1 /*! \page publis Reference publications about SimGrid
4 When citing SimGrid, the prefered reference paper is <i>SimGrid: a
5 Generic Framework for Large-Scale Distributed Experimentations</i>.
7 \li <b>SimGrid: a Generic Framework for Large-Scale Distributed
9 by <em>Henri Casanova, Arnaud Legrand and Martin Quinson</em>\n
10 Proceedings of the 10th IEEE International Conference on Computer
11 Modelling and Simulation (UKSIM/EUROSIM'08)\n
12 Distributed computing is a very broad and active research area
13 comprising fields such as cluster computing, computational
14 grids, desktop grids and peer-to-peer (P2P) systems.
15 Unfortunately, it is often impossible to obtain theoretical or
16 analytical results to compare the performance of algorithms
17 targeting such systems. One possibility is to conduct large
18 numbers of back-to-back experiments on real platforms. While
19 this is possible on tightly-coupled platforms, it is infeasible
20 on modern distributed platforms as experiments are labor-intensive
21 and results typically not reproducible. Consequently, one must
22 resort to simulations, which enable reproducible results and also
23 make it possible to explore wide ranges of platform and
24 application scenarios.\n
25 In this paper we describe the SimGrid framework, a
26 simulation-based framework for evaluating cluster, grid and P2P
27 algorithms and heuristics. This paper focuses on SimGrid v3, which
28 greatly improves on previous versions thanks to a novel and
29 validated modular simulation engine that achieves higher
30 simulation speed without hindering simulation accuracy. Also, two
31 new user interfaces were added to broaden the targeted research
32 community. After surveying existing tools and methodologies we
33 describe the key features and benefits of SimGrid.\n
34 http://www.loria.fr/~quinson/articles/SimGrid-uksim08.pdf
37 @InProceedings{simgrid,
38 author = {Casanova, Henri and Legrand, Arnaud and Quinson, Martin},
39 title = {{SimGrid: a Generic Framework for Large-Scale Distributed Experiments}},
40 booktitle = {10th IEEE International Conference on Computer Modeling and Simulation},
46 \section publis_others Other publications
48 A lot of other papers where published about SimGrid. The list is
49 splited in 3 pages (also accessible from the navbar on top of this page):
51 This section contains papers describing some sub-parts of SimGrid,
52 or references superseeded by the one given above.
53 - \ref publis_extern\n
54 SimGrid is used by an ever growing scientific community. This
55 section lists all the papers resulting of works in which the core
56 SimGrid team were not involved.
58 This section lists the paper co-signed by at least one of the core
59 team member, and using SimGrid as a tool (and not studying SimGrid
62 \section publis_count Amount of published papers using SimGrid results
66 <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>
67 <td>2008</td><td>Total</td></tr>
68 <tr><td>Amount of papers external to the core team</td>
69 <td>-</td> <td>-</td> <td>-</td> <td>3</td> <td>6</td> <td>3</td> <td>8</td> <td>6</td>
70 <td>2</td><td>26</td></tr>
71 <tr><td>Amount of papers co-signed by one team member</td>
72 <td>1</td> <td>1</td> <td>1</td> <td>2</td> <td>2</td> <td>-</td> <td>4</td> <td>4</td>
73 <td>1</td><td>15</td></tr>
76 \page publis_core Other publications about the SimGrid framework
78 \li <b>Speed and Accuracy of Network Simulation in the SimGrid Framework</b>\n
79 by <em>K. Fujiwara, H. Casanova</em>\n
80 in Proceedings of the First International Workshop on Network Simulation Tools (NSTools), Nantes, France, October 2007.\n
81 http://navet.ics.hawaii.edu/~casanova/homepage/papers/fujiwara_nstool2007.pdf
83 \li <b>Cost and Accuracy of Packet-Level vs. Analytical Network Simulations: An Empirical Study</b>\n
84 by <em>K. Fujiwara</em>\n
85 <b>M.S. Thesis</b>, Dept. of Information and Computer Sciences, University of Hawai`i at Manoa, April 2007.\n
86 http://navet.ics.hawaii.edu/~casanova/homepage/theses/kayo_fujiwara_MS.pdf
88 \li <b>Gras: A Research & Development Framework for Grid and P2P
90 by <em>Martin Quinson</em>\n
