1 /*! \page publis Reference publications about SimGrid
4 When citing SimGrid, the prefered reference paper is <i>Scheduling
5 Distributed Applications: the SimGrid Simulation Framework</i>, even if it's
6 a bit old now. We are actively working on improving this.
8 \li <b>Scheduling Distributed Applications: the
9 SimGrid Simulation Framework</b>\n
10 by <em>Henri Casanova and Arnaud Legrand and Loris Marchal</em>\n
11 Proceedings of the third IEEE International Symposium
12 on Cluster Computing and the Grid (CCGrid'03)\n
13 Since the advent of distributed computer systems an active field
14 of research has been the investigation of scheduling strategies
15 for parallel applications. The common approach is to employ
16 scheduling heuristics that approximate an optimal
17 schedule. Unfortunately, it is often impossible to obtain
18 analytical results to compare the efficacy of these heuristics.
19 One possibility is to conducts large numbers of back-to-back
20 experiments on real platforms. While this is possible on
21 tightly-coupled platforms, it is infeasible on modern distributed
22 platforms (i.e. Grids) as it is labor-intensive and does not
23 enable repeatable results. The solution is to resort to
24 simulations. Simulations not only enables repeatable results but
25 also make it possible to explore wide ranges of platform and
26 application scenarios.\n
27 In this paper we present the SimGrid framework which enables the
28 simulation of distributed applications in distributed computing
29 environments for the specific purpose of developing and evaluating
30 scheduling algorithms. This paper focuses on SimGrid v2, which
31 greatly improves on the first version of the software with more
32 realistic network models and topologies. SimGrid v2 also enables
33 the simulation of distributed scheduling agents, which has become
34 critical for current scheduling research in large-scale platforms.
35 After describing and validating these features, we present a case
36 study by which we demonstrate the usefulness of SimGrid for
37 conducting scheduling research.\n
38 http://www-id.imag.fr/Laboratoire/Membres/Legrand_Arnaud/articles/simgrid2_CCgrid03.pdf
40 Previous publication do not cover the GRAS part of the framework. So, if you
41 want to cite GRAS, please use this publication instead:
43 \li <b>Gras: A Research & Development Framework for Grid and P2P
45 by <em>Martin Quinson</em>\n
46 <b>Best paper</b> of the 18th IASTED International Conference on
47 Parallel and Distributed Computing and Systems (PDCS 2006)\n
48 http://www.loria.fr/~quinson/articles/gras-iasted06.pdf
50 \section publis_others Other publications
52 A lot of other papers where published about SimGrid. The list is
53 splited in 3 pages (also accessible from the navbar on top of this page):
55 This section contains papers describing some sub-parts of SimGrid,
56 or references superseeded by the one given above.
