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Two Research Fellow Positions at NTU Singapore on Green Data Center
by Tan Rui (Asst Prof) 10 Dec '17

10 Dec '17

Two Research Fellow positions with competitive remuneration are immediately available at School of Computer Science and Engineering (SCSE), Nanyang Technological University (NTU). The positions are part of a research project under Singapore’s strategic Green Data Center Program that aims at improving data center energy efficiency. The project will unprecedentedly provide full access to a newly built data center testbed that hosts nearly 100 servers, with system faults, failures, and server hardware damage allowed. Through extensive experimentation and data analytics, the research will explore basic relationships among server workload, computing performance, hardware component reliability, thermal condition, air flows, and etc under Singapore’s tropic environment condition. The results will provide basis for stipulating new construction and operation guidelines for Singapore's data center industry. The candidate should have obtained a PhD degree in computer science/engineering (or relevant disciplines) and demonstrated strong research ability by publications on venues in the areas of cyber-physical systems (CPS) and data analytics. Knowledge and experiences with data centers are pluses. Interested candidates can send CV with full publication list to Dr. Rui Tan at tanrui(a)ntu.edu.sg. The group that the successful candidates will join is dedicated to CPS and IoT research. We aim to conduct quality research and publish on prestigious CPS/IoT venues. Our past work has been recognized by multiple Best Paper Awards and Runner-Ups. We sincerely invite candidates with great passion for systems research to join us! ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you.

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The Second International Workshop on Parallel and Distributed Data Mining (WPDM 2018)
by Massimo Cafaro 05 Dec '17

05 Dec '17

The Second International Workshop on Parallel and Distributed Data Mining (WPDM 2018) CALL FOR PAPERS As part of The 18th International Conference on Computational Science and Its Applications (ICCSA 2018), http://www.iccsa.org July 2 - 5 2018, Melbourne, Australia Submission Deadline: January 28, 2018 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 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-gui… To submit a paper, please connect to the Submission site from the link available at the ICCSA 2018 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 January 28, 2018: Deadline for paper submission April 8, 2018: Notification of Acceptance. May 6, 2018: Early-bird Registration ends. May 6, 2018: Submission deadline for the final version of the Papers July 2-5, 2018: ICCSA 2018 Conference WORKSHOP ORGANIZERS Massimo Cafaro University of Salento, Italy Phone: +39 0832 297371 Fax: +39 0832 297235 Email: massimo.cafaro(a)unisalento.it Italo Epicoco University of Salento, Italy Phone: +39 0832 297235 Fax: +39 0832 297235 Email: italo.epicoco(a)unisalento.it Marco Pulimeno University of Salento, Italy Phone: +39 0832 297371 Fax: +39 0832 297235 Email: marco.pulimeno(a)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(a)unisalento.it International Program Committee: All submitted papers will be reviewed by the workshop technical program committee members. Program Committee formation is pending and will be finalised shortly. Current TPC members: Gianfranco Bilardi, University of Padova, Italy Alfredo Cuzzocrea, University of Trieste and ICAR-CNR, Italy Giuliano Laccetti, University of Naples, Italy Pablo Moscato, University of Newcastle, Australia Domenico Talia, University of Calabria, Italy Paolo Trunfio, University of Calabria, Italy Jeffrey D. Ullman, Stanford University, USA - ************************************************************************************ 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(a)unisalento.it cafaro(a)ieee.org cafaro(a)acm.org CMCC Foundation Euro-Mediterranean Center on Climate Change Via Augusto Imperatore, 16 - 73100 Lecce massimo.cafaro(a)cmcc.it ************************************************************************************

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CFP- Complexis 2018: 3rd International Conference on Complexity, Future Information Systems and Risk Extended Deadline
by Anna Kobusińska 05 Dec '17

