2016
Conference article
Open Access
An holistic approach for high-level programming of next-generation data-intensive applications targeting distributed heterogeneous computing environment
Carlini E., Dazzi P., Mordacchini M.
General Environmental Science High-level Programming Models Cloud Computing Cloud Federation Data-intensive Applications General Earth and Planetary Sciences Resource Management
Data-intensive applications are one of the largest customers of high throughput computing environments. As clearly shown by the BigData raise, there is a widely recognised urge for processing large amount of data, universallyconsidered the "new oil", from which to extract wisdom, knowledge and, more in general, information of very different kinds, ranging from commercial to financial, from medical to political hints. This extreme intrinsic richness andheterogeneity of data is paired with the extreme complexity in its storing and processing.
Source: Cf 2016 - Cloud Forward Conference, pp. 131–134, Madrid, Spain, 18-20/10/2016
1. Coutinho, J., Pell, O., ONeill, E., Sanders, P., McGlone, J., Grigoras, P., et al. Harness project: Managing heterogeneous compute resources for a cloud platform. In: Proc. the 10th International Symposium on Applied Reconfigurable Computing (ARC). 2014, .
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4. Satyanarayanan, M., Bahl, P., Caceres, R., Davies, N.. The case for vm-based cloudlets in mobile computing. Pervasive Computing, IEEE 2009;8(4):14-23.
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6. Anastasi, G.F., Cassara`, P., Dazzi, P., Gotta, A., Mordacchini, M., Passarella, A.. A hybrid cross-entropy cognitive-based algorithm for resource allocation in cloud environments. In: 2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems. IEEE; 2014, p. 11-20.
7. Aldinucci, M., Campa, S., Danelutto, M., Kilpatrick, P., Torquati, M.. Pool evolution: a domain specific parallel pattern. In: Proc. of the 7th Intl. Symposium on High-level Parallel Programming and Applications (HLPP), Amsterdam. 2014, .
8. Carlini, E., Coppola, M., Dazzi, P., Ricci, L., Righetti, G.. Cloud federations in contrail. In: Euro-Par 2011: Parallel Processing Workshops. Springer; 2011, p. 159-168.
9. Danelutto, M., Pasin, M., Vanneschi, M., Dazzi, P., Laforenza, D., Presti, L.. Pal: exploiting java annotations for parallelism. In: Achievements in European Research on Grid Systems. Springer US; 2008, .
10. Danelutto, M., Dazzi, P.. A java/jini framework supporting stream parallel computations. In: et al., G.R.J., editor. Proceedings of the International Conference ParCo 2005. ISBN 3-00-017352-8; 2005, .
This work has been partly supported by BASMATI project H2020 G.A. no. 723131 and ICT R&D program of
Korean Ministry of Science, ICT and Future Planning no. R0115-16-0001 1. Dazzi P, Felber P, Leonini L, Mordacchini M, Perego R, Rajman M, Rivière É. Peer-to-peer clustering of web-browsing users. In Proceedings
of LSDS-IR; 2009. 2. Baraglia R, Dazzi P, Mordacchini M, Ricci L, Alessi L. Group: A gossip based building community protocol. In Balandin S, Koucheryavy Y,
Hu H, editors. Smart Spaces and Next Generation Wired/Wireless Networking, Heidelberg, 2011. Lecture Notes in Computer Science,
Volume 6869. Springer; p. 496-507. 3. Conti M, Mordacchini M, Passarella A. Design and performance evaluation of data dissemination systems for opportunistic networks based on
cognitive heuristics. ACM Transactions on Autonomous and Adaptive Systems, 2013;8:3, p. 12:1-12:32. 4. Coutinho J, Pell O, ONeill E, Sanders E, McGlone J, Grigoras P, Luc W, Ragusa C. Harness project: Managing heterogeneous compute
Architectures, Tools, and Applications, Heidelberg, 2014. Lecture Notes in Computer Science, Volume 8405. Springer; p. 324-329. 5. Satyanarayanan M, Bahl P, Caceres R, Davies N. The case for vm-based cloudlets in mobile computing. Pervasive Computing 2009;8:4. 6. Stojmenovic I. Fog computing: a cloud to the ground support for smart things and machine-to-machine networks. In the 2014 Australasian
Conference on Telecommunication Networks and Applications Conference. Southbank. IEEE; p. 117-122. 7. Aldinucci M, Campa S, Danelutto M, Kilpatrick P, Torquati M. Pool evolution: a domain specific parallel pattern. In the 7th International
Symposium on High-level Parallel Programming and Applications. Amsterdam. 2014. 8. Carlini E, Coppola M, Dazzi P, Ricci L, Righetti G. Cloud federations in contrail. In Alexander M et al., editors. Euro-Par 2011: Parallel
Processing Workshops, 2011. Lecture Notes in Computer Science, Volume 7155. Springer; p. 159-168. 9. Danelutto M, Pasin M, Vanneschi M, Dazzi P, Laforenza D, Presti L. Pal: exploiting java annotations for parallelism. In Gorlatch S, Bubak M,
Priol T, editors. Achievements in European Research on Grid Systems, 2008. Springer; p. 83-96. 10. Danelutto M, Dazzi P. A Java/Jini framework supporting stream parallel computations. ParCo 2005. Central Institute for Applied
Mathematics, Jülich: Málaga, 2005; p. 681-688.
