Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Partnerships and Cooperations
Dissemination
Bibliography
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Bibliography

Major publications by the team in recent years
[1]
N. 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
[2]
A. 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
[3]
B. 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
[4]
M. 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
[5]
M. 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
[6]
M. 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
[7]
M. 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
[8]
M. 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
[9]
M. 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
[10]
P. 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
[11]
B. 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/
[12]
B. 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
[13]
R. 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
Publications of the year

Doctoral Dissertations and Habilitation Theses

[14]
N. Cheriere.
Towards Malleable Distributed Storage Systems: From Models to Practice, École normale supérieure de Rennes, November 2019.
https://tel.archives-ouvertes.fr/tel-02376032
[15]
A. Costan.
From Big Data to Fast Data: Efficient Stream Data Management, ENS Rennes, March 2019, Habilitation à diriger des recherches.
https://hal.archives-ouvertes.fr/tel-02059437

Invited Conferences

[16]
G. Antoniu, A. Costan, O.-C. Marcu.
ZettaFlow: Towards High-Performance ML-based Analytics across the Digital Continuum, in: BDEC2 2019 - Workshop on Big Data and Extreme-scale Computing, San Diego, United States, San Diego Supercomputing Center, October 2019, 4 p.
https://hal.archives-ouvertes.fr/hal-02428382
[17]
G. Antoniu, A. Costan, O.-C. Marcu, M. Hernández-Pérez, N. Stojanovic.
Towards a demonstrator of the Sigma Data Processing Architecture for BDEC 2, in: BDEC2 2019 - Workshop on Big Data and Extreme-scale Computing, Poznan, Poland, Poznan Supercomputing and Networking Center, May 2019, 4 p.
https://hal.archives-ouvertes.fr/hal-02428391

International Conferences with Proceedings

[18]
N. Cheriere, M. Dorier, G. Antoniu.
Is it Worth Relaxing Fault Tolerance to Speed Up Decommission in Distributed Storage Systems?, in: CCGrid 2019 - IEEE/ACM International Symposium in Cluster, Cloud, and Grid Computing, Larnaca, Cyprus, IEEE, May 2019, pp. 1-10. [ DOI : 10.1109/CCGRID.2019.00024 ]
https://hal.archives-ouvertes.fr/hal-02116727
[19]
P. Silva, A. Costan, G. Antoniu.
Investigating Edge vs. Cloud Computing Trade-offs for Stream Processing, in: BigData 2019 - IEEE International Conference on Big Data, Los Angeles, United States, IEEE, December 2019.
https://hal.archives-ouvertes.fr/hal-02415684
[20]
P. Silva, A. Costan, G. Antoniu.
Towards a Methodology for Benchmarking Edge Processing Frameworks, in: IPDPSW 2019 - IEEE International Parallel and Distributed Processing Symposium Workshops, Rio de Janeiro, Brazil, IEEE, May 2019, pp. 904-907. [ DOI : 10.1109/IPDPSW.2019.00149 ]
https://hal.inria.fr/hal-02310154

Other Publications

[21]
K. Fauvel, D. Balouek-Thomert, D. Melgar, P. Silva, A. Simonet, G. Antoniu, A. Costan, V. Masson, M. Parashar, I. Rodero, A. Termier.
A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning, November 2019, working paper or preprint.
https://hal.archives-ouvertes.fr/hal-02373429
References in notes
[22]
Amazon Elastic Map-Reduce (EMR), 2017.
https://aws.amazon.com/emr/
[23]
Digital Single Market, 2015.
https://ec.europa.eu/digital-single-market/en/digital-single-market/
[24]
European Exascale Software Initiative, 2013.
http://www.eesi-project.eu/
[25]
The European Technology Platform for High-Performance Computing, 2012.
http://www.etp4hpc.eu/
[26]
European Cloud Strategy, 2012.
https://ec.europa.eu/digital-single-market/en/european-cloud-computing-strategy/
[27]
Apache Flink, 2016.
http://flink.apache.org/
[28]
International Exascale Software Program, 2011.
http://www.exascale.org/iesp/
[29]
Scientific challenges of the Inria Rennes-Bretagne Atlantique research centre, 2016.
https://www.inria.fr/centre-inria-rennes-bretagne-atlantique/
[30]
Inria's strategic plan "Towards Inria 2020", 2016.
https://www.inria.fr/recherche-innovation/
[31]
Joint Laboratory for Extreme Scale Computing (JLESC), 2017.
https://jlesc.github.io/
[32]
Apache Spark, 2017.
http://spark.apache.org/
[33]
Storm, 2014.
http://storm.apache.org/
[34]
T. 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.
[35]
J. Dean, S. Ghemawat.
MapReduce: simplified data processing on large clusters, in: Communications of the ACM, 2008, vol. 51, no 1, pp. 107–113.