05 Dec '17

--------------------------- CALL FOR PAPERS --------------------------- Dear Colleagues: We cordially invite you to share your latest research results at the 2018 Complexis Conference. Due to many requests, the regular papers submission deadline of this conference has been extended: EXTENDED DEALINE OF POSITION PAPERS: *DECEMBER 6, 2017 * 3rd International Conference on Complexity, Future Information Systems and Risk (COMPLEXIS 2018) Funchal, Madeira / Portugal March 19 - 21, 2018 http://www.complexis.org/ https://www.facebook.com/ES2014ECs2015 ---------------------------- IMPORTANT DATES ---------------------------- Position Papers Paper Submission: December 6, 2017 Authors Notification: January 11, 2018 Camera Ready and Registration: January 24, 2018 Workshops Paper Submission: January 11, 2018 Authors Notification: January 25, 2018 Camera Ready and Registration: February 2, 2018 Doctoral Consortium Paper Submission: January 15, 2018 Authors Notification: January 26, 2018 Camera Ready and Registration: February 7, 2018 Special Sessions Special Session Proposal: December 13, 2017 Tutorials Tutorial Proposal: January 30, 2018 Demos Demo Proposal: January 30, 2018 Panels Panel Proposal: January 30, 2018 Open Communications Paper Submission: January 15, 2018 Authors Notification: January 26, 2018 Camera Ready and Registration: February 7, 2018 Forums Paper Submission: January 15, 2018 Authors Notification: January 26, 2018 Camera Ready and Registration: February 7, 2018 ---------------------------- Conference Scope: COMPLEXIS – the International Conference on Complexity, Future Information Systems and Risk, aims at becoming a yearly meeting place for presenting and discussing innovative views on all aspects of Complex Information Systems, in different areas such as Informatics, Telecommunications, Computational Intelligence, Biology, Biomedical Engineering and Social Sciences. Information is pervasive in many areas of human activity – perhaps all and complexity is a characteristic of current Exabyte- sized, highly connected and hyper dimensional, information systems. COMPLEXIS 2018 is expected to provide an overview of the state of the art as well as upcoming trends, and to promote discussion about the potential of new methodologies, technologies and application areas of complex information systems, in the academic and corporate world. Conference Areas: 1 - Complexity in Informatics, Automation and Networking 2 - Complexity in Biology and Biomedical Engineering 3 - Complexity in Social Sciences 4 - Complexity in Computational Intelligence and Future Information Systems 5 - Complexity in EDA, Embedded Systems, and Computer Architecture 6 - Network Complexity 7 - Complexity in Risk and Predictive Modeling ---------------------------- PUBLICATION ---------------------------- All papers presented at the congress venue will also be available at the SCITEPRESS Digital Library. Proceedings will be submitted for indexation by: DBLP, Thomson-Reuters Conference Proceedings Citation Index, INSPEC, EI and SCOPUS A short list of presented papers will be selected and their revised and extended versions will be published in the *Special Issue of Journal of Grid Computing (JGC)*. Other special issues in the high quality journals like FGCS are also being discussed. ---------------------------- KEYNOTE SPEAKERS ---------------------------- Tobias Hoellwarth, EuroCloud Europe, Austria Péter Kacsuk, MTA SZTAKI, Hungary --------------------------- WORKSHOPS: --------------------------- Big Data Analytics and IoT for Smarter Healthcare - IoTforeHealth (IoTBDS) Chairs: Farshad Firouzi, Bahar Farahani and Victor Chang Submission: January 11, 2018 ---------------------------- PUBLICATION ---------------------------- In Cooperation with: International Federation for Systems Research European Association for Theoretical Computer Science All papers presented at the conference venue will also be available at the SCITEPRESS Digital Library. Proceedings will be submitted for indexation by: DBLP, Thomson-Reuters Conference Proceedings Citation Index, INSPEC, EI and SCOPUS ------------------------------- Organizing Committees ------------------------------- CONFERENCE CHAIR Victor Chang, Xi'an Jiaotong-Liverpool University, China PROGRAM CO-CHAIRS Víctor Méndez Muñoz, Universitat Autònoma de Barcelona, UAB, Spain Muthu Ramachandran, Leeds Beckett University, United Kingdom PUBLICITY CHAIR Anna Kobusinska, Poznan University of Technology, Poland Keynote Speaker Ernesto Estrada, University of Strathclyde, United Kingdom Please visit the IEEE COMPLEXIS 2018 website http://www.complexis.org/ProgramCommittee.aspx for the complete listing of organizing committee and TPC members.

