Bibliography
Major publications by the team in recent years
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1N. Cheriere, M. Dorier.
Design and Evaluation of Topology-aware Scatter and AllGather Algorithms for Dragonfly Networks, November 2016, Supercomputing 2016, Poster.
https://hal.inria.fr/hal-01400271 -
2A. Costan, R. Tudoran, G. Antoniu, G. Brasche.
TomusBlobs: Scalable Data-intensive Processing on Azure Clouds, in: CCPE - Concurrency and Computation: Practice and Experience, May 2013.
https://hal.inria.fr/hal-00767034 -
3B. Da Mota, R. Tudoran, A. Costan, G. Varoquaux, G. Brasche, P. J. Conrod, H. Lemaitre, T. Paus, M. Rietschel, V. Frouin, J.-B. Poline, G. Antoniu, B. Thirion.
Machine Learning Patterns for Neuroimaging-Genetic Studies in the Cloud, in: Frontiers in Neuroinformatics, April 2014, vol. 8.
https://hal.inria.fr/hal-01057325 -
4M. Dorier, G. Antoniu, F. Cappello, M. Snir, L. Orf.
Damaris: How to Efficiently Leverage Multicore Parallelism to Achieve Scalable, Jitter-free I/O, in: CLUSTER - IEEE International Conference on Cluster Computing, Beijing, China, IEEE, September 2012.
https://hal.inria.fr/hal-00715252 -
5M. Dorier, G. Antoniu, F. Cappello, M. Snir, R. Sisneros, O. Yildiz, S. Ibrahim, T. Peterka, L. Orf.
Damaris: Addressing Performance Variability in Data Management for Post-Petascale Simulations, in: ACM Transactions on Parallel Computing, 2016.
https://hal.inria.fr/hal-01353890 -
6M. Dorier, G. Antoniu, R. Ross, D. Kimpe, S. Ibrahim.
CALCioM: Mitigating I/O Interference in HPC Systems through Cross-Application Coordination, in: IPDPS - International Parallel and Distributed Processing Symposium, Phoenix, United States, May 2014.
https://hal.inria.fr/hal-00916091 -
7M. Dorier, M. Dreher, T. Peterka, G. Antoniu, B. Raffin, J. M. Wozniak.
Lessons Learned from Building In Situ Coupling Frameworks, in: ISAV 2015 - First Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (held in conjunction with SC15), Austin, United States, November 2015. [ DOI : 10.1145/2828612.2828622 ]
https://hal.inria.fr/hal-01224846 -
8M. Dorier, S. Ibrahim, G. Antoniu, R. Ross.
Omnisc'IO: A Grammar-Based Approach to Spatial and Temporal I/O Patterns Prediction, in: SC14 - International Conference for High Performance Computing, Networking, Storage and Analysis, New Orleans, United States, IEEE, ACM, November 2014.
https://hal.inria.fr/hal-01025670 -
9M. Dorier, S. Ibrahim, G. Antoniu, R. Ross.
Using Formal Grammars to Predict I/O Behaviors in HPC: the Omnisc'IO Approach, in: TPDS - IEEE Transactions on Parallel and Distributed Systems, October 2015. [ DOI : 10.1109/TPDS.2015.2485980 ]
https://hal.inria.fr/hal-01238103 -
10P. Matri, A. Costan, G. Antoniu, J. Montes, M. S. Pérez.
Týr: Blob Storage Meets Built-In Transactions, in: IEEE ACM SC16 - The International Conference for High Performance Computing, Networking, Storage and Analysis 2016, Salt Lake City, United States, November 2016.
https://hal.inria.fr/hal-01347652 -
11B. Nicolae, G. Antoniu, L. Bougé, D. Moise, A. Carpen-Amarie.
BlobSeer: Next-Generation Data Management for Large-Scale Infrastructures, in: JPDC - Journal of Parallel and Distributed Computing, February 2011, vol. 71, no 2, pp. 169–184.
http://hal.inria.fr/inria-00511414/en/ -
12B. Nicolae, J. Bresnahan, K. Keahey, G. Antoniu.
