Loris Marchal
Publications
Publications
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Cache Management for Mixture-of-Experts LLMs31st European Conference on Parallel and Distributed Processing (EURO-PAR 2025), Aug 2025, Dresden, Germany. pp.18-32, ⟨10.1007/978-3-031-99872-0_2⟩ |
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Deadline-Aware Scheduling of Mixed-Criticality TasksICPP '25 - 54th International Conference on Parallel Processing, Sep 2025, San Diego, CA, United States |
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Leveraging Expert Usage to Speed up LLM Inference with Expert ParallelismEuro-Par 2025: Parallel Processing, Aug 2025, Dresden, Germany |
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Data-Driven Locality-Aware Batch SchedulingAPDCM 2024 - 26th Workshop on Advances in Parallel and Distributed Computational Models, 38th IEEE International Parallel and Distributed Processing Symposium, May 2024, San Francisco, United States. pp.202-211, ⟨10.1109/IPDPSW63119.2024.00058⟩ |
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Solving the Restricted Assignment Problem to Schedule Multi-get Requests in Key-Value Stores30th European Conference on Parallel and Distributed Processing, Aug 2024, Madrid, Spain. pp.195-209, ⟨10.1007/978-3-031-69577-3_14⟩ |
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Hector: A Framework to Design and Evaluate Scheduling Strategies in Persistent Key-Value StoresICPP 2023 - 52nd International Conference on Parallel Processing, Aug 2023, Salt Lake City, United States |
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Checkpointing à la Young/Daly: An OverviewIC3 2022 - 2022 Fourteenth International Conference on Contemporary Computing, Aug 2022, Noida, India. pp.701-710, ⟨10.1145/3549206.3549328⟩ |
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Bounding the Flow Time in Online Scheduling with Structured Processing SetsIPDPS 2022 - 36th IEEE International Parallel & Distributed Processing Symposium, May 2022, Lyon, France. pp.1-11 |
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Memory-Aware Scheduling of Tasks Sharing Data on Multiple GPUs with Dynamic Runtime SystemsIPDPS 2022 - 36th IEEE International Parallel & Distributed Processing Symposium, May 2022, Lyon, France. pp.1-11, ⟨10.1109/IPDPS53621.2022.00073⟩ |
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Locality-Aware Scheduling of Independent Tasks for Runtime SystemsCOLOC 2021 - 5th workshop on data locality - 27th International European Conference on Parallel and Distributed Computing, Aug 2021, Lisbon, Portugal. pp.1-12, ⟨10.1007/978-3-031-06156-1_1⟩ |
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Taming Tail Latency in Key-Value Stores: a Scheduling PerspectiveEuro-Par 2021 - 27th International European Conference on Parallel and Distributed Computing, Aug 2021, Lisbon (virtual), Portugal. pp.136-150, ⟨10.1007/978-3-030-85665-6_9⟩ |
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Robustness of the Young/Daly formula for stochastic iterative applicationsICPP 2020 - 49th International Conference on Parallel Processing, Aug 2020, Edmonton / Virtual, Canada. pp.1-11, ⟨10.1145/3404397.3404418⟩ |
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Revisiting dynamic DAG scheduling under memory constraints for shared-memory platformsIPDPS - 2020 - IEEE International Parallel and Distributed Processing Symposium Workshops, May 2020, New Orleans / Virtual, United States. pp.1-10, ⟨10.1109/IPDPSW50202.2020.00102⟩ |
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Reliable and energy-aware mapping of streaming series-parallel applications onto hierarchical platformsSBAC-PAD 2020 - IEEE 32nd International Symposium on Computer Architecture and High Performance Computing, Sep 2020, Porto, Portugal. pp.1-11 |
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Improving mapping for sparse direct solvers: A trade-off between data locality and load balancingEuroPar 2020 - 26th International European Conference on Parallel and Distributed Computing, Aug 2020, Warsaw / Virtual, Poland. pp.1-16 |
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Memory-aware tree partitioning on homogeneous platformsPDP 2018 - 26th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, Mar 2018, Cambridge, United Kingdom. pp.321-324, ⟨10.1109/PDP2018.2018.00056⟩ |
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Reliability-aware energy optimization for throughput-constrained applications on MPSoCICPADS - 24th International Conference on Parallel and Distributed Systems, Dec 2018, Sentosa, Singapore. pp.1-10 |
