• Danilo Carastan dos Santos, Krzysztof Rzadca, Leonel Sousa, and Denis Trystram. A community-guided discussion about social and environmental effects of post-COVID-19 Computer Science conferencing. preprint, 2023. ICT4S, Rennes june 2023. URL
  • Miguel Felipe Silva Vasconcelos, Daniel Cordeiro, Georges da Costa, Fanny Dufoss´e, Jean-Marc Nicod, and Veronika Rehn-Sonigo. Optimal sizing of a globally distributed low carbon cloud federation. In 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid), Bangalore, May 2023. URL
  • Kevi Eniko and Nguyn Kim Thang. Primal-Dual Algorithms with Predictions for Online Bounded Allocation and Ad-Auctions Problems. In Algorithmic Learning Theory, Singapore, February 2023. URL


  • Mael Madon, Georges da Costa, and Jean-Marc Pierson. Characterization of Different User Behaviors for Demand Response in Data Centers. In 28th International Conference on Parallel and Distributed Computing (Euro-Par 2022), volume 13440 of LNCS, pages 53–68, Glasgow, August 2022. Springer. doi: 10.1007/978-3-031-12597-3 4. URL
  • Vincent Fagnon, Giorgio Lucarelli, Clément Mommessin, and Denis Trystram. Two-Agent Scheduling with Resource Augmentation on Multiple Machines. preprint, May 2022. Euro-Par 2022, volume 13440 of LNCS, Glasgow, August 2022. Springer. URL
  • Evripidis Bampis, Konstantinos Dogeas, Alexander Kononov, Giorgio Lucarelli, and Fanny Pascual. Scheduling with Untrusted Predictions. In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}, pages 4581–4587, Vienna, July 2022. doi: 10.24963/ijcai.2022/636. URL
  • Konstantinos Dogeas, Energy minimization, data movements and uncertainties, PhD thesis, Sorbonne Université, 6 avril 2022
  • Fanny Dufossé, Christoph Durr, Noel Nadal, Denis Trystram, and Oscar Vasquez. Scheduling with a processing time oracle. Applied Mathematical Modelling, 104:701–720, April 2022. doi: 10.1016/j.apm.2021.12.020. URL


  • Georges da Costa. MojitO/S, November 2021. URL
  • Eric Angel, Evripidis Bampis, Vincent Chau, and Vassilis Zissimopoulos. Calibrations scheduling with arbitrary lengths and activation length. Journal of Scheduling, 24:459–467, October 2021. doi: 10.1007/s10951-021-00688-5. URL
  • Evripidis Bampis, Konstantinos Dogeas, Alexander Kononov, Giorgio Lucarelli, and Fanny Pascual. Speed Scaling with Explorable Uncertainty. In 33th ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2021), pages 83–93, virtual conference, United States, July 2021. ACM. doi: 10.1145/3409964.3461812. URL
  • Salah Zrigui. Understanding and improving HPC performance using Machine Learning and Statistical analysis. Theses, Université Grenoble Alpes, March 2021. URL


  • Nesryne Mejri, Briag Dupont, and Georges da Costa. Energy-aware scheduling of malleable HPC applications using a Particle Swarm optimised greedy algorithm. Sustainable Computing : Informatics and Systems, 28:100447, December 2020. doi: 10.1016/j.suscom.2020.100447. URL
  • Christoph Durr, Thomas Erlebach, Nicole Megow, and Julie Meissner. An Adversarial Model for Scheduling with Testing. Algorithmica, July 2020. doi: 10.1007/s00453-020-00742-2. URL
  • Evripidis Bampis, Konstantinos Dogeas, Alexander Kononov, Giorgio Lucarelli, and Fanny Pascual. Scheduling Malleable Jobs Under Topological Constraints. In 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS), pages 316–325, New Orleans, LA, May 2020. IEEE. doi: 10.1109/IPDPS47924.2020.00041. URL


  • Salah Zrigui, Raphael de Camargo, Denis Trystram, and Arnaud Legrand. Improving the Performance of Batch Schedulers Using Online Job Size Classification, October 2019 published in JPDC vol. 164, 2022. URL
  • Arnaud Legrand, Denis Trystram, and Salah Zrigui. Adapting Batch Scheduling to Workload Characteristics: What can we expect From Online Learning? In IPDPS 2019 - 33rd IEEE International Parallel & Distributed Processing Symposium, pages 686–695, Rio de Janeiro, May 2019. IEEE. doi: 10.1109/IPDPS.2019.00077 URL
  • Danilo Carastan-Santos, Raphael de Camargo, Denis Trystram, and Salah Zrigui. One can only gain by replacing EASY Backfilling: A simple scheduling policies case study. In CCGrid 2019 - International Symposium in Cluster, Cloud, and Grid Computing, pages 1–10, Larnaca, Cyprus, May 2019. IEEE. doi: 10.1109/CCGRID.2019.00010. URL

You will find here the public deliverable of the Energumen Project