57 - \ref publis_extern\n
58 SimGrid is used by an ever growing scientific community. This
59 section lists all the papers resulting of works in which the core
60 SimGrid team were not involved.
62 This section lists the paper co-signed by at least one of the core
63 team member, and using SimGrid as a tool (and not studying SimGrid
66 \section publis_count Amount of published papers using SimGrid results
70 <tr><td>Year</td><td>2000</td><td>2001</td><td>2002</td><td>2003</td><td>2004</td><td>2005</td><td>2006</td><td>2007</td></tr>
71 <tr><td>Amount of papers external to the core team</td>
72 <td>-</td> <td>-</td> <td>-</td> <td>3</td> <td>6</td> <td>3</td> <td>8</td> <td>4</td></tr>
73 <tr><td>Amount of papers co-signed by one team member</td>
74 <td>1</td> <td>1</td> <td>1</td> <td>2</td> <td>2</td> <td>-</td> <td>4</td> <td>4</td></tr>
77 \page publis_core Other publications about the SimGrid framework
79 \li <b>Speed and Accuracy of Network Simulation in the SimGrid Framework</b>\n
80 by <em>K. Fujiwara, H. Casanova</em>\n
81 in Proceedings of the First International Workshop on Network Simulation Tools (NSTools), Nantes, France, October 2007.\n
82 http://navet.ics.hawaii.edu/~casanova/homepage/papers/fujiwara_nstool2007.pdf
84 \li <b>Cost and Accuracy of Packet-Level vs. Analytical Network Simulations: An Empirical Study</b>\n
85 by <em>K. Fujiwara</em>\n
86 <b>M.S. Thesis</b>, Dept. of Information and Computer Sciences, University of Hawai`i at Manoa, April 2007.\n
87 http://navet.ics.hawaii.edu/~casanova/homepage/theses/kayo_fujiwara_MS.pdf
89 \li <b>The SimGrid Project - Simulation and Deployment of Distributed Applications</b>\n
90 by <em>A. Legrand, M. Quinson, K. Fujiwara, H. Casanova</em>\n
91 <b>POSTER</b> in Proceedings of the IEEE International Symposium on High Performance Distributed Computing (HPDC-15), Paris, France, May 2006.\n
93 <a href="http://navet.ics.hawaii.edu/~casanova/homepage/papers/simgrid_hpdc06.pdf"><img src="poster_thumbnail.png" /></a>
95 http://navet.ics.hawaii.edu/~casanova/homepage/papers/simgrid_hpdc06.pdf
97 \li <b>A Network Model for Simulation of Grid Application</b>\n
98 by <em>Henri Casanova and Loris Marchal</em>\n
100 In this work we investigate network models that can be
101 potentially employed in the simulation of scheduling algorithms for
102 distributed computing applications. We seek to develop a model of TCP
103 communication which is both high-level and realistic. Previous research
104 works show that accurate and global modeling of wide-area networks, such
105 as the Internet, faces a number of challenging issues. However, some
106 global models of fairness and bandwidth-sharing exist, and can be link
107 withthe behavior of TCP. Using both previous results and simulation (with
108 NS), we attempt to understand the macroscopic behavior of
109 TCP communications. We then propose a global model of the network for the
110 Grid platform. We perform partial validation of this model in
111 simulation. The model leads to an algorithm for computing
112 bandwidth-sharing. This algorithm can then be implemented as part of Grid
113 application simulations. We provide such an implementation for the
114 SimGrid simulation toolkit.\n
115 ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-40.ps.gz
118 \li <b>MetaSimGrid : Towards realistic scheduling simulation of
119 distributed applications</b>\n
120 by <em>Arnaud Legrand and Julien Lerouge</em>\n
121 Most scheduling problems are already hard on homogeneous
122 platforms, they become quite intractable in an heterogeneous
123 framework such as a metacomputing grid. In the best cases, a
124 guaranteed heuristic can be found, but most of the time, it is
125 not possible. Real experiments or simulations are often
126 involved to test or to compare heuristics. However, on a
127 distributed heterogeneous platform, such experiments are
128 technically difficult to drive, because of the genuine
129 instability of the platform. It is almost impossible to
130 guarantee that a platform which is not dedicated to the
131 experiment, will remain exactly the same between two tests,
132 thereby forbidding any meaningful comparison. Simulations are
133 then used to replace real experiments, so as to ensure the
134 reproducibility of measured data. A key issue is the
135 possibility to run the simulations against a realistic
136 environment. The main idea of trace-based simulation is to