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Deadline Extension for ACM GLSVLSI'18 and Call for Special Sessions
by Yi-Chung Chen 04 Dec '17

04 Dec '17

[Apologies if you receive multiple copies of this email] *************** DEADLINE EXTENSION: New Paper Submission Deadline: December 21, 2017. (Final Deadline) IN ADDITION, CALL FOR SPECIAL SESSIONS: http://www.glsvlsi.org/GLSVLSI18-Special-Session-CFP.pdf The 28th Edition of the ACM Great Lakes Symposium on VLSI (GLSVLSI), Sponsored by ACM SIGDA Conference dates: May 23-25, 2018 Location: Chicago, USA http://www.glsvlsi.org/ The 28th edition of GLSVLSI will be held in Chicago. Original, unpublished papers describing research in the general areas of VLSI and hardware design are solicited. Please visit http://www.glsvlsi.org/·for more information. In addition to the traditional topic areas of GLSVLSI listed below, papers are solicited for a special theme of IoT Hardware and Heterogeneous Computing for Artificial Intelligence. - Track 1: VLSI Design - Track 2: VLSI Circuits and Power Aware Design - Track 3: Computer-Aided Design (CAD) - Track 4: Testing, Reliability, Fault-Tolerance - Track 5: Emerging Computing & Post-CMOS Technologies - Track 6: Hardware Security - Track 7: VLSI for Machine Learning and Artificial Intelligence Details of the requirements that each track places on submitted papers can be found on the conference website. Paper Submission Guidelines ============================ Authors are invited to submit full-length (6 pages maximum), original, unpublished papers along with an abstract of at most 200 words. To enable blind review, the author list should be omitted from the main document. Previously published papers or papers currently under review for other conferences/journals should NOT be submitted and will not be considered. Electronic submission in PDF format to the http://www.glsvlsi.org/ website is required. Author and contact information (name, affiliation, mailing address, telephone, fax, e-mail) must be entered during the submission process. Paper Format: Submissions should be in camera-ready two-column format, following the ACM proceedings specifications located at: http://www.acm.org/publications/proceedings-template-16dec2016and the classification system detailed at: http://www.acm.org/publications/class-2012. Paper Publication and Presenter Registration: Papers will be accepted for regular or poster presentation at the symposium. Every accepted paper MUST have at least one author registered to the symposium by the time the camera-ready paper is submitted; at least one of the authors is also expected to attend the symposium and present the paper. Important Dates ============================ Paper submission deadline: December 21, 2017 Acceptance Notification: February 13, 2018 Camera-Ready Paper Due: March 13, 2018 Special Session Proposal submission deadline: January 15, 2018 Notification of acceptance/rejection: January 31, 2018 Organizers ============================ General Chair: Deming Chen University of Illinois at Urbana-Champaign, USA Program Co-Chairs: Houman Homayoun George Mason University, USA Baris Taskin Drexel University, USA Finance Chair: Weisheng Zhao Beihang University, China Local Chair: Qi Zhu Northwestern University, USA Publicity Co-Chairs: Robert Wille Johannes Kepler University, Austria Yuan-Hao Chang Academia Sinica, Taiwan Miao Hu Binghamton University, USA Special Sessions Chair: Yanjing Li University of Chicago, USA Web & Registration Chair: Yi-Chung Chen SUNY at New Paltz, USA Proceedings Chair: Kyle Rupnow Inspirit IoT, Inc., USA

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CFP to Special Issue in SCAC on Scalable Algorithms and Behavior Analytics in Cyber-Enabled World - Deadline Mar. 31, 2018
by Xiaokang Zhou 04 Dec '17