91 <b>Best paper</b> of the 18th IASTED International Conference on
92 Parallel and Distributed Computing and Systems (PDCS 2006)\n
93 http://www.loria.fr/~quinson/articles/gras-iasted06.pdf
95 \li <b>The SimGrid Project - Simulation and Deployment of Distributed Applications</b>\n
96 by <em>A. Legrand, M. Quinson, K. Fujiwara, H. Casanova</em>\n
97 <b>POSTER</b> in Proceedings of the IEEE International Symposium on High Performance Distributed Computing (HPDC-15), Paris, France, May 2006.\n
99 <a href="http://navet.ics.hawaii.edu/~casanova/homepage/papers/simgrid_hpdc06.pdf"><img src="poster_thumbnail.png" /></a>
101 http://navet.ics.hawaii.edu/~casanova/homepage/papers/simgrid_hpdc06.pdf
103 \li <b>Scheduling Distributed Applications: the SimGrid Simulation Framework</b>\n
104 by <em>Henri Casanova and Arnaud Legrand and Loris Marchal</em>\n
105 Proceedings of the third IEEE International Symposium
106 on Cluster Computing and the Grid (CCGrid'03)\n
107 http://www-id.imag.fr/Laboratoire/Membres/Legrand_Arnaud/articles/simgrid2_CCgrid03.pdf
109 \li <b>A Network Model for Simulation of Grid Application</b>\n
110 by <em>Henri Casanova and Loris Marchal</em>\n
112 In this work we investigate network models that can be
113 potentially employed in the simulation of scheduling algorithms for
114 distributed computing applications. We seek to develop a model of TCP
115 communication which is both high-level and realistic. Previous research
116 works show that accurate and global modeling of wide-area networks, such
117 as the Internet, faces a number of challenging issues. However, some
118 global models of fairness and bandwidth-sharing exist, and can be link
119 withthe behavior of TCP. Using both previous results and simulation (with
120 NS), we attempt to understand the macroscopic behavior of
121 TCP communications. We then propose a global model of the network for the
122 Grid platform. We perform partial validation of this model in
123 simulation. The model leads to an algorithm for computing
124 bandwidth-sharing. This algorithm can then be implemented as part of Grid
125 application simulations. We provide such an implementation for the
126 SimGrid simulation toolkit.\n
127 ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-40.ps.gz
130 \li <b>MetaSimGrid : Towards realistic scheduling simulation of
131 distributed applications</b>\n
132 by <em>Arnaud Legrand and Julien Lerouge</em>\n
133 Most scheduling problems are already hard on homogeneous
134 platforms, they become quite intractable in an heterogeneous
135 framework such as a metacomputing grid. In the best cases, a
136 guaranteed heuristic can be found, but most of the time, it is
137 not possible. Real experiments or simulations are often
138 involved to test or to compare heuristics. However, on a
139 distributed heterogeneous platform, such experiments are
140 technically difficult to drive, because of the genuine
141 instability of the platform. It is almost impossible to
142 guarantee that a platform which is not dedicated to the
143 experiment, will remain exactly the same between two tests,
144 thereby forbidding any meaningful comparison. Simulations are
145 then used to replace real experiments, so as to ensure the
146 reproducibility of measured data. A key issue is the
147 possibility to run the simulations against a realistic
148 environment. The main idea of trace-based simulation is to
149 record the platform parameters today, and to simulate the
150 algorithms tomorrow, against the recorded data: even though it
151 is not the current load of the platform, it is realistic,
152 because it represents a fair summary of what happened
153 previously. A good example of a trace-based simulation tool is
154 SimGrid, a toolkit providing a set of core abstractions and
155 functionalities that can be used to easily build simulators for
156 specific application domains and/or computing environment
157 topologies. Nevertheless, SimGrid lacks a number of convenient
158 features to craft simulations of a distributed application
159 where scheduling decisions are not taken by a single