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Data-Locality Aware Dynamic Schedulers for Independent Tasks with Replicated InputsIPDPSW 2018 IEEE International Parallel and Distributed Processing Symposium Workshops, May 2018, Vancouver, Canada. pp.1-8, ⟨10.1109/IPDPSW.2018.00187⟩ |
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Online Scheduling of Task Graphs on Hybrid PlatformsEuro-Par 2018 - 24th International European Conference On Parallel And Distributed Computing, Aug 2018, Turin, Italy. pp.1-14, ⟨10.1007/978-3-319-96983-1_14⟩ |
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Parallel scheduling of DAGs under memory constraintsIPDPS 2018 - 32nd IEEE International Parallel and Distributed Processing Symposium, May 2018, Vancouver, Canada. pp.1-10, ⟨10.1109/IPDPS.2018.00030⟩ |
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Minimizing I/Os in Out-of-Core Task Tree Scheduling19th Workshop on Advances in Parallel and Distributed Computational Models, May 2017, Orlando, United States. ⟨10.1109/IPDPSW.2017.58⟩ |
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Low-Cost Approximation Algorithms for Scheduling Independent Tasks on Hybrid PlatformsEuro-Par 2017: 23rd International European Conference on Parallel and Distributed Computing, Aug 2017, Santiago de Compostela, Spain. ⟨10.1007/978-3-319-64203-1_17⟩ |
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Dynamic Memory-Aware Task-Tree SchedulingIPDPS 2017 - 31st IEEE International Parallel & Distributed Processing Symposium, May 2017, Orlando, United States. pp.10 |
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Minimizing Rental Cost for Multiple Recipe Applications in the CloudIPDPS Workshops, May 2016, Chicago, United States. pp.28--37, ⟨10.1109/IPDPSW.2016.71⟩ |
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Minimizing Rental Cost for Multiple Recipe Applications in the CloudInternational Parallel and Distributed Processing Symposium, May 2016, Chicago, IL, United States |
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Bridging the Gap between Performance and Bounds of Cholesky Factorization on Heterogeneous PlatformsHeterogeneity in Computing Workshop 2015, May 2015, Hyderabad, India. ⟨10.1109/IPDPSW.2015.35⟩ |
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Scheduling Trees of Malleable Tasks for Sparse Linear AlgebraInternational European Conference on Parallel and Distributed Computing (Euro-Par 2015), 2015, Vienna, Austria. pp.479-490, ⟨10.1007/978-3-662-48096-0_37⟩ |
Determining the Optimal Redistribution for a Given Data Partition13th International Symposium on Parallel and Distributed Computing (ISPDC), 2014, Marseille, France. ⟨10.1109/ISPDC.2014.16⟩ |
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Analysis of Dynamic Scheduling Strategies for Matrix Multiplication on Heterogeneous PlatformsACM Symposium on High-Performance Parallel and Distributed Computing, Jun 2014, Vancouver, Canada. ⟨10.1145/2600212.2600223⟩ |
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Model and complexity results for tree traversals on hybrid platformsHeteroPar - International Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms, Aug 2013, Aachen, Germany |
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Scheduling tree-shaped task graphs to minimize memory and makespanIPDPS 2013 - 27th IEEE International Parallel & Distributed Processing Symposium, May 2013, Boston, United States |
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Non Linear Divisible Loads: There is No Free LunchIPDPS 2013, 27th IEEE International Parallel & Distributed Processing Symposium, IEEE, May 2013, Boston, United States |
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Non-clairvoyant reduction algorithms for heterogeneous platformsHeteroPar'2013, in conjunction with Euro-Par 2013, Aug 2013, Aachen, Germany |
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Minimizing Weighted Mean Completion Time for Malleable Tasks SchedulingIPDPS 2012, 26th IEEE International Parallel & Distributed Processing Symposium, May 2012, Shangai, China |
On optimal tree traversals for sparse matrix factorizationIPDPS'2011, the 25th IEEE International Parallel and Distributed Processing Symposium, 2011, Unknown |
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Comparing archival policies for BlueWatersInternational Conference on High Performance Computing (HiPC'2011), 2011, Unknown |
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Scheduling complex streaming applications on the Cell processor4th Workshop on Multi-threaded Architectures and Applications (MTAAP 2010), May 2010, Atlanta, GA, United States. pp.1-8, ⟨10.1109/IPDPSW.2010.5470684⟩ |