04 Dec '17

[Apologies if you receive this more than once] [SCAC Call for Papers] http://static.springer.com/sgw/documents/1608722/application/pdf/scalable+a… ======================================================================= Scalable Computing and Communications Special Issue on Scalable Algorithms and Behavior Analytics in Cyber-Enabled World ----------------------------------------------------------------------------------------------------------------------------- Aims and Scope Due to the emerging computing paradigm, the physical, social, and mental world are increasingly integrating and merging into the cyberspace. In this emerging but significant field, it is necessary to model the human individual information processing along with their corresponding behaviors, in order to build systematic knowledge about new phenomena, behaviors, properties and practices across the broad applications in cyber-enabled world. Specifically, studies related to scalable algorithm and behavioral analysis are conducted in terms of the cyber entities, as well as their relations and conjugations in physical, social and mental spaces, which focuses more on the basic attributes, models, functions, and evolutions of cyber entities, and all their possible relations conjugated with real things. For this scientific and systematic study, numerous challenges are raised as: How to establish and improve the foundational theory and methodology for the scalable computing and data processing in the cyber-enabled world? How to find a unified way to study and represent the diversified cyber entities along with their behavior patterns and communications? How to systematically extract, create, and fuse the information, knowledge, and intelligence generated across the physical-social systems for the sustainable utilization? How to deal with the accompanying issues while producing numerous cyber things, such as security, reliability, and etc. Topics may include (but are not limited to): • Scalable Communications in Cyber-world • Data Centric Computing in Cyberspace • Scalable Knowledge Modeling and Management in Cyber-world • User Behavior Analysis and Modeling in Cyber-physical Systems • User Influence Measure and Model in Cyberspace • Cyber-Social Sensing and Behavior Analysis • Scalable Cyber Hybrid Interface/System Design • Scalable Mechanisms for Intelligent Transportation Systems • Cyber-Based Learning Analytics with Scalable Computing • Cyber-Empowered Sentiment Analysis and Mental Computing • Wearable Computing and Smart Sensor • Scalable Computing for Healthcare • Scalability in Cyber Security, Privacy and Reliability • Scalable algorithms for Cyber Visualization • Scalable deep learning architectures • Scalable Brain-inspired Computing and Soft Computing • Scalable Agent-based Computing • Scalable algorithms for the Internet of Things • Scalable algorithms for Edge computing (EC) and Mobile Edge Computing (MEC) • Scalable Services for Pervasive Computing Submissions Authors should prepare their manuscript according to the Guide for Authors of Scalable Computing and Communications available from http://www.springer.com/41122 , and submit online at: https://www.editorialmanager.com/scac . To ensure that the manuscript is correctly identified for inclusion into the special issue, authors must select "Scalable Algorithms and Behavior Analytics in Cyber-Enabled World" when they reach the “Article Type” step in the submission process. Tentative Schedule Paper Submission Due: Mar. 31, 2018 Completion of first review cycle: Jul. 15, 2018 Deadline for submitting the revised papers: Oct. 15, 2018 2nd review completion: Nov. 30, 2018 Camera-ready Manuscript Due: Dec. 31, 2018 Guest editors: Xiaokang Zhou, Shiga University, Japan Kevin Wang, The University of Auckland, New Zealand Flavia C. Delicato, Federal University of Rio de Janeiro, Brazil Adnan Al-Anbuky, Auckland University of Technology, New Zealand Contact Information Corresponding Guest Editor, Dr. Zhou (zhou(a)biwako.shiga-u.ac.jp) -- Xiaokang Zhou (周暁康), Ph.D. Faculty of Data Science The Center for Data Science Education and Research, Shiga University 1-1-1 Banba, Hikone, Shiga 522-8522, Japan Email: zhou(a)biwako.shiga-u.ac.jp Phone: +81-749-27-1290

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ACDL 2018, Advanced Course on Data Science and Machine Learning - Early Registration March 31
by Giuseppe Nicosia 01 Dec '17