160 process. Furthermore, modeling a complex platform by hand is
161 fastidious for a few hosts and is almost impossible for a real
162 grid. This report is a survey on simulation for scheduling
163 evaluation purposes and present MetaSimGrid, a simulator built
165 ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-28.ps.gz
167 \li <b>SimGrid: A Toolkit for the Simulation of Application
169 by <em>Henri Casanova</em>\n
170 Advances in hardware and software technologies have made it
171 possible to deploy parallel applications over increasingly large
172 sets of distributed resources. Consequently, the study of
173 scheduling algorithms for such applications has been an active area
174 of research. Given the nature of most scheduling problems one must
175 resort to simulation to effectively evaluate and compare their
176 efficacy over a wide range of scenarios. It has thus become
177 necessary to simulate those algorithms for increasingly complex
178 distributed, dynamic, heterogeneous environments. In this paper we
179 present SimGrid, a simulation toolkit for the study of scheduling
180 algorithms for distributed application. This paper gives the main
181 concepts and models behind SimGrid, describes its API and
182 highlights current implementation issues. We also give some
183 experimental results and describe work that builds on SimGrid's
185 http://doi.ieeecomputersociety.org/10.1109/CCGRID.2001.923223
187 \page publis_extern Papers that use SimGrid-generated results (not counting our owns)
189 This list is a selection of articles. We list only papers written by people
190 external to the development group, but we also use our tool ourselves (see
197 - <b>Scheduling DAGs on Grids with Copying and Migration</b>\n
198 by <em>Israel Hernandez and Murray Cole</em>.\n
199 Parallel Processing and Applied Mathematics 2007 (PPAM07), LNCS 4967, pages 1019-1028, Springer, 2008.\n
200 http://www.springerlink.com/content/l555166254q2778p/?p=754ec30fb8044cce9f3f18dc9f304f4f&pi=107
201 - <b>Scheduling Dynamic Workflows onto Clusters of Clusters using Postponing</b>\n
202 by <em>Sascha Hunold, Thomas Rauber and Frédéric Suter</em>.\n
203 Proceedings of the 3rd International Workshop on Workflow Systems in
204 e-Science (WSES 08), Lyon, France, May 2008.
206 - <b>Reliable DAG Scheduling with Rewinding and Migration</b>\n
207 by <em>Israel Hernandez and Murray Cole</em>.\n
208 First International Conference on Networks for Grid Applications (GridNets07), pages 1-8, ACM Press, 2007.\n
209 http://portal.acm.org/citation.cfm?id=1386610.1386614
210 - <b>Reactive Grid Scheduling of DAG Applications.</b>\n by
211 <em>I. Hernandez and M. Cole (UK)</em>. In Parallel and Distributed Computing and Networks, 2007.\n
212 http://www.actapress.com/PaperInfo.aspx?PaperID=29625
213 - <b>Dynamic Scheduling of Multi-Processor Tasks on Clusters of Clusters</b>\n
214 by <em>S. Hunold, T. Rauber and G. Rünger</em>.\n
215 Proceedings of the Sixth International Workshop on Algorithms,
216 Models and Tools for Parallel Computing on Heterogeneous Networks
217 (Heteropar'07), Austin, TX, September 2007.
218 - <b>Scheduling Delta-Critical Tasks in Mixed-Parallel Applications on a National Grid</b>\n
219 by <em>Frédéric Suter</em>.\n
220 In 8th IEEE/ACM International Conference on Grid Computing (Grid 2007), Austin, TX, September 2007.
221 - <b>Brokering strategies in computational grids using stochastic
222 prediction models.</b>\n by <em>Vandy Berten and Bruno
223 Gaujal</em>. In Parallel Computing, vol. 33(4-5): 238-249, 2007.\n
224 http://dev.ulb.ac.be/sched/articles/PARCO.pdf
225 - <b>Managing Scheduling and Replication in the LHC Grid.</b>\n by
226 <em>Thomas Ferrandiz and Vania Marangozova</em>. In CoreGrid
227 Workshop on middleware, 2007.\n
230 - <b>Simbatch: an API for simulating and predicting the performance of parallel resources and batch systems.</b>\n
231 by <em>Jean-Sébastien Gay and Yves Caniou</em>\n
232 INRIA Research Report 6040, November 2006.\n
233 https://hal.inria.fr/inria-00115880
234 - <b>Simbatch : une API pour la simulation et la prédiction de performances de systèmes batch</b>\n
