2 | 2 | - | 4 | 4 | +15 |