01 Dec '17

ACDL 2018, Advanced Course on Data Science and Machine Learning An Interdisciplinary Course: Data Science, Machine Learning and Artificial intelligence without Borders ACDL 2018 – A Unique Experience: Data Science & Machine Learning with the World’s Leaders in the fascinating atmosphere of the ancient Certosa di Pontignano Certosa di Pontignano, Siena - Tuscany, Italy July 19-23, 2018 https://acdl2018.icas.xyz/ Early registration deadline: March 31, 2018 https://acdl2018.icas.xyz/registration/ LECTURERS: Roman Belavkin, Middlesex University London, UK Yoshua Bengio, University of Montreal, Canada Sergiy Butenko, Texas A&M University, USA Yi-Ke Guo, Imperial College London, UK Yann LeCun, Director of AI Research, Facebook New York University, USA Peter Norvig, Director of Research, Google Panos Pardalos, University of Florida, USA Alex 'Sandy' Pentland, MIT, USA Mauricio Resende, Amazon, USA More speakers to be announced soon! SCOPE: The Advanced Course is not a summer school suited only for younger scholars. Rather, a significant proportion of seasoned investigators are regularly present among the attendees, often senior faculty at their own institutions. The balanced audience that we strive to maintain in each Advanced Course greatly contributes to the development of intense cross-disciplinary debates among faculty and participants that typically address the most advanced and emerging areas of each topic. Each faculty member presents lectures and discusses with the participants for one entire day. Such long interaction together with the small, exclusive Course size provides the uncommon opportunity to fully explore the expertise of each faculty, often through one-to-one mentoring. This is unparalleled and priceless. The Certosa di Pontignano provides the perfect setting to a relaxed yet intense learning atmosphere, with the stunning backdrop of the Tuscan landscapes. World-class wines and traditional foods will make the Advanced Course on Data Science and Machine Learning the experience of a lifetime. VENUE & ACCOMMODATION: The venue of ACDL 2018 will be The Certosa di Pontignano — Siena The Certosa di Pontigniano Loc. Pontignano, 5 – 53019, Castelnuovo Berardenga (SI) – Tuscany – Italy phone: +39-0577-1521104 fax: +39-0577-1521098 info(a)lacertosadipontignano.com http://www.lacertosadipontignano.com/ A few kilometres from Siena, on a hill dominating the town stands the ancient Certosa di Pontignano, a unique place where nature, history and hospitality blend together in memorable harmony. Built in the 1300, its medieval structure remains intact with additions of the following centuries. The Certosa is centred on its historic cloisters and gardens. https://acdl2018.icas.xyz/venue/ REGISTRATION: https://acdl2018.icas.xyz/registration/ lod(a)icas.xyz https://acdl2018.icas.xyz/

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Announcement - NICO Hosts International Conference on Computational Social Science
by Northwestern Institute on Complex Systems 28 Nov '17

28 Nov '17

Dear colleagues, We are very excited to announce that Northwestern University and Northwestern Institute on Complex Systems (NICO<https://www.nico.northwestern.edu/>) is once again hosting the annual International Conference on Computational Social Science from July 12-15, 2018<http://www.kellogg.northwestern.edu/news-events/conference/ic2s2/2018.aspx>. Our Call for Abstracts for presentations has just opened, and our chairs and committee members thought members of your group might be interested. Visit this page?<https://www.kellogg.northwestern.edu/faculty/uzzi/IC2S2/IC2S22018-CallForAb…> for further information. Feel free to forward this link to others if interested as well. Sincerely, Yasmeen Khan Business Coordinator, NICO?????? [cid:image001.jpg@01D362AD.C692A580]

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Special Issue on Parallel and Distributed Data Mining
by Massimo Cafaro 27 Nov '17