235 by <em>Jean-Sébastien Gay and Yves Caniou</em>.\n
236 In 17ème Rencontres Francophones du Parallélisme, des Architectures et des Systèmes, RenPar'17.\n
237 October 4-6, Perpignan, France
238 - <b>Metascheduling Multiple Resource Types using the MMKP</b>\n
239 by <em>D. Vanderster, N. Dimopoulos, R. Sobie</em>\n
240 7th IEEE/ACM International Conference on Grid Computing\n
241 Barcelona, September 28th-29th 2006
242 - <b>Master-Slave Tasking on Asymmetric Networks</b>\n
243 by <em>Cyril Banino-Rokkones, Olivier Beaumont and Lasse Natvig</em>.\n
244 In Proceedings of 12th International Euro-Par Conference, Euro-Par 2006.\n
245 August 29 - September 1, Pages 167--176, Dresden, Germany.
246 - <b>Critical Path and Area Based Scheduling of Parallel Task Graphs on Heterogeneous Platforms</b>\n
247 by <em>Tchimou N'Takpé and Frédéric Suter</em>\n
248 Proceedings of the Twelfth International Conference on Parallel and Distributed Systems (ICPADS)\n
249 Minneapolis, MN, July 12-15, 2006.
250 - <b>Sensitivity Analysis of Knapsack-based Task Scheduling on the Grid</b>\n
251 by <em>D.C. Vanderster and N.J. Dimopoulos</em>.\n
252 In Proceedings of The 20th ACM International Conference on Supercomputing\n
253 Cairns, Australia, June 28-July 1, 2006.\n
254 http://portal.acm.org/citation.cfm?id=1183401.1183446&coll=GUIDE&dl=%23url.coll
255 - <b>Hierarchical Scheduling of Independent Tasks with Shared Files</b>\n
256 by <em>H. Senger, F. Silva, W. Nascimento</em>.\n
257 Proceedings of the Sixth IEEE International Symposium on Cluster
258 Computing and the Grid Workshop (CCGRIDW'06)\n
259 Singapore, 16-19 May 2006.\n
260 http://www.unisantos.br/mestrado/informatica/hermes/File/senger-HierarchicalScheduling-Workshop-TB120.pdf
261 - <b>Evaluation of Knapsack-based Scheduling using the NPACI JOBLOG</b>\n
262 by <em>D. Vanderster, N. Dimopoulos, R. Parra-Hernandez and R. Sobie</em>.\n
263 20th International Symposium on High-Performance Computing in an
264 Advanced Collaborative Environment (HPCS'06)\n
265 St. John's, Newfoundland, Canada, 14-17 May 2006\n
266 http://doi.ieeecomputersociety.org/10.1109/HPCS.2006.23
269 - <b>On Dynamic Resource Management Mechanism using Control
270 Theoretic Approach for Wide-Area Grid Computing</b>\n
271 by <em>Hiroyuki Ohsaki, Soushi Watanabe, and Makoto Imase</em>\n
272 in Proceedings of IEEE Conference on Control Applications (CCA 2005), Aug. 2005.\n
273 http://www.ispl.jp/~oosaki/papers/Ohsaki05_CCA.pdf
274 - <b>Evaluation of Meta-scheduler Architectures and Task Assignment Policies for
275 high Throughput Computing</b>\n
276 by <em>Eddy Caron, Vincent Garonne and Andrei Tsaregorodtsev</em>\n
277 Proceedings of 4th Internationnal Symposium on Parallel and
278 Distributed Computing Job Scheduling Strategies for Parallel
279 Processing (ISPDC'05), July 2005.\n
280 http://www.ens-lyon.fr/LIP/Pub/Rapports/RR/RR2005/RR2005-27.pdf
281 - <b>Algorithmes de redistribution de données pour anneaux de processeurs hétérogènes</b>\n
282 by <em>Héléne Renard, Yves Robert and Frédéric Vivien</em>\n
283 In 16ième Rencontres Francophones du Parallélisme des Architectures et des Systèmes, Le Croisic, France, 6-8 avril 2005.\n
284 http://www.polytech.unice.fr/~hrenard/recherche/Renpar16.ps
286 - <b>Deadline Scheduling with Priority for Client-Server Systems on the Grid</b>\n
287 by <em>Eddy Caron, PK Chouhan, Frédéric Desprez</em>\n
288 in IEEE International Conference On Grid Computing. Super Computing 2004, oct 2004.
