-/*! \page index
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-\section overview Overview
-
-SimGrid is a toolkit that provides core functionalities for the simulation
-of distributed applications in heterogeneous distributed environments.
-The specific goal of the project is to facilitate research in the area of
-distributed and parallel application scheduling on distributed computing
-platforms ranging from simple network of workstations to Computational
-Grids.
-
-\section people People
-
-The authors of SimGrid are:
-
-\author Henri Casanova <casanova@cs.ucsd.edu>
-\author Arnaud Legrand <arnaud.legrand@imag.fr>
-\author Martin Quinson <martin.quinson@tuxfamily.org>
-
-\section intro Available Softwares
-
-The SimGrid toolkit is composed of different modules :
-
-\li XBT (eXtensive Bundle of Tools) is a portable library with many
- convenient portable datastructures (vectors, hashtables, heap,
- contexts ...). Most other SimGrid modules rely on it.
-
-\li SURF provides the core functionnalities to simulate a virtual
- platform. It is very low-level and is not intended to be used as
- such but rather to serve as a basis for higher-level simulators
- (like MSG, GRAS, SMPI, ...). It relies on a fast max min linear
- solver.
-
-\li MSG is a simulator built using the previous modules. It aims at
- being realistic and is application-oriented. It is the software layer
- of choice for building simulation with multiple scheduling agents.
-
-\li GRAS (<em>not functionnal yet</em>) is an ongoing project to emulate virtual virtual platforms
- through SURF. As a consequence a code developped using the GRAS
- framework is able to run as well in the real-world as in the
- simulator. The resulting code is very portable and highly interoperable while
- remaining very efficient. Even if you do not plan to run your code for real,
- you may want to switch to GRAS if you intend to use MSG in a very intensive way
- (e.g. for simulating a peer-to-peer environment).
-
-\li SMPI (<em>not functionnal yet</em>) is an ongoing project to enable MPI code to run on top of a
- virtual platform through SURF. It follows the same principle as
- the ones used in GRAS but is specific to MPI applications.
-
-The section \ref publications contains links to papers that provide
-additional details on the project as well as validation and
-experimental results.
-
-The software can be downloaded from <a href="http://gcl.ucsd.edu/SimGrid/dl/">here</a>.
-
-\section install Installation
-
-Simply type
- \li <tt>./configure</tt>
- \li <tt>make all install</tt>
-
-If you are not familiar with compiling C files under UNIX and using
-libraries, you will find some more informations in Section \ref
-faq.
-
-\section documentation API Documentation
-
-The API of all different modules is described in \ref SimGrid_API.
-
-See \ref SimGrid_examples for an introduction on the way to use these modules.
-
-\section users_contributers Users / Contributers
-
-\subsection contributers Contributers
-
- \li Loris Marchal: wrote the new algorithm for simulation TCP
- bandwidth-sharing.
- \li Julien Lerouge : wrote a XML parser for ENV descriptions and
- helped for the general design during a 4 month period (march-june 2002)
- in the LIP.
- \li Clément Menier and Marc Perache : wrote a first prototype of
- the MSG interface during a project at ENS-Lyon (jan 2002).
- \li Dmitrii Zagorodnov : wrote some parts of the first version
- of SimGrid (1999).
-
-\subsection mailinglist User Mailing List
-
- We have a <a href=https://listes.ens-lyon.fr/wws/info/simgrid2-users> mailing list for
- SimGrid users</a>.<p>
-
-\section publications Publications
-
-\subsection simulation About simulation
-
-\li <b>Scheduling Distributed Applications: the
- SimGrid Simulation Framework</b>\n
- by <em>Henri Casanova and Arnaud Legrand and Loris Marchal</em>\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
- 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 <b>A Network Model for Simulation of Grid Application</b>\n
- by <em>Henri Casanova and Loris Marchal</em>\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 <b>MetaSimGrid : Towards realistic scheduling simulation of
- distributed applications</b>\n
- by <em>Arnaud Legrand and Julien Lerouge</em>\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 <b>SimGrid: A Toolkit for the Simulation of Application
- Scheduling</b>\n
- by <em>Henri Casanova</em>\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
+Currently, the documentation contains 3 main sections:
+<ul>
+ <li><h2><a href="../user_guide/html/index.html">SimGrid User Guide</a></h2></li>
+ <li><h2><a href="../ref_guide/html/index.html">SimGrid Reference Manual</a>.</h2></li>
+ <li><h2>You can also retrieve tutorials from <a href="http://simgrid.gforge.inria.fr/faq.html">here</a>.</h2></li>
+</ul>
+\endhtmlonly
+Other information sources:
+ - The official webpage is <a href="http://simgrid.gforge.inria.fr/">simgrid.gforge.inria.fr</a>.
+ - The Frequently Asked Questions are <a href="http://simgrid.gforge.inria.fr/faq.html">here</a>.
+ - The development webpage is <a href="https://gforge.inria.fr/projects/simgrid//">gforge.inria.fr/projects/simgrid</a>.
+ - The user mailing list is <simgrid-user@lists.gforge.inria.fr>
+ - The SimGrid software package can be downloaded from <a href="http://simgrid.gforge.inria.fr/download.php">here</a>.
-\subsection research Papers using SimGrid results
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+<a href="http://creativecommons.org/licenses/LGPL/2.1/"><img alt="CC-GNU LGPL" border="0" src="http://creativecommons.org/images/public/cc-LGPL-a.png" /></a>
+</center>
+\endhtmlonly
-\li <b>Optimal algorithms for scheduling divisible workloads on
- heterogeneous systems</b>\n
- by <em>Olivier Beaumont and Arnaud Legrand and Yves Robert</em>\n
- In this paper, we discuss several algorithms for scheduling
- divisible loads on heterogeneous systems. Our main contributions
- are (i) new optimality results for single-round algorithms and (ii)
- the design of an asymptotically optimal multi-round algorithm. This
- multi-round algorithm automatically performs resource selection, a
- difficult task that was previously left to the user. Because it is
- periodic, it is simpler to implement, and more robust to changes in
- the speeds of processors or communication links. On the theoretical
- side, to the best of our knowledge, this is the first published
- result assessing the absolute performance of a multi-round
- algorithm. On the practical side, extensive simulations reveal
- that our multi-round algorithm outperforms existing solutions on a
- large variety of platforms, especially when the
- communication-to-computation ratio is not very high (the difficult
- case).\n
- ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-36.ps.gz
-\li <b>On-line Parallel Tomography</b>\n
- by <em>Shava Smallen</em>\n
- Masters Thesis, UCSD, May 2001
-\li <b>Applying Scheduling and Tuning to On-line Parallel Tomography </b>\n
- by <em>Shava Smallen, Henri Casanova, Francine Berman</em>\n
- in Proceedings of Supercomputing 2001
-\li <b>Heuristics for Scheduling Parameter Sweep applications in
- Grid environments</b>\n
- by <em>Henri Casanova, Arnaud Legrand, Dmitrii Zagorodnov and
- Francine Berman</em>\n
- in Proceedings of the 9th Heterogeneous Computing workshop
- (HCW'2000), pp349-363.
*/