137 record the platform parameters today, and to simulate the
138 algorithms tomorrow, against the recorded data: even though it
139 is not the current load of the platform, it is realistic,
140 because it represents a fair summary of what happened
141 previously. A good example of a trace-based simulation tool is
142 SimGrid, a toolkit providing a set of core abstractions and
143 functionalities that can be used to easily build simulators for
144 specific application domains and/or computing environment
145 topologies. Nevertheless, SimGrid lacks a number of convenient
146 features to craft simulations of a distributed application
147 where scheduling decisions are not taken by a single
148 process. Furthermore, modeling a complex platform by hand is
149 fastidious for a few hosts and is almost impossible for a real
150 grid. This report is a survey on simulation for scheduling
151 evaluation purposes and present MetaSimGrid, a simulator built
153 ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-28.ps.gz
155 \li <b>SimGrid: A Toolkit for the Simulation of Application
157 by <em>Henri Casanova</em>\n
158 Advances in hardware and software technologies have made it
159 possible to deploy parallel applications over increasingly large
160 sets of distributed resources. Consequently, the study of
161 scheduling algorithms for such applications has been an active area
162 of research. Given the nature of most scheduling problems one must
163 resort to simulation to effectively evaluate and compare their
164 efficacy over a wide range of scenarios. It has thus become
165 necessary to simulate those algorithms for increasingly complex
166 distributed, dynamic, heterogeneous environments. In this paper we
167 present SimGrid, a simulation toolkit for the study of scheduling
168 algorithms for distributed application. This paper gives the main
169 concepts and models behind SimGrid, describes its API and
170 highlights current implementation issues. We also give some
171 experimental results and describe work that builds on SimGrid's
173 http://grail.sdsc.edu/papers/simgrid_ccgrid01.ps.gz
175 \page publis_extern Papers that use SimGrid-generated results (not counting our owns)
177 This list is a selection of articles. We list only papers written by people
178 external to the development group, but we also use our tool ourselves (see
182 - <b>Reactive Grid Scheduling of DAG Applications.</b>\n by
183 <em>I. Hernandez and M. Cole (UK)</em>. In Parallel and Distributed Computing and Networks, 2007.\n
184 http://www.actapress.com/PaperInfo.aspx?PaperID=29625
185 - <b>Scheduling Δ-Critical Tasks in Mixed-Parallel Applications on a National Grid</b>\n
186 by <em>Frédéric Suter</em>.\n
187 In 8th IEEE/ACM International Conference on Grid Computing (Grid 2007), Austin, TX, September 2007.
188 - <b>Brokering strategies in computational grids using stochastic
189 prediction models.</b>\n by <em>Vandy Berten and Bruno
190 Gaujal</em>. In Parallel Computing, vol. 33(4-5): 238-249, 2007.\n
191 http://dev.ulb.ac.be/sched/articles/PARCO.pdf
192 - <b>Managing Scheduling and Replication in the LHC Grid.</b>\n by
193 <em>Thomas Ferrandiz and Vania Marangozova</em>. In CoreGrid
194 Workshop on middleware, 2007.\n
197 - <b>Simbatch: an API for simulating and predicting the performance of parallel resources and batch systems.</b>\n
198 by <em>Jean-Sébastien Gay and Yves Caniou</em>\n
199 INRIA Research Report 6040, November 2006.\n
200 https://hal.inria.fr/inria-00115880
201 - <b>Simbatch : une API pour la simulation et la prédiction de performances de systèmes batch</b>\n
202 by <em>Jean-Sébastien Gay and Yves Caniou</em>.\n
203 In 17ème Rencontres Francophones du Parallélisme, des Architectures et des Systèmes, RenPar'17.\n
204 October 4-6, Perpignan, France
205 - <b>Metascheduling Multiple Resource Types using the MMKP</b>\n
206 by <em>D. Vanderster, N. Dimopoulos, R. Sobie</em>\n
207 7th IEEE/ACM International Conference on Grid Computing\n
208 Barcelona, September 28th-29th 2006
209 - <b>Master-Slave Tasking on Asymmetric Networks</b>\n
210 by <em>Cyril Banino-Rokkones, Olivier Beaumont and Lasse Natvig</em>.\n
211 In Proceedings of 12th International Euro-Par Conference, Euro-Par 2006.\n
212 August 29 - September 1, Pages 167--176, Dresden, Germany.
213 - <b>Critical Path and Area Based Scheduling of Parallel Task Graphs on Heterogeneous Platforms</b>\n