289 - <b>Efficient Scheduling Heuristics for GridRPC Systems</b>\n
290 by <em>Yves Caniou and Emmanuel Jeannot.</em>\n
291 in IEEE QoS and Dynamic System workshop (QDS) of International Conference
292 on Parallel and Distributed Systems (ICPADS), New-Port Beach California, USA,
293 pages 621-630, July 2004\n
294 http://graal.ens-lyon.fr/~ycaniou/QDS04.ps
295 - <b>Exploiting Replication and Data Reuse to Efficiently Schedule
296 Data-intensive Applications on Grids</b>\n
297 by <em> E. Santos-Neto, W. Cirne, F. Brasileiro, A. Lima.</em>\n
298 Proceedings of 10th Job Scheduling Strategies for Parallel Processing, June 2004.\n
299 http://www.lsd.ufcg.edu.br/~elizeu/articles/jsspp.v6.pdf
300 - <b>Resource Management and Knapsack Formulations on the Grid</b>\n
301 by <em>R. Parra-Hernandez, D. Vanderster and N. J. Dimopoulos</em>\n
302 Fifth IEEE/ACM International Workshop on Grid Computing (GRID'04)\n
303 http://doi.ieeecomputersociety.org/10.1109/GRID.2004.54
304 - <b>Scheduling BoT Applications in Grids using a Slave Oriented Adaptive
306 by <em>T. Ferreto, C. A. F. De Rose and C. Northfleet.</em>\n
307 Second International Symposium on Parallel and Distributed Processing
308 and Applications (ISPA), 2004, Hong Kong. Published in Lecture Notes in
309 Computer Science (LNCS), Volume 3358, by Springer-Verlag. p. 392-398.
310 - <b>Data redistribution algorithms for heterogeneous processor rings</b>\n
311 by <em>Héléne Renard, Yves Robert and Frédéric Vivien</em>\n
312 In International Conference on High Performance Computing HiPC'2004\n
313 http://www.polytech.unice.fr/~hrenard/recherche/Hipc.pdf
315 - <b>Link-Contention-Aware Genetic Scheduling Using Task Duplication in Grid Environments</b>\n
316 by <em>Wensheng Yao, Xiao Xie and Jinyuan You</em>\n
317 in Grid and Cooperative Computing: Second International Workshop, GCC 2003, Shanghai, China, December 7-10, 2003 (LNCS)\n
318 http://www.chinagrid.edu.cn/chinagrid/download/GCC2003/pdf/266.pdf
319 - <b>New Dynamic Heuristics in the Client-Agent-Server Model</b>\n
320 by <em>Yves Caniou and Emmanuel Jeannot</em>\n
321 in IEEE 13th Heteregeneous Computing Workshop - HCW'03, Nice, France, April 2003.\n
322 http://graal.ens-lyon.fr/~ycaniou/HCW03.ps
323 - <b>A Hierarchical Resource Reservation Algorithm for Network Enabled Servers</b>\n
324 by <em>Eddy Caron, Frédéric Desprez, Franck Petit, V. Villain</em>\n
325 in the 17th International Parallel and Distributed Processing Symposium -- IPDPS'03, Nice - France, April 2003.
327 \page publis_intra Our own papers that use SimGrid-generated results
329 This list is a selection of the articles we have written that used results
330 generated by SimGrid.
333 - <b>Toward a Fully Decentralized Algorithm for Multiple Bag-of-tasks Application Scheduling on Grids</b>\n
334 by <em>Rémi Bertin, Arnaud Legrand, and Corinne Touati</em>.\n
335 In IEEE/ACM International Conference on Grid Computing (Grid), Tsukuba, Japan, 2008.
337 - <b>Assessing the Quality of Automatically Built Network Representations</b>\n
338 by <em>Lionel Eyraud-Dubois and Martin Quinson</em>\n
339 In Seventh IEEE International Symposium on Cluster Computing and
340 the Grid (CCGrid 2007), 14-17 May 2007, Rio de Janeiro, Brazil.
341 - <b>A Comparison of Scheduling Approaches for Mixed-Parallel Applications on Heterogeneous Platforms</b>\n
342 by <em>Tchimou N'takpé, Frédéric Suter, and Henri Casanova</em>\n
343 In 6th International Symposium on Parallel and Distributed Computing, Hagenberg, Austria, July 2007.
344 - <b>A First Step Towards Automatically Building Network Representations</b>\n
345 by <em>Lionel Eyraud-Dubois, Arnaud Legrand, Martin Quinson and Frédéric Vivien</em>\n
346 In 12th International Euro-Par Conference 28-31 August, Rennes, France.
347 - <b>Centralized Versus Distributed Schedulers Multiple Bag-of-Tasks Applications</b>\n
348 by <em>Olivier Beaumont, Larry Carter, Jeanne Ferrante, Arnaud Legrand, Loris Marchal, and Yves Robert</em>\n