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A Fair Decentralized Scheduler for Bag-of-tasks Applications on Desktop GridsCCGrid 2010 - 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, May 2010, Malbourne, Australia. ⟨10.1109/CCGRID.2010.13⟩ |
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Mapping pipelined applications with replication to increase throughput and reliabilityInternational Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), 2010, Petropolis, Brazil. pp.55-62, ⟨10.1109/SBAC-PAD.2010.16⟩ |
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Efficient Scheduling of Task Graph Collections on Heterogeneous ResourcesIPDPS'2009 - International Parallel and Distributed Processing Symposium, 2009, Roma, Italy. ⟨10.1109/IPDPS.2009.5161045⟩ |
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Complexity Analysis and Performance Evaluation of Matrix Product on Multicore ArchitecturesICPP '09. International Conference on Parallel Processing, 2009., Sep 2009, Vienna, Austria. pp.196-203, ⟨10.1109/ICPP.2009.40⟩ |
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Resource-aware allocation strategies for divisible loads on large-scale systemsHCW 2009 - 18th International Heterogeneity in Computing Workshop, 2009, Roma, Italy. ⟨10.1109/IPDPS.2009.5160912⟩ |
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Steady-State for Batches of Identical Task GraphsEuro-Par'09, 2009, Netherlands. pp.203--215 |
Offline and online scheduling of concurrent bags-of-tasks on heterogeneous platforms10th Workshop on Advances in Parallel and Distributed Computational Models APDCM 2008, 2008, Unknown, United States |
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Allocating Series of Workflows on Computing GridsProceedings of the 14th IEEE International Conference on Parallel and Distributed Systems (ICPADS'08), 2008, Unknown, pp.48-55, ⟨10.1109/ICPADS.2008.96⟩ |
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Towards Real-Time Distributed Signal Modeling for Brain Machine InterfacesProceedings of Dynamic Data Driven Application Systems (workshop of ICCS), 2007, Unknown, China. pp.964-971, ⟨10.1007/978-3-540-72584-8_127⟩ |
Voronet: A scalable object network based on voronoi tessellations.International Parallel and Distributed Processing Symposium -- IPDPS 2007, 2007, Long Beach, United States |
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Scheduling and data redistribution strategies on star platformsPDP'2007, 15th Euromicro Workshop on Parallel, Distributed and Network-based Processing, 2007, Unknown, Italy. pp.288-295, ⟨10.1109/PDP.2007.72⟩ |
Centralized Versus Distributed Schedulers Multiple Bag-of-Task ApplicationsInternational Parallel and Distributed Processing Symposium IPDPS'2006, 2006, Rhodes Island, Greece. ⟨10.1109/TPDS.2007.70747⟩ |
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Voronet, un réseau objet-à-objet sur le modèle petit-mondeCFSE'5: Conférence Française sur les Systèmes d'Exploitation, 2006, Unknown, France |
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FIFO scheduling of divisible loads with return messages under the one-port modelParallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International, Apr 2006, Rhodes, Greece. ⟨10.1109/IPDPS.2006.1639390⟩ |
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Optimal bandwidth sharing in grid environmentHPDC'2006, the 15th International Symposium on High Performance Distributed Computing, 2006, Unknown, France |
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Optimizing network resource sharing in gridsIEEE Global Telecommunications Conference GlobeCom'2005, 2005, Unknown |
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Scheduling Divisible Loads with Return Messages on Heterogeneous Master-Worker PlatformsHigh Performance Computing – HiPC 2005, Dec 2005, Goa, India. ⟨10.1007/11602569⟩ |
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Broadcast Trees for Heterogeneous PlatformsParallel and Distributed Processing Symposium, IPDPS 2005. Proceedings. 19th IEEE International, Apr 2005, Denver, United States. ⟨10.1109/IPDPS.2005.131⟩ |
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Independent and Divisible Tasks Scheduling on Heterogeneous Star-Schaped Platforms with Limited MemoryPDP\'2005, 13th Euromicro Workshop on Parallel, Distributed and Network-Based Processing, 2005, Unknown, pp.179―186 |
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A realistic network/application model for scheduling divisible loads on large-scale platformsInternational Parallel and Distributed Processing Symposium IPDPS'2005, 2005, Unknown |
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Complexity Results and Heuristics for Pipelined Multicast Operations on Heterogeneous Platforms2004 International Conference on Parallel Processing (ICPP\'2004), 2004, Unknown, pp.267―274, ⟨10.1109/ICPP.2004.1327931⟩ |
