X-Git-Url: http://info.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/2ec2fb8f0e24bc6201d2b6d5d82aafaf69a004e7..87761c2a8db8f783a12feb505d9106e2fd154e56:/doc/publis.doc diff --git a/doc/publis.doc b/doc/publis.doc index 05cd746f78..130e6d119b 100644 --- a/doc/publis.doc +++ b/doc/publis.doc @@ -1,153 +1,86 @@ -/*! \page publis Publications - -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. - -\subsection pub_simulation About simulation - -\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 +/*! \page publis Reference publications about SimGrid + + +When citing SimGrid, the prefered reference paper is SimGrid: a +Generic Framework for Large-Scale Distributed Experimentations. + +\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. - - -\li A Network Model for Simulation of Grid Application\n - by Henri Casanova and Loris Marchal\n - \anchor paper_tcp - In this work we investigate network models that can be - potentially employed in the simulation of scheduling algorithms for - distributed computing applications. We seek to develop a model of TCP - communication which is both high-level and realistic. Previous research - works show that accurate and global modeling of wide-area networks, such - as the Internet, faces a number of challenging issues. However, some - global models of fairness and bandwidth-sharing exist, and can be link - withthe behavior of TCP. Using both previous results and simulation (with - NS), we attempt to understand the macroscopic behavior of - TCP communications. We then propose a global model of the network for the - Grid platform. We perform partial validation of this model in - simulation. The model leads to an algorithm for computing - bandwidth-sharing. This algorithm can then be implemented as part of Grid - application simulations. We provide such an implementation for the - SimGrid simulation toolkit.\n - ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-40.ps.gz - - -\li MetaSimGrid : Towards realistic scheduling simulation of - distributed applications\n - by Arnaud Legrand and Julien Lerouge\n - Most scheduling problems are already hard on homogeneous - platforms, they become quite intractable in an heterogeneous - framework such as a metacomputing grid. In the best cases, a - guaranteed heuristic can be found, but most of the time, it is - not possible. Real experiments or simulations are often - involved to test or to compare heuristics. However, on a - distributed heterogeneous platform, such experiments are - technically difficult to drive, because of the genuine - instability of the platform. It is almost impossible to - guarantee that a platform which is not dedicated to the - experiment, will remain exactly the same between two tests, - thereby forbidding any meaningful comparison. Simulations are - then used to replace real experiments, so as to ensure the - reproducibility of measured data. A key issue is the - possibility to run the simulations against a realistic - environment. The main idea of trace-based simulation is to - record the platform parameters today, and to simulate the - algorithms tomorrow, against the recorded data: even though it - is not the current load of the platform, it is realistic, - because it represents a fair summary of what happened - previously. A good example of a trace-based simulation tool is - SimGrid, a toolkit providing a set of core abstractions and - functionalities that can be used to easily build simulators for - specific application domains and/or computing environment - topologies. Nevertheless, SimGrid lacks a number of convenient - features to craft simulations of a distributed application - where scheduling decisions are not taken by a single - process. Furthermore, modeling a complex platform by hand is - fastidious for a few hosts and is almost impossible for a real - grid. This report is a survey on simulation for scheduling - evaluation purposes and present MetaSimGrid, a simulator built - on top of SimGrid.\n - ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-28.ps.gz - -\li SimGrid: A Toolkit for the Simulation of Application - Scheduling\n - by Henri Casanova\n - Advances in hardware and software technologies have made it - possible to deploy parallel applications over increasingly large - sets of distributed resources. Consequently, the study of - scheduling algorithms for such applications has been an active area - of research. Given the nature of most scheduling problems one must - resort to simulation to effectively evaluate and compare their - efficacy over a wide range of scenarios. It has thus become - necessary to simulate those algorithms for increasingly complex - distributed, dynamic, heterogeneous environments. In this paper we - present SimGrid, a simulation toolkit for the study of scheduling - algorithms for distributed application. This paper gives the main - concepts and models behind SimGrid, describes its API and - highlights current implementation issues. We also give some - experimental results and describe work that builds on SimGrid's - functionalities.\n - http://grail.sdsc.edu/papers/simgrid_ccgrid01.ps.gz - -\subsection pub_research Papers using SimGrid results - -\li A study of meta-scheduling architectures for high throughput - computing: Pull vs. Push\n - by Vincent Garonne, Andrei Tsaregorodtsev, and Eddy Caron \n - Proceedings of 4th Internationnal Symposium on Parallel and - Distributed Computing Job Scheduling Strategies for Parallel - Processing (ISPDC'05), July 2005.\n - Preliminary version in http://marwww.in2p3.fr/~garonne/garonne-meta.pdf - -\li Exploiting Replication and Data Reuse to Efficiently Schedule - Data-intensive Applications on Grids\n - by E. Santos-Neto, W. Cirne, F. Brasileiro, A. Lima.\n - Proceedings of 10th Job Scheduling Strategies for Parallel Processing, June 2004.\n - http://www.lsd.ufcg.edu.br/~elizeu/articles/jsspp.v6.pdf - -\li Optimal algorithms for scheduling divisible workloads on - heterogeneous systems\n - by Olivier Beaumont and Arnaud Legrand and Yves Robert\n - in Proceedings of the 17th International Parallel and Distributed Processing Symposium (IPDPS'03).\n - Preliminary version on ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-36.ps.gz - -\li On-line Parallel Tomography\n - by Shava Smallen\n - Masters Thesis, UCSD, May 2001 -\li Applying Scheduling and Tuning to On-line Parallel Tomography \n - by Shava Smallen, Henri Casanova, Francine Berman\n - in Proceedings of Supercomputing 2001 -\li Heuristics for Scheduling Parameter Sweep applications in - Grid environments\n - by Henri Casanova, Arnaud Legrand, Dmitrii Zagorodnov and - Francine Berman\n - in Proceedings of the 9th Heterogeneous Computing workshop - (HCW'2000), pp349-363. -*/ \ No newline at end of file + 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 + +\verbatim +@InProceedings{simgrid, + author = {Casanova, Henri and Legrand, Arnaud and Quinson, Martin}, + title = {{SimGrid: a Generic Framework for Large-Scale Distributed Experiments}}, + booktitle = {10th IEEE International Conference on Computer Modeling and Simulation}, + year = 2008, + month = mar +} +\endverbatim + +\section publis_others Other publications + +A lot of other papers where published about SimGrid. The list is +splited in 3 pages (also accessible from the navbar on top of this page): + - \ref publis_core\n + This section contains papers describing some sub-parts of SimGrid, + or references superseeded by the one given above. + - \ref publis_extern\n + SimGrid is used by an ever growing scientific community. This + section lists all the papers resulting of works in which the core + SimGrid team were not involved. + - \ref publis_intra\n + This section lists the paper co-signed by at least one of the core + team member, and using SimGrid as a tool (and not studying SimGrid + itself). + +\section publis_count Amount of published papers using SimGrid results + +\htmlinclude publis_count.html + +\page publis_core Publications about the SimGrid framework + +\htmlinclude publis_core_bib.html + +\page publis_extern Papers that use SimGrid-generated results (not counting our owns) + +This list is a selection of articles. We list only papers written by people +external to the development group, but we also use our tool ourselves (see +next section). + +\htmlinclude publis_extern_bib.html + +\page publis_intra Our own papers that use SimGrid-generated results + +This list is a selection of the articles we have written that used results +generated by SimGrid. + +\htmlinclude publis_intra_bib.html + + +*/