SIMGRID: A toolkit for the simulation of application scheduling. 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. We present Simgrid a simulation toolkit for the study of scheduling algorithms for distributed application. We give the main concepts and models behind Simgrid, describe its API and highlight current implementation issues. We also give some experimental results and describe work that builds on Simgrid’s functionalities.

References in zbMATH (referenced in 22 articles )

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  1. Benoit, Anne; Gallet, Matthieu; Gaujal, Bruno; Robert, Yves: Computing the throughput of probabilistic and replicated streaming applications (2014)
  2. Frincu, Marc E.; Genaud, Stéphane; Gossa, Julien: On the efficiency of several VM provisioning strategies for workflows with multi-threaded tasks on clouds (2014)
  3. Mansouri, Najme: Network and data location aware approach for simultaneous job scheduling and data replication in large-scale data grid environments (2014) ioport
  4. Mello Schnorr, Lucas; Huard, Guillaume; Navaux, Philippe Olivier Alexandre: A hierarchical aggregation model to achieve visualization scalability in the analysis of parallel applications (2012) ioport
  5. Bahi, Jacques M.; Contassot-Vivier, Sylvain; Giersch, Arnaud: Load balancing in dynamic networks by bounded delays asynchronous diffusion (2011)
  6. Glatard, Tristan; Camarasu-Pop, Sorina: A model of pilot-job resource provisioning on production grids (2011) ioport
  7. Casanova, Henri; Desprez, Frédéric; Suter, Frédéric: On cluster resource allocation for multiple parallel task graphs (2010)
  8. Chin, Sung Ho; Suh, Taeweon; Yu, Heon Chang: Adaptive service scheduling for workflow applications in Service-Oriented Grid (2010) ioport
  9. Lingrand, Diane; Montagnat, Johan; Martyniak, Janusz; Colling, David: Optimization of jobs submission on the EGEE production grid: modeling faults using workload (2010) ioport
  10. Estrada, Trilce; Taufer, Michela; Anderson, David P.: Performance prediction and analysis of BOINC projects: an empirical study with EmBOINC (2009) ioport
  11. Li, Chunlin; Li, Layuan: A global optimization approach for three layers of computational grid stack (2009)
  12. Yin, Fei; Du, Xiaoli; Jiang, Changjun; Deng, Rong: Directed acyclic task graph scheduling for heterogeneous computing systems by dynamic critical path duplication algorithm (2009)
  13. Venugopal, Srikumar; Buyya, Rajkumar: An SCP-based heuristic approach for scheduling distributed data-intensive applications on global grids (2008)
  14. Wilson García, Edscott; Morales-Luna, Guillermo: Simulation for bulk synchronous parallel superstep task assignment in desktop grids characterised by Gaussian parameter distributions (2008)
  15. Legrand, A.; Marchal, L.; Robert, Y.: Optimizing the steady-state throughput of scatter and reduce operations on heterogeneous platforms (2005)
  16. Otoo, Ekow; Rotem, Doron; Shoshani, Arie: Impact of admission and cache replacement policies on response times of jobs on data grids (2005) ioport
  17. Gong, YiLi; Dong, FangPeng; Li, Wei; Xu, ZhiWei: VEGA infrastructure for resource discovery in grids (2003)
  18. Beaumont, Olivier; Legrand, Arnaud; Robert, Yves: Static scheduling strategies for heterogeneous systems (2002)
  19. Buyya, Rajkumar; Murshed, Manzur: GridSim: a toolkit for the modeling and simulation of distributed resource management and scheduling for grid computing (2002)
  20. Faerman, Marcio; Birnbaum, Adam; Casanova, Henri; Berman, Fran: Resource allocation for steerable parallel parameter searches (2002)

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