214 by <em>Tchimou N'Takpé and Frédéric Suter</em>\n
215 Proceedings of the Twelfth International Conference on Parallel and Distributed Systems (ICPADS)\n
216 Minneapolis, MN, July 12-15, 2006.
217 - <b>Sensitivity Analysis of Knapsack-based Task Scheduling on the Grid</b>\n
218 by <em>D.C. Vanderster and N.J. Dimopoulos</em>.\n
219 In Proceedings of The 20th ACM International Conference on Supercomputing\n
220 Cairns, Australia, June 28-July 1, 2006.\n
221 http://portal.acm.org/citation.cfm?id=1183401.1183446&coll=GUIDE&dl=%23url.coll
222 - <b>Hierarchical Scheduling of Independent Tasks with Shared Files</b>\n
223 by <em>H. Senger, F. Silva, W. Nascimento</em>.\n
224 Proceedings of the Sixth IEEE International Symposium on Cluster
225 Computing and the Grid Workshop (CCGRIDW'06)\n
226 Singapore, 16-19 May 2006.\n
227 http://www.unisantos.br/mestrado/informatica/hermes/File/senger-HierarchicalScheduling-Workshop-TB120.pdf
228 - <b>Evaluation of Knapsack-based Scheduling using the NPACI JOBLOG</b>\n
229 by <em>D. Vanderster, N. Dimopoulos, R. Parra-Hernandez and R. Sobie</em>.\n
230 20th International Symposium on High-Performance Computing in an
231 Advanced Collaborative Environment (HPCS'06)\n
232 St. John's, Newfoundland, Canada, 14-17 May 2006\n
233 http://doi.ieeecomputersociety.org/10.1109/HPCS.2006.23
236 - <b>On Dynamic Resource Management Mechanism using Control
237 Theoretic Approach for Wide-Area Grid Computing</b>\n
238 by <em>Hiroyuki Ohsaki, Soushi Watanabe, and Makoto Imase</em>\n
239 in Proceedings of IEEE Conference on Control Applications (CCA 2005), Aug. 2005.\n
240 http://www.ispl.jp/~oosaki/papers/Ohsaki05_CCA.pdf
241 - <b>Evaluation of Meta-scheduler Architectures and Task Assignment Policies for
242 high Throughput Computing</b>\n
243 by <em>Eddy Caron, Vincent Garonne and Andrei Tsaregorodtsev</em>\n
244 Proceedings of 4th Internationnal Symposium on Parallel and
245 Distributed Computing Job Scheduling Strategies for Parallel
246 Processing (ISPDC'05), July 2005.\n
247 http://www.ens-lyon.fr/LIP/Pub/Rapports/RR/RR2005/RR2005-27.pdf
248 - <b>Algorithmes de redistribution de données pour anneaux de processeurs hétérogènes</b>\n
249 by <em>Héléne Renard, Yves Robert and Frédéric Vivien</em>\n
250 In 16ième Rencontres Francophones du Parallélisme des Architectures et des Systèmes, Le Croisic, France, 6-8 avril 2005.\n
251 http://www.polytech.unice.fr/~hrenard/recherche/Renpar16.ps
253 - <b>Deadline Scheduling with Priority for Client-Server Systems on the Grid</b>\n
254 by <em>Eddy Caron, PK Chouhan, Frédéric Desprez</em>\n
255 in IEEE International Conference On Grid Computing. Super Computing 2004, oct 2004.
256 - <b>Efficient Scheduling Heuristics for GridRPC Systems</b>\n
257 by <em>Yves Caniou and Emmanuel Jeannot.</em>\n
258 in IEEE QoS and Dynamic System workshop (QDS) of International Conference
259 on Parallel and Distributed Systems (ICPADS), New-Port Beach California, USA,