Going Back and Forth: Efficient Multi-Deployment and Multi-Snapshotting on Clouds, in: HPDC 2011 - The 20th International ACM Symposium on High-Performance Parallel and Distributed Computing, San José, CA, United States, June 2011.
http://hal.inria.fr/inria-00570682/en -
13R. Tudoran, A. Costan, G. Antoniu.
OverFlow: Multi-Site Aware Big Data Management for Scientific Workflows on Clouds, in: IEEE Transactions on Cloud Computing, June 2015. [ DOI : 10.1109/TCC.2015.2440254 ]
https://hal.inria.fr/hal-01239128
Doctoral Dissertations and Habilitation Theses
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14T.-D. Phan.
Energy-efficient Straggler Mitigation for Big Data Applications on the Clouds, ENS Rennes, November 2017.
https://tel.archives-ouvertes.fr/tel-01669469 -
15L. E. Pineda Morales.
Efficient support for data-intensive scientific workflows on geo-distributed clouds, INSA de Rennes, May 2017.
https://tel.archives-ouvertes.fr/tel-01645434 -
16O. Yildiz.
Efficient Big Data Processing on Large-Scale Shared Platforms: Managing I/Os and Failures, ENS Rennes, December 2017.
https://tel.archives-ouvertes.fr/tel-01671413
Articles in International Peer-Reviewed Journals
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17P. Matri, M. S. Pérez, A. Costan, L. Bougé, G. Antoniu.
Keeping up with storage: Decentralized, write-enabled dynamic geo-replication, in: Future Generation Computer Systems, June 2017, pp. 1-19. [ DOI : 10.1016/j.future.2017.06.009 ]
https://hal.inria.fr/hal-01617658
International Conferences with Proceedings
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18N. Cheriere, G. Antoniu.
How Fast Can One Scale Down a Distributed File System?, in: BigData 2017 - IEEE International Conference on Big Data, Boston, United States, December 2017.
https://hal.archives-ouvertes.fr/hal-01644928 -
19J. Liu, L. Pineda-Morales, E. Pacitti, A. Costan, P. Valduriez, G. Antoniu, M. Mattoso.
Efficient Scheduling of Scientific Workflows using Hot Metadata in a Multisite Cloud, in: BDA: Conférence sur la Gestion de Données — Principes, Technologies et Applications, Nancy, France, November 2017, 13 p.
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01620231 -
20O.-C. Marcu, A. Costan, G. Antoniu, M. S. Pérez-Hernández, R. Tudoran, S. Bortoli, B. Nicolae.
Towards a Unified Storage and Ingestion Architecture for Stream Processing, in: Second Workshop on Real-time & Stream Analytics in Big Data Colocates with the 2017 IEEE International Conference on Big Data, Boston, United States, IEEE, December 2017, pp. 1-6.
https://hal.inria.fr/hal-01649207 -
21O.-C. Marcu, R. Tudoran, B. Nicolae, A. Costan, G. Antoniu, M. S. Pérez-Hernández.
Exploring Shared State in Key-Value Store for Window-Based Multi-Pattern Streaming Analytics, in: Workshop on the Integration of Extreme Scale Computing and Big Data Management and Analytics in conjunction with IEEE/ACM CCGrid 2017, Madrid, Spain, May 2017.
https://hal.inria.fr/hal-01530744 -
22P. Matri, Y. Alforov, A. Brandon, M. Kuhn, P. Carns, T. Ludwig.
Could Blobs Fuel Storage-Based Convergence Between HPC and Big Data?, in: CLUSTER 2017 - IEEE International Conference on Cluster Computing, Honolulu, United States, September 2017, pp. 81 - 86. [ DOI : 10.1109/CLUSTER.2017.63 ]
https://hal.inria.fr/hal-01617655 -
23T.-D. Phan, S. Ibrahim, A. C. Zhou, G. Aupy, G. Antoniu.
Energy-Driven Straggler Mitigation in MapReduce, in: Euro-Par'17 - 23rd International European Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain, August 2017.
https://hal.inria.fr/hal-01560044 -
24Y. Taleb, S. Ibrahim, G. Antoniu, T. Cortes.