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Assessing the Impact and Limits of Steady-State Scheduling for Mixed Task and Data Parallelism on Heterogeneous PlatformsHeteroPar\'2004: International Conference on Heterogeneous Computing, Jointly Published with ISPDC\'2004: International Symposium on Parallel and Distributed Computing, 2004, Unknown, pp.296―302, ⟨10.1109/ISPDC.2004.12⟩ |
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Steady-State Scheduling on Heterogeneous Clusters: Why and How?6th Workshop on Advances in Parallel and Distributed Computational Models APDCM, 2004, Unknown, 171a (8 p.) |
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Optimizing the Steady-State Throughput of Scatter and Reduce Operations on Heterogeneous Platforms6th Workshop on Advances in Parallel and Distributed Computational Models APDCM 2004, 2004, Unknown, 176a (8 p.), ⟨10.1016/j.jpdc.2005.05.021⟩ |
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Pipelining broadcasts on heterogeneous platformsInternational Parallel and Distributed Processing Symposium IPDPS'2004, 2004, Unknown |
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Scheduling Distributed Applications: the SimGrid Simulation FrameworkProceedings of the Third IEEE International Symposium on Cluster Computing and the Grid (CCGrid\'03), 2003, Unknown |
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Memory-Aware Scheduling Of Tasks Sharing Data On Multiple GPUsISC 2023 - ISC High Performance 2023, May 2023, Hamburg, Germany. Lecture Notes in Computer Science |
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Memory-Aware Scheduling Of Tasks Sharing Data On Multiple GPUsHiPEAC ACACES 2022 - 18th International Summer School on Advanced Computer Architecture and Compilation for High-performance Embedded Systems, Jul 2022, Fiuggi, Italy |
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Locality-Aware Scheduling Of Independent Tasks For Runtime SystemsHiPEAC ACACES 2021, Sep 2021, Fiuggi, Italy |
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Memory-Aware Scheduling of Tasks Sharing Data on Multiple GPUsJLESC 2023 -15th JLESC Workshop, Mar 2023, Bordeaux, France. 2023 |
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Memory-Aware Scheduling of Tasks Sharing Data on Multiple GPUs with Dynamic Runtime Systems15th Scheduling for Large Scale Systems Workshop, Jun 2022, Fréjus, France |
Special Issue Proposal for the Parallel Computing Journal: HeteroPar 2016 and HCW 2016 WorkshopsElsevier, 2019 |
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Special issue on Advances in scheduling for large-scale distributed platformsLoris Marchal and Frédéric Vivien. Parallel Computing 37, 11, pp.693-729, 2011 |
Scheduling for Large-Scale SystemsAllen Tucker; Teofilo Gonzalez; Heikki Topi; Jorge Diaz-Herrera. The Computing Handbook - Two-Volume Set, 1, Chapman and Hall/CRC Press, pp.3816, 2014, 9781439898444 |
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Steady-State SchedulingYves Robert and Frederic Vivien. Introduction To Scheduling, Taylor and Francis, 2009 |
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Towards Parallel Transformer-Based Large Language Models for Fast InferenceRR-9573, Inria. 2025, pp.42 |
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Bounding the Flow Time in Online Scheduling with Structured Processing Sets (extended version)[Research Report] RR-9446, INRIA. 2022, pp.1-35 |
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Locality-aware batch scheduling of I/O intensive workloadsRR-9497, ENS Lyon; Inria Bordeaux; Uppsala Universitet. 2022, pp.25 |
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Locality-Aware Scheduling of Independant Tasks for Runtime Systems[Research Report] RR-9394, Inria Grenoble -Rhône-Alpes. 2021, pp.21 |
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Trading Performance for Memory in Sparse Direct Solvers using Low-rank Compression[Research Report] RR-9368, INRIA. 2020 |
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Reliable and energy-aware mapping of streaming series-parallel applications onto hierarchical platforms[Research Report] RR-9346, INRIA. 2020 |
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Optimal Checkpointing Strategies for Iterative Applications[Research Report] RR-9371, Inria - Research Centre Grenoble – Rhône-Alpes. 2020 |
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Robustness of the Young/Daly formula for stochastic iterative applications[Research Report] RR-9332, Inria Grenoble Rhône-Alpes. 2020 |