27 Nov '17

Special Issue on Parallel and Distributed Data Mining Information Sciences, Elsevier Submission deadline: February 1st, 2018 The sheer volume of new data, which is being generated at an increasingly fast pace, has already produced an anticipated data deluge that is difficult to challenge. We are in the presence of an overwhelming vast quantity of data, owing to how easy is to produce or derive digital data. Even the storage of this massive amount of data is becoming a highly demanding task, outpacing the current development of hardware and software infrastructure. Nonetheless, this effort must be undertaken now for the preservation, organization and long-term maintenance of these precious data. However, the collected data is useless without our ability fully understand and make use of it. Therefore, we need new algorithms to address this challenge. 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. This Special Issue takes into account the increasing interest in the design and implementation of parallel and distributed data mining algorithms. Parallel algorithms can easily address both the running time and memory requirement issues, by exploiting the vast aggregate main memory and processing power of processors and accelerators available on parallel computers. 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. 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. Moreover, increasingly the data is spread among different geographically distributed sites. Centralized processing of this data is very inefficient and expensive. In some cases, it may even be impractical and subject to security risks. Therefore, processing the data minimizing the amount of data being exchanged whilst guaranteeing at the same time correctness and efficiency is an extremely important challenge. Distributed data mining performs data analysis and mining in a fundamentally distributed manner paying careful attention to resource constraints, in particular bandwidth limitation, privacy concerns and computing power. The focus of this Special Issue is on all forms of advances in high-performance and distributed data mining algorithms and applications. The topics relevant to the Special Issue include (but are not limited to) the following. TOPICS OF INTEREST Scalable parallel data mining algorithms using message-passing, shared-memory or hybrid programming paradigms Exploiting modern parallel architectures including FPGA, GPU and many-core accelerators for parallel data mining applications Middleware for high-performance data mining on grid and cloud environments 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 Map-reduce based parallel data mining algorithms Caching, streaming, pipelining, and other optimization techniques for data management in high-performance computing for data mining Novel distributed data mining algorithms SUBMISSION GUIDELINES All manuscripts and any supplementary material should be submitted electronically through Elsevier Editorial System (EES) at http://ees.elsevier.com/ins (http://ees.elsevier.com/ins). The authors must select as “SI:PDDM” when they reach the “Article Type” step in the submission process. A detailed submission guideline is available as “Guide to Authors” at: http://www.elsevier.com/journals/information-sciences/0020-0255/guide-for-a…. IMPORTANT DATES Submission deadline: February 1st, 2018 First round notification: May 1st, 2018 Revised version due: July 1st, 2018 Final notification: August 1st, 2018 Camera-ready due: September 15th, 2018 Publication tentative date: December 2018 Guest editors: Massimo Cafaro, Email: massimo.cafaro(a)unisalento.it University of Salento, Italy and Euro-Mediterranean Centre on Climate Change, Foundation Italo Epicoco, Email: italo.epicoco(a)unisalento.it University of Salento, Italy and Euro-Mediterranean Centre on Climate Change, Foundation Marco Pulimeno, Email: marco.pulimeno(a)unisalento.it University of Salento, Italy - ************************************************************************************ 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(a)unisalento.it cafaro(a)ieee.org cafaro(a)acm.org CMCC Foundation Euro-Mediterranean Center on Climate Change Via Augusto Imperatore, 16 - 73100 Lecce massimo.cafaro(a)cmcc.it ************************************************************************************

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IEEE 7th Parlearning workshop with IPDPS 2018
by ngoko 24 Nov '17

24 Nov '17

Please, accept our apologies in case of multiple copies of this CFP. ******************************************************************* The 7th International Workshop on Parallel and Distributed Computing for Large Scale Machine Learning and Big Data Analytics May 21, 2018 Vancouver, British Columbia CANADA http://parlearning.ecs.fullerton.edu In Conjunction with 32nd IEEE International Parallel & Distributed Processing Symposium. Scaling up machine-learning (ML), data mining (DM) and reasoning algorithms from Artificial Intelligence (AI) for massive datasets is a major technical challenge in the time of "Big Data". The past ten years have seen the rise of multi-core and GPU based computing. In parallel and distributed computing, several frameworks such as OpenMP, OpenCL, and Spark continue to facilitate scaling up ML/DM/AI algorithms using higher levels of abstraction. We invite novel works that advance the trio-fields of ML/DM/AI through development of scalable algorithms or computing frameworks. Ideal submissions should describe methods for scaling up X using Y on Z, where potential choices for X, Y and Z are provided below. Scaling up • Recommender systems • Optimization algorithms (gradient descent, Newton methods) • Deep learning • Sampling/sketching techniques • Clustering (agglomerative techniques, graph clustering, clustering heterogeneous data) • Classification (SVM and other classifiers) • SVD and other matrix computations • Probabilistic inference (Bayesian networks) • Logical reasoning • Graph algorithms/graph mining and knowledge graphs • Semi-supervised learning • Online/streaming learning • Generative adversarial networks Using • Parallel architectures/frameworks (OpenMP, OpenCL, OpenACC, Intel TBB) • Distributed systems/frameworks (GraphLab, Hadoop, MPI, Spark) • Machine learning frameworks (TensorFlow, PyTorch, Theano, Caffe) On • Clusters of conventional CPUs • Many-core CPU (e.g. Xeon Phi) • FPGA • Specialized ML accelerators (e.g. GPU and TPU) IMPORTANT DATES • Paper submission: January 13, 2018 AoE • Notification: February 10, 2018 • Camera Ready: February 24, 2018 PAPER GUIDELINES Submitted manuscripts should be upto 10 single-spaced double-column pages using 10-point size font on 8.5x11 inch pages (IEEE conference style), including figures, tables, and references. Format requirements are posted on the IEEE IPDPS web page. All submissions must be uploaded electronically at TBA TRAVEL AWARDS Students with accepted papers can apply for a travel award. Please find details at www.ipdps.org

