-------- Forwarded Message -------- Subject: [computational.science] The Third International Workshop on Parallel and Distributed Data Mining (WPDM 2019) Date: Sat, 26 Jan 2019 15:25:39 +0100 From: Massimo CAFARO massimo.cafaro@unisalento.it To: DMANET ML dmanet@zpr.uni-koeln.de, COMPUTATIONAL SCIENCE ML computational.science@lists.iccsa.org, CSE ML cse-cfp@cse.stfx.ca, HPC Announce ML hpc-announce@mcs.anl.gov, CONCURRENCY ML concurrency@cwi.nl, tcbd@comsoc.org tcbd@COMSOC.ORG, SIAM ML siam-sc@siam.org, INFORMATICS EUROPE ML announce@informatics-europe.org, DBWORLD ML dbworld@cs.wisc.edu, TCSC ML tcsc@cse.stfx.ca

WPDM 2019

The Third International Workshop on Parallel and Distributed Data Mining (WPDM 2019) http://sara.unisalento.it/~cafaro/WPDM2019/

CALL FOR PAPERS

The Third Workshop on Parallel and Distributed Data Mining (WPDM 2019) will be held in conjunction with The 19th International Conference on Computational Science and Its Applications (ICCSA 2019), http://www.iccsa.org

Saint Petersburg University, Saint Petersburg, Russia July 1-4 2019

Final submission Deadline: February 17, 2019

SCOPE AND OBJECTIVES

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 an d 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-guid...

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

February 17, 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: massimo.cafaro@unisalento.it

Italo Epicoco University of Salento, Italy Phone: +39 0832 297235 Fax: +39 0832 297235 Email: italo.epicoco@unisalento.it

Marco Pulimeno University of Salento, Italy Phone: +39 0832 297371 Fax: +39 0832 297235 Email: marco.pulimeno@unisalento.it

Giovanni Aloisio University of Salento & Euro Mediterranean Center on Climate Change Foundation, Italy Phone: +39 334 6501704 Fax: +39 0832 297235 Email: giovanni.aloisio@unisalento.it

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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Massimo Cafaro, Ph.D. Associate Professor Dept. of Engineering for Innovation University of Salento, Lecce, Italy Via per Monteroni 73100 Lecce, Italy Voice/Fax +39 0832 297371 Web http://sara.unisalento.it/~cafaro E-mail massimo.cafaro@unisalento.it cafaro@ieee.org cafaro@acm.org

CMCC Foundation Euro-Mediterranean Center on Climate Change Via Augusto Imperatore, 16 - 73100 Lecce massimo.cafaro@cmcc.it

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