An Empirical Evaluation of How The Network Impacts The Performance and Energy Efficiency in RAMCloud, in: Workshop on the Integration of Extreme Scale Computing and Big Data Management and Analytics in conjunction with IEEE/ACM CCGrid 2017, Madrid, Spain, May 2017.
https://hal.inria.fr/hal-01376923 -
25Y. Taleb, S. Ibrahim, G. Antoniu, T. Cortes.
Characterizing Performance and Energy-Efficiency of The RAMCloud Storage System, in: The 37th IEEE International Conference on Distributed Computing Systems (ICDCS 2017), Atlanta, United States, June 2017.
https://hal.inria.fr/hal-01496959 -
26O. Yildiz, A. C. Zhou, S. Ibrahim.
Eley: On the Effectiveness of Burst Buffers for Big Data Processing in HPC systems, in: Cluster'17-2017 IEEE International Conference on Cluster Computing, Hawaii, United States, September 2017.
https://hal.inria.fr/hal-01570737
Internal Reports
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27O.-C. Marcu, A. Costan, G. Antoniu, M. S. Pérez-Hernández.
Kera: A Unified Storage and Ingestion Architecture for Efficient Stream Processing, Inria Rennes - Bretagne Atlantique, June 2017, no RR-9074.
https://hal.inria.fr/hal-01532070
Other Publications
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28P. Le Noac'h, A. Costan, L. Bougé.
A Performance Evaluation of Apache Kafka in Support of Big Data Streaming Applications, December 2017, IEEE Big Data 2017, Poster.
https://hal.archives-ouvertes.fr/hal-01647229 -
29Y. Taleb, R. Stutsman, G. Antoniu, T. Cortes.
Tailwind: fast and atomic RDMA-based replication, January 2018, working paper or preprint.
https://hal.inria.fr/hal-01676502
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30Amazon Elastic Map-Reduce (EMR), 2017.
https://aws.amazon.com/emr/ -
31The Decaf Project, 2017.
https://bitbucket.org/tpeterka1/decaf -
32Digital Single Market, 2015.
https://ec.europa.eu/digital-single-market/en/digital-single-market -
33European Exascale Software Initiative, 2013.
http://www.eesi-project.eu -
34The European Technology Platform for High-Performance Computing, 2012.
http://www.etp4hpc.eu -
35European Cloud Strategy, 2012.
https://ec.europa.eu/digital-single-market/en/european-cloud-computing-strategy -
36Apache Flink, 2016.
http://flink.apache.org -
37International Exascale Software Program, 2011.
http://www.exascale.org/iesp/Main_Page -
38Scientific challenges of the Inria Rennes-Bretagne Atlantique research centre, 2016.
https://www.inria.fr/en/centre/rennes/research -
39Inria's strategic plan "Towards Inria 2020", 2016.
https://www.inria.fr/en/institute/strategy/strategic-plan -
40Joint Laboratory for Extreme Scale Computing (JLESC), 2017.
https://jlesc.github.io -
41Apache Spark, 2017.
http://spark.apache.org -
42Storm, 2014.
http://storm-project.net/ -
43The FlowVR Project, 2014.
http://flowvr.sourceforge.net/ -
44T. Akidau, A. Balikov, K. Bekiroğlu, S. Chernyak, J. Haberman, R. Lax, S. McVeety, D. Mills, P. Nordstrom, S. Whittle.
MillWheel: fault-tolerant stream processing at internet scale, in: Proceedings of the VLDB Endowment, 2013, vol. 6, no 11, pp. 1033–1044. -
45J. Dean, S. Ghemawat.
MapReduce: simplified data processing on large clusters, in: Communications of the ACM, 2008, vol. 51, no 1, pp. 107–113. -
46S. Wilde, M. Hategan, J. M. Wozniak, B. Clifford, D. Katz, I. T. Foster.
Swift: A language for distributed parallel scripting, in: Parallel Computing, 2011, vol. 37, no 9, pp. 633–652.
http://dx.doi.org/10.1016/j.parco.2011.05.005