260 pages 621-630, July 2004\n
261 http://graal.ens-lyon.fr/~ycaniou/QDS04.ps
262 - <b>Exploiting Replication and Data Reuse to Efficiently Schedule
263 Data-intensive Applications on Grids</b>\n
264 by <em> E. Santos-Neto, W. Cirne, F. Brasileiro, A. Lima.</em>\n
265 Proceedings of 10th Job Scheduling Strategies for Parallel Processing, June 2004.\n
266 http://www.lsd.ufcg.edu.br/~elizeu/articles/jsspp.v6.pdf
267 - <b>Resource Management and Knapsack Formulations on the Grid</b>\n
268 by <em>R. Parra-Hernandez, D. Vanderster and N. J. Dimopoulos</em>\n
269 Fifth IEEE/ACM International Workshop on Grid Computing (GRID'04)\n
270 http://doi.ieeecomputersociety.org/10.1109/GRID.2004.54
271 - <b>Scheduling BoT Applications in Grids using a Slave Oriented Adaptive
273 by <em>T. Ferreto, C. A. F. De Rose and C. Northfleet.</em>\n
274 Second International Symposium on Parallel and Distributed Processing
275 and Applications (ISPA), 2004, Hong Kong. Published in Lecture Notes in
276 Computer Science (LNCS), Volume 3358, by Springer-Verlag. p. 392-398.
277 - <b>Data redistribution algorithms for heterogeneous processor rings</b>\n
278 by <em>Héléne Renard, Yves Robert and Frédéric Vivien</em>\n
279 In International Conference on High Performance Computing HiPC'2004\n
280 http://www.polytech.unice.fr/~hrenard/recherche/Hipc.pdf
282 - <b>Link-Contention-Aware Genetic Scheduling Using Task Duplication in Grid Environments</b>\n
283 by <em>Wensheng Yao, Xiao Xie and Jinyuan You</em>\n
284 in Grid and Cooperative Computing: Second International Workshop, GCC 2003, Shanghai, China, December 7-10, 2003 (LNCS)\n
285 http://www.chinagrid.edu.cn/chinagrid/download/GCC2003/pdf/266.pdf
286 - <b>New Dynamic Heuristics in the Client-Agent-Server Model</b>\n
287 by <em>Yves Caniou and Emmanuel Jeannot</em>\n
288 in IEEE 13th Heteregeneous Computing Workshop - HCW'03, Nice, France, April 2003.\n
289 http://graal.ens-lyon.fr/~ycaniou/HCW03.ps
290 - <b>A Hierarchical Resource Reservation Algorithm for Network Enabled Servers</b>\n
291 by <em>Eddy Caron, Frédéric Desprez, Franck Petit, V. Villain</em>\n
292 in the 17th International Parallel and Distributed Processing Symposium -- IPDPS'03, Nice - France, April 2003.
294 \page publis_intra Our own papers that use SimGrid-generated results
296 This list is a selection of the articles we have written that used results
297 generated by SimGrid.
300 - <b>Assessing the Quality of Automatically Built Network Representations</b>\n
301 by <em>Lionel Eyraud-Dubois and Martin Quinson</em>\n
302 In Seventh IEEE International Symposium on Cluster Computing and
303 the Grid (CCGrid 2007), 14-17 May 2007, Rio de Janeiro, Brazil.
304 - <b>A Comparison of Scheduling Approaches for Mixed-Parallel Applications on Heterogeneous Platforms</b>\n
305 by <em>Tchimou N'takpé, Frédéric Suter, and Henri Casanova</em>\n
306 In 6th International Symposium on Parallel and Distributed Computing, Hagenberg, Austria, July 2007.
307 - <b>A First Step Towards Automatically Building Network Representations</b>\n
308 by <em>Lionel Eyraud-Dubois, Arnaud Legrand, Martin Quinson and Frédéric Vivien</em>\n
309 In 12th International Euro-Par Conference 28-31 August, Rennes, France.
310 - <b>Centralized Versus Distributed Schedulers Multiple Bag-of-Tasks Applications</b>\n
311 by <em>Olivier Beaumont, Larry Carter, Jeanne Ferrante, Arnaud Legrand, Loris Marchal, and Yves Robert</em>\n
