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The Workshop on Parallel and Distributed Data Mining is an international forum which brings together researchers and practitioners working on different high-performance aspects of data mining algorithms, enabling novel applications. Data mining techniques and algorithms to process huge amount of data in order to extract useful and interesting information have become popular in many different contexts. Algorithms are required to make sense of data automatically and in efficient ways. Nonetheless, even though sequential computer systems performance is improving, they are not suitable to keep up with the increase in the demand for data mining applications and the data size. Moreover, the main memory of sequential systems may not be enough to hold all the data related to current applications. Therefore, there is an increasing interest in the design and implementation of parallel data mining algorithms. On parallel computers, by exploiting the vast aggregate main memory and processing power of processors and accelerators, parallel algorithms can easily address both the running time and memory requirement issues. Anyway, parallelizing existing algorithms in order to achieve good performance and scalability with regard to massive datasets is not trivial. Indeed, it is of paramount importance a good data organization and decomposition strategy in order to balance the workload while minimizing data dependences. Another concern is related to minimizing synchronization and communication overhead. Finally, I/O costs should be minimized as well. The Workshop will allow exchanging ideas and results related to on-going research, focusing on high-performance aspects of data mining algorithms and applications. Creating breakthrough parallel algorithms for high-performance data mining applications requires addressing several key computing problems which may lead to novel solutions and new insights in interdisciplinary applications. The focus of the workshop is on all forms of advances in high-performance data mining algorithms and applications, and related topics.
The WPDM Workshop topics include (but are not limited to) the following:
- Parallel data mining algorithms using MPI and/or OpenMP
- Parallel data mining algorithms targeting GPUs and many-cores accelerators
- Parallel data mining applications exploiting FPGA
- Distributed data mining algorithms
- Benchmarking and performance studies of high-performance data mining applications
- Novel programming paradigms to support high-performance computing for data mining
- Performance models for high-performance data mining applications and middleware
- Programming models, tools, and environments for high-performance computing in data mining
- Caching, streaming, pipelining, and other optimization techniques for data management in high-performance computing for data mining
INSTRUCTIONS FOR PAPER SUBMISSIONS
You are invited to submit original and unpublished research works on above topics. Submitted papers must not have been published or simultaneously submitted elsewhere. The submitted paper must be between 10 to 16 pages long and formatted according to the Springer LNCS (Lecture Notes in Computer Science) rules, Guidelines and templates can be found at the url http://www.springer.com/it/computer-science/lncs/conference-proceedings-guidelines
To submit a paper, please connect to the Submission site from the link available at the ICCSA 2019 web site: http://ess.iccsa.org.
Only papers submitted through the electronic system and strictly adhering to the relevant format will be considered for reviewing and publication. Please pay attention, when submitting your contribution to the workshop, to select the right entry in the listbox shown in the submission form.
CONFERENCE POLICY
By submitting the paper to ICCSA conference, all authors agree to abide by all ICCSA conference paper submission, publication and presentation policies. Namely, authors confirm that the work is original, has not appeared in literature in any form in the past and will not be submitted to any other venue concurrently with ICCSA submission or until it appears in ICCSA proceedings (in the case of acceptance). Furthermore, upon paper acceptance, authors agree to transfer copyright on the accepted paper to ICCSA, and one of the authors will register the paper and present the paper at the event. No paper withdrawals can be accepted after Conference pre-registration date or within three months of the actual event, whichever date comes first. Paper withdrawal request can be only accepted in writing through email, letter or fax to conference organizers. The conference has no responsibility for any intentional or accidental misuse, misinterpretation, or failure to follow above rules and conditions and holds no legal, civil or other responsibility for opinions, content or utilization of any methods/algorithms expressed in the Conference Proceedings.
If you have any questions about paper submission or the workshop, please contact the workshop organisers.
IMPORTANT DATES
March 3, 2019: Deadline for paper submission
March 31, 2019: Notification of Acceptance.
May 8, 2019: Early-bird Registration ends.
May 8, 2019: Submission deadline for the final version of the Papers
July 1-4, 2019: ICCSA 2019 Conference
WORKSHOP ORGANIZERS
Massimo Cafaro
University of Salento, Italy
Phone: +39 0832 297371
Fax: +39 0832 297235
Email: [email protected]
Italo Epicoco
University of Salento, Italy
Phone: +39 0832 297235
Fax: +39 0832 297235
Email: [email protected]
Marco Pulimeno
University of Salento, Italy
Phone: +39 0832 297371
Fax: +39 0832 297235
Email: [email protected]
Giovanni Aloisio
University of Salento & Euro Mediterranean Center on Climate Change Foundation, Italy
Phone: +39 334 6501704
Fax: +39 0832 297235
Email: [email protected]
All submitted papers will be reviewed by the workshop technical program committee members.
International Program Committee:
Alfredo Cuzzocrea, University of Trieste and ICAR-CNR, Italy
Bronis R. de Supinski, Lawrence Livermore National Laboratory, USA
Giuseppe Di Fatta, University of Reading, UK
Ann Gordon-Ross, University of Florida, USA
Kenli Li, Hunan University, China
Donato Malerba, University of Bari, Italy
Barbara Masucci, University of Salerno, Italy
Mitsunori Ogihara, University of Miami, USA
Takahiko Shintani, The University of Electro-Communications , Japan
Domenico Talia, University of Calabria, Italy
Paolo Trunfio, University of Calabria, Italy
Jeffrey D. Ullman, Stanford University, USA
Laurence T. Yang, St Francis Xavier University, Canada
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