349 In IEEE Trans. Parallel Distributed Systems, 2007.
351 - <b>On the Harmfulness of Redundant Batch Requests</b>\n
352 by <em>H. Casanova</em>\n
353 Proceedings of the IEEE International Symposium on High Performance Distributed Computing (HPDC-15), Paris, France, May 2006.\n
354 http://navet.ics.hawaii.edu/~casanova/homepage/papers/hpdc_2006.pdf
355 - <b>An evaluation of Job Scheduling Strategies for Divisible Loads on Grid Platforms</b>\n
356 by <em>Y. Cardinale, H. Casanova</em>\n
357 in Proceedings of the High Performance Computing & Simulation Conference (HPC&S'06), Bonn, Germany, May 2006.\n
358 http://navet.ics.hawaii.edu/~casanova/homepage/papers/cardinale_2006.pdf
359 - <b>Centralized Versus Distributed Schedulers Multiple Bag-of-Tasks Applications</b>\n
360 by <em>Olivier Beaumont, Larry Carter, Jeanne Ferrante, Arnaud Legrand, Loris Marchal, and Yves Robert</em>\n
361 International Parallel and Distributed Processing Symposium IPDPS'2006, 2006
362 - <b>Interference-Aware Scheduling</b>\n
363 by <em>B. Kreaseck, L. Carter, H. Casanova, J. Ferrante, S. Nandy</em>\n
364 International Journal of High Performance Computing Applications (IJHPCA).\n
365 http://navet.ics.hawaii.edu/~casanova/homepage/papers/kreaseck_ijhpca_2005.pdf
367 - <b>From Heterogeneous Task Scheduling to Heterogeneous Mixed Data and Task Parallel Scheduling</b>\n
368 by <em>F. Suter, V. Boudet, F. Desprez, H. Casanova</em>\n
369 Proceedings of Europar, 230--237, (LCNS volume 3149), Pisa, Italy, August 2004.
370 - <b>On the Interference of Communication on Computation</b>\n
371 by <em>B. Kreaseck, L. Carter, H. Casanova, J. Ferrante</em>\n
372 Proceedings of the workshop on Performance Modeling, Evaluation, and Optimization of Parallel and Distributed Systems, Santa Fe, April 2004.\n
373 http://navet.ics.hawaii.edu/~casanova/homepage/papers/k_pmeo2004.pdf
376 - <b>RUMR: Robust Scheduling for Divisible Workloads</b>\n
377 by <em>Y. Yang, H. Casanova</em>\n
378 Proceedings of the 12th IEEE Symposium on High Performance and Distributed Computing (HPDC-12), Seattle, June 2003.\n
379 http://navet.ics.hawaii.edu/~casanova/homepage/papers/yang_hpdc2003.pdf
380 - <b>Resource Allocation Strategies for Guided Parameter Space Searches</b>\n
381 by <em>M. Faerman, A. Birnbaum, F. Berman, H. Casanova</em>\n
382 International Journal of High Performance Computing Applications (IJHPCA), 17(4), 383--402, 2003.\n
383 http://grail.sdsc.edu/papers/faerman_ijhpca04.pdf
385 - <b>Resource Allocation for Steerable Parallel Parameter Searches</b>\n
386 by <em>M. Faerman, A. Birnbaum, H. Casanova, F. Berman</em>\n
387 Proceedings of the Grid Computing Workshop, Baltimore, 157--169, November 2002.\n
388 http://grail.sdsc.edu/projects/vi_itr/grid02.pdf
390 - <b>Applying Scheduling and Tuning to On-line Parallel Tomography </b>\n
391 by <em>Shava Smallen, Henri Casanova, Francine Berman</em>\n
392 in Proceedings of Supercomputing 2001\n
393 http://grail.sdsc.edu/papers/tomo_journal.ps.gz
395 - <b>Heuristics for Scheduling Parameter Sweep applications in Grid environments</b>\n
396 by <em>Henri Casanova, Arnaud Legrand, Dmitrii Zagorodnov and Francine Berman</em>\n
397 in Proceedings of the 9th Heterogeneous Computing workshop (HCW'2000), pp349-363.\n
398 http://navet.ics.hawaii.edu/~casanova/homepage/papers/hcw00_pst.pdf
403 \li <b>Optimal algorithms for scheduling divisible workloads on
404 heterogeneous systems</b>\n
405 by <em>Olivier Beaumont and Arnaud Legrand and Yves Robert</em>\n
406 in Proceedings of the 17th International Parallel and Distributed Processing Symposium (IPDPS'03).\n
407 Preliminary version on ftp://ftp.ens-lyon.fr/pub/LIP/Rapports/RR/RR2002/RR2002-36.ps.gz
410 \li <b>On-line Parallel Tomography</b>\n
411 by <em>Shava Smallen</em>\n
412 Masters Thesis, UCSD, May 2001