2. Conti, M., Mordacchini, M., Passarella, A.. Design and performance evaluation of data dissemination systems for opportunistic networks based on cognitive heuristics. ACM Transactions on Autonomous and Adaptive Systems (TAAS) 2013;8(3):12.
3. Marzolla, M., Mordacchini, M., Orlando, S.. A p2p resource discovery system based on a forest of trees. In: 17th International Workshop on Database and Expert Systems Applications (DEXA'06). IEEE; 2006, p. 261-265.
4. Satyanarayanan, M., Bahl, P., Caceres, R., Davies, N.. The case for vm-based cloudlets in mobile computing. Pervasive Computing, IEEE 2009;8(4):14-23.
5. Stojmenovic, I.. Fog computing: a cloud to the ground support for smart things and machine-to-machine networks. In: Telecommunication Networks and Applications Conference (ATNAC), 2014 Australasian. IEEE; 2014, p. 117-122.
6. Anastasi, G.F., Cassara`, P., Dazzi, P., Gotta, A., Mordacchini, M., Passarella, A.. A hybrid cross-entropy cognitive-based algorithm for resource allocation in cloud environments. In: 2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems. IEEE; 2014, p. 11-20.
7. Aldinucci, M., Campa, S., Danelutto, M., Kilpatrick, P., Torquati, M.. Pool evolution: a domain specific parallel pattern. In: Proc. of the 7th Intl. Symposium on High-level Parallel Programming and Applications (HLPP), Amsterdam. 2014, .
8. Carlini, E., Coppola, M., Dazzi, P., Ricci, L., Righetti, G.. Cloud federations in contrail. In: Euro-Par 2011: Parallel Processing Workshops. Springer; 2011, p. 159-168.
9. Danelutto, M., Pasin, M., Vanneschi, M., Dazzi, P., Laforenza, D., Presti, L.. Pal: exploiting java annotations for parallelism. In: Achievements in European Research on Grid Systems. Springer US; 2008, .
10. Danelutto, M., Dazzi, P.. A java/jini framework supporting stream parallel computations. In: et al., G.R.J., editor. Proceedings of the International Conference ParCo 2005. ISBN 3-00-017352-8; 2005, .
This work has been partly supported by BASMATI project H2020 G.A. no. 723131 and ICT R&D program of
Korean Ministry of Science, ICT and Future Planning no. R0115-16-0001 1. Dazzi P, Felber P, Leonini L, Mordacchini M, Perego R, Rajman M, Rivière É. Peer-to-peer clustering of web-browsing users. In Proceedings
of LSDS-IR; 2009. 2. Baraglia R, Dazzi P, Mordacchini M, Ricci L, Alessi L. Group: A gossip based building community protocol. In Balandin S, Koucheryavy Y,
Hu H, editors. Smart Spaces and Next Generation Wired/Wireless Networking, Heidelberg, 2011. Lecture Notes in Computer Science,
Volume 6869. Springer; p. 496-507. 3. Conti M, Mordacchini M, Passarella A. Design and performance evaluation of data dissemination systems for opportunistic networks based on
cognitive heuristics. ACM Transactions on Autonomous and Adaptive Systems, 2013;8:3, p. 12:1-12:32. 4. Coutinho J, Pell O, ONeill E, Sanders E, McGlone J, Grigoras P, Luc W, Ragusa C. Harness project: Managing heterogeneous compute
Architectures, Tools, and Applications, Heidelberg, 2014. Lecture Notes in Computer Science, Volume 8405. Springer; p. 324-329. 5. Satyanarayanan M, Bahl P, Caceres R, Davies N. The case for vm-based cloudlets in mobile computing. Pervasive Computing 2009;8:4. 6. Stojmenovic I. Fog computing: a cloud to the ground support for smart things and machine-to-machine networks. In the 2014 Australasian
Conference on Telecommunication Networks and Applications Conference. Southbank. IEEE; p. 117-122. 7. Aldinucci M, Campa S, Danelutto M, Kilpatrick P, Torquati M. Pool evolution: a domain specific parallel pattern. In the 7th International
Symposium on High-level Parallel Programming and Applications. Amsterdam. 2014. 8. Carlini E, Coppola M, Dazzi P, Ricci L, Righetti G. Cloud federations in contrail. In Alexander M et al., editors. Euro-Par 2011: Parallel
Processing Workshops, 2011. Lecture Notes in Computer Science, Volume 7155. Springer; p. 159-168. 9. Danelutto M, Pasin M, Vanneschi M, Dazzi P, Laforenza D, Presti L. Pal: exploiting java annotations for parallelism. In Gorlatch S, Bubak M,
Priol T, editors. Achievements in European Research on Grid Systems, 2008. Springer; p. 83-96. 10. Danelutto M, Dazzi P. A Java/Jini framework supporting stream parallel computations. ParCo 2005. Central Institute for Applied
Mathematics, Jülich: Málaga, 2005; p. 681-688.
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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:359363,
title = {An holistic approach for high-level programming of next-generation data-intensive applications targeting distributed heterogeneous computing environment},
author = {Carlini E. and Dazzi P. and Mordacchini M.},
doi = {10.1016/j.procs.2016.08.290},
booktitle = {Cf 2016 - Cloud Forward Conference, pp. 131–134, Madrid, Spain, 18-20/10/2016},
year = {2016}
}
0000-0003-3643-5404CNR ExploRA
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