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Revisiting dynamic DAG scheduling under memory constraints for shared-memory platforms[Research Report] RR-9323, Inria. 2020 |
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Improving mapping for sparse direct solvers: A trade-off between data locality and load balancing[Research Report] RR-9328, Inria Rhône-Alpes. 2020, pp.21 |
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Partitioning tree-shaped task graphs for distributed platforms with limited memory[Research Report] RR-9115, Inria Grenoble Rhône-Alpes. 2019, pp.1-34 |
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Limiting the memory footprint when dynamically scheduling DAGs on shared-memory platforms[Research Report] RR-9231, Inria Grenoble Rhône-Alpes. 2018, pp.1-41 |
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Online Scheduling of Sequential Task Graphs on Hybrid Platforms[Research Report] RR-9150, LIP - ENS Lyon. 2018 |
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Reliability-aware energy optimization for throughput-constrained applications on MPSoC[Research Report] RR-9168, Laboratoire LIP, École Normale Supérieure de Lyon & CNRS & Inria, France; Shanghai Key Lab. of Trustworthy Computing, East China Normal University, China; Georgia Institute of Technology, USA. 2018, pp.1-35 |
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Matching-Based Assignement Strategies for Improving Data Locality of Map Tasks in MapReduce[Research Report] RR-8968, Inria - Research Centre Grenoble – Rhône-Alpes; Inria Bordeaux Sud-Ouest. 2017 |
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Parallel scheduling of DAGs under memory constraints[Research Report] RR-9108, LIP - ENS Lyon. 2017 |
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Minimizing I/Os in Out-of-Core Task Tree Scheduling[Research Report] RR-9025, INRIA. 2017 |
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Low-Cost Approximation Algorithms for Scheduling Independent Tasks on Hybrid Platforms[Research Report] RR-9029, Inria - Research Centre Grenoble – Rhône-Alpes. 2017 |
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Scheduling Series-Parallel Task Graphs to Minimize Peak Memory[Research Report] RR-8975, Inria Grenoble Rhône-Alpes, Université de Grenoble. 2016 |
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Malleable task-graph scheduling with a practical speed-up model[Research Report] RR-8856, ENS de Lyon. 2016 |
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Dynamic memory-aware task-tree scheduling[Research Report] RR-8966, INRIA Grenoble - Rhone-Alpes. 2016 |
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Scheduling malleable task trees[Research Report] RR-8587, INRIA. 2014 |
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Parallel scheduling of task trees with limited memory[Research Report] RR-8606, INRIA. 2014, pp.37 |
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Memory-aware list scheduling for hybrid platforms[Research Report] RR-8461, INRIA. 2014, pp.30 |
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Scheduling Trees of Malleable Tasks for Sparse Linear Algebra[Research Report] 8616, ENS Lyon. 2014 |
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Determining the optimal redistribution[Research Report] RR-8499, INRIA. 2014 |
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Tree traversals with task-memory affinities[Research Report] RR-8226, INRIA. 2013, pp.31 |
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Non-clairvoyant reduction algorithms for heterogeneous platforms[Research Report] RR-8315, INRIA. 2013 |
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Scheduling tree-shaped task graphs to minimize memory and makespan[Research Report] RR-8082, INRIA. 2012, pp.21 |
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Non-Linear Divisible Loads: There is No Free Lunch[Research Report] RR-8170, INRIA. 2012, pp.20 |
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Comparing archival policies for Blue Waters[Research Report] RR-7583, INRIA. 2011 |
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The impact of cache misses on the performance of matrix product algorithms on multicore platforms[Research Report] RR-7456, INRIA. 2010, pp.32 |
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Complexity analysis of matrix products on multicore architectures[Research Report] LIP RR-2008-41, Laboratoire de l'informatique du parallélisme. 2008, 16p |
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Allocating Series of Workflows on Computing Grids[Research Report] RR-6603, INRIA. 2008, pp.31 |
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Who needs a scheduler?[Research Report] LIP RR-2008-34, Laboratoire de l'informatique du parallélisme. 2008, 11p |