312 In IEEE Trans. Parallel Distributed Systems, 2007.
314 - <b>On the Harmfulness of Redundant Batch Requests</b>\n
315 by <em>H. Casanova</em>\n
316 Proceedings of the IEEE International Symposium on High Performance Distributed Computing (HPDC-15), Paris, France, May 2006.\n
317 http://navet.ics.hawaii.edu/~casanova/homepage/papers/hpdc_2006.pdf
318 - <b>An evaluation of Job Scheduling Strategies for Divisible Loads on Grid Platforms</b>\n
319 by <em>Y. Cardinale, H. Casanova</em>\n
320 in Proceedings of the High Performance Computing & Simulation Conference (HPC&S'06), Bonn, Germany, May 2006.\n
321 http://navet.ics.hawaii.edu/~casanova/homepage/papers/cardinale_2006.pdf
322 - <b>Centralized Versus Distributed Schedulers Multiple Bag-of-Tasks Applications</b>\n
323 by <em>Olivier Beaumont, Larry Carter, Jeanne Ferrante, Arnaud Legrand, Loris Marchal, and Yves Robert</em>\n
324 International Parallel and Distributed Processing Symposium IPDPS'2006, 2006
325 - <b>Interference-Aware Scheduling</b>\n
326 by <em>B. Kreaseck, L. Carter, H. Casanova, J. Ferrante, S. Nandy</em>\n
327 International Journal of High Performance Computing Applications (IJHPCA).\n
328 http://navet.ics.hawaii.edu/~casanova/homepage/papers/kreaseck_ijhpca_2005.pdf
330 - <b>From Heterogeneous Task Scheduling to Heterogeneous Mixed Data and Task Parallel Scheduling</b>\n
331 by <em>F. Suter, V. Boudet, F. Desprez, H. Casanova</em>\n
332 Proceedings of Europar, 230--237, (LCNS volume 3149), Pisa, Italy, August 2004.
333 - <b>On the Interference of Communication on Computation</b>\n
334 by <em>B. Kreaseck, L. Carter, H. Casanova, J. Ferrante</em>\n
335 Proceedings of the workshop on Performance Modeling, Evaluation, and Optimization of Parallel and Distributed Systems, Santa Fe, April 2004.\n
336 http://navet.ics.hawaii.edu/~casanova/homepage/papers/k_pmeo2004.pdf
339 - <b>RUMR: Robust Scheduling for Divisible Workloads</b>\n
340 by <em>Y. Yang, H. Casanova</em>\n
341 Proceedings of the 12th IEEE Symposium on High Performance and Distributed Computing (HPDC-12), Seattle, June 2003.\n
342 http://navet.ics.hawaii.edu/~casanova/homepage/papers/yang_hpdc2003.pdf
343 - <b>Resource Allocation Strategies for Guided Parameter Space Searches</b>\n
344 by <em>M. Faerman, A. Birnbaum, F. Berman, H. Casanova</em>\n
345 International Journal of High Performance Computing Applications (IJHPCA), 17(4), 383--402, 2003.\n
346 http://grail.sdsc.edu/papers/faerman_ijhpca04.pdf
348 - <b>Resource Allocation for Steerable Parallel Parameter Searches</b>\n
349 by <em>M. Faerman, A. Birnbaum, H. Casanova, F. Berman</em>\n
350 Proceedings of the Grid Computing Workshop, Baltimore, 157--169, November 2002.\n
351 http://grail.sdsc.edu/projects/vi_itr/grid02.pdf
353 - <b>Applying Scheduling and Tuning to On-line Parallel Tomography </b>\n
354 by <em>Shava Smallen, Henri Casanova, Francine Berman</em>\n
355 in Proceedings of Supercomputing 2001\n
356 http://grail.sdsc.edu/papers/tomo_journal.ps.gz
358 - <b>Heuristics for Scheduling Parameter Sweep applications in Grid environments</b>\n
359 by <em>Henri Casanova, Arnaud Legrand, Dmitrii Zagorodnov and Francine Berman</em>\n
360 in Proceedings of the 9th Heterogeneous Computing workshop (HCW'2000), pp349-363.\n
361 http://navet.ics.hawaii.edu/~casanova/homepage/papers/hcw00_pst.pdf
366 \li <b>Optimal algorithms for scheduling divisible workloads on
367 heterogeneous systems</b>\n
368 by <em>Olivier Beaumont and Arnaud Legrand and Yves Robert</em>\n
369 in Proceedings of the 17th International Parallel and Distributed Processing Symposium (IPDPS'03).\n
370 Preliminary version on ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-36.ps.gz
373 \li <b>On-line Parallel Tomography</b>\n
374 by <em>Shava Smallen</em>\n
375 Masters Thesis, UCSD, May 2001