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Offline and Online Scheduling of Concurrent Bags-of-Tasks on Heterogeneous Platforms[Research Report] RR-6401, INRIA. 2007, pp.49 |
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Scheduling and data redistribution strategies on star platforms[Research Report] RR-6005, LIP RR-2006-23, INRIA, LIP. 2006, pp.42 |
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VoroNet: A scalable object network based on Voronoi tessellations[Research Report] RR-5833, LIP RR-2006-11, INRIA, LIP. 2006, 2+21 p |
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Scheduling divisible loads with return messages on heterogeneous master-worker platforms[Research Report] LIP RR-2005-21, Laboratoire de l'informatique du parallélisme. 2005, 2+19p |
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Scheduling multiple bags of tasks on heterogeneous master- worker platforms: centralized versus distributed solutionsRR-5739, INRIA. 2005, pp.35 |
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Scheduling network requests with transmission window[Research Report] LIP RR-2005-32, Laboratoire de l'informatique du parallélisme. 2005, 2+13p |
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FIFO scheduling of divisible loads with return messages under the one-port modelRR-5738, INRIA. 2005, pp.25 |
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Optimizing Network Resource Sharing in Grids[Research Report] RR-5523, LIP RR 2005-10, INRIA, LIP. 2005 |
Pipelining broadcasts on heterogeneous platforms under the one-port model[Research Report] RR-2004-32, 2004 |
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Complexity results and heuristics for pipelined multicast operations on heterogeneous platforms[Research Report] RR-5123, LIP RR-2004-07, INRIA, LIP. 2004 |
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Assessing the impact and limits of steady-state scheduling for mixed task and data parallelism on heterogeneous platforms[Research Report] RR-5198, LIP RR-2004-20, INRIA, LIP. 2004, pp.44 |
Steady-State Scheduling on Heterogeneous Clusters: Why and How?[Research Report] 2004-11, 2004 |
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A realistic network/application model for scheduling divisible loads on large-scale platforms[Research Report] RR-5197, LIP RR-2004-21, INRIA, LIP. 2004, pp.22 |
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Pipelining Broadcasts on Heterogeneous Platforms under the One-Port Model.[Research Report] LIP RR-2004-32, Laboratoire de l'informatique du parallélisme. 2004, 2+22p |
Broadcast Trees for Heterogeneous Platforms[Research Report] RR-2004-46, 2004 |
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Steady-State Scheduling on Heterogeneous Clusters: Why and How?.[Research Report] LIP RR-2004-11, Laboratoire de l'informatique du parallélisme. 2004, 2+11p |
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Independent and Divisible Task Scheduling on Heterogeneous Star-shaped Platforms with Limited Memory[Research Report] RR-5196, LIP RR-2004-22, INRIA, LIP. 2004, pp.28 |
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Broadcast Trees for Heterogeneous Platforms.[Research Report] Laboratoire de l'informatique du parallélisme; LIP RR-2004-46. 2004, 2+18p |
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Optimizing the steady-state throughput of scatter and reduce operationson heterogeneous platformsRR-4872, INRIA. 2003 |
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Optimizing the steady-state throughput of Broadcasts on heterogeneous platformsRR-4871, INRIA. 2003 |
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Steady-state scheduling of task graphs on heterogeneous computing platforms[Research Report] RR-4870, LIP RR-2003-29, INRIA, LIP. 2003 |
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Optimizing the steady-state throughput of scatter and reduce operations on heterogeneous platforms.[Research Report] LIP RR-2003-33, Laboratoire de l'informatique du parallélisme. 2003, 2+26p |
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A Network Model for Simulation of Grid Application[Research Report] RR-4596, LIP RR-2002-40, INRIA, LIP. 2002 |
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Communications collectives et ordonnancement en régime permanent sur plates-formes hétérogènesRéseaux et télécommunications [cs.NI]. Ecole normale supérieure de lyon - ENS LYON, 2006. Français. ⟨NNT : ⟩ |
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Memory and data aware schedulingDistributed, Parallel, and Cluster Computing [cs.DC]. École Normale Supérieure de Lyon, 2018 |