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CFP: IEEE Workshop on Parallel / Distributed Computing and Optimization (PDCO 2018) in conjunction with IEEE IPDPS 2018 Vancouver Canada
by Didier Elbaz 24 Nov '17

24 Nov '17

Please, accept our apologies in case of multiple copies of this CFP. ********************************************************************** The 8th IEEE Workshop on Parallel / Distributed Computing and Optimization (PDCO 2018) https://pdco2018.sciencesconf.org/ held in conjunction with the 32nd IEEE International Parallel and Distributed Processing Symposium (IPDPS'2018) May 21-25, 2017 Vancouver, Canada http://www.ipdps.org ********************************************************************** ************************************************** Submission Deadline: December 15, 2017 ************************************************** Scope: ====== The IEEE Workshop on Parallel / Distributed Computing and Optimization aims at providing a forum for scientific researchers and engineers on recent advances in the field of parallel or distributed computing for difficult optimization problems, ranging from theoretical to applied problems. The latter include 0-1 multidimensional knapsack problems and cutting stock problems, large scale linear programming problems, nonlinear optimization problems, global optimization and scheduling problems. Emphasis will be placed on new techniques for solving these difficult problems, like cooperative methods for integer programming problems, nature-inspired techniques and hybrid methods. Aspects related to Combinatorial Scientific Computing (CSC) will also be treated. We also solicit submissions of original manuscripts on sparse matrix computations and related topics (including graph algorithms); and related methods and tools for their efficiency on different parallel systems. The use of new approaches in parallel and distributed computing like GPU, MIC, cloud computing, volunteer computing will be considered. Applications combining traditional parallel and distributed computing and optimization techniques as well as theoretical issues (convergence, complexity, etc.) are welcome. Application domains of interest include (but are not limited to) cloud computing, planning, logistics, manufacturing, finance, telecommunications and computational biology. Topics: ======= * Integer programming, linear programming, nonlinear programming; * Scheduling; * Global optimization, polynomial optimization; * Exact methods, heuristics, metaheuristics, hybrid methods; * Cooperative methods, hybrid methods; * Parallel / distributed algorithms for combinatorial optimization; * Parallel / distributed metaheuristics; * Distributed optimization algorithms; * Nature inspired distributed computing; * Parallel sparse matrix computations, graph algorithms, load balancing; * Peer to peer computing and optimization problems; * Applications: cloud computing, planning, logistics, manufacturing, finance, telecommunications, computational biology, combinatorial algorithms in high performance computing. Steering Committee: =================== Pascal Bouvry, University of Luxembourg, Luxembourg (co-chair) Didier El Baz, team CDA, LAAS-CNRS, France (co-chair) El-Ghazali Talbi, University of Lille, INRIA, CNRS, France Albert Y. Zomaya, The University of Sydney, Australia General Chairs: =============== Grégoire Danoy, University of Luxembourg, Luxembourg Didier El Baz, team CDA, LAAS-CNRS, France Program Chairs: =============== Vincent Boyer, University of Nuevo Leon, Mexico Bernabe Dorronsoro, Universidad de Cádiz, Spain Publicity Chairs: ================= Keqin Li, State University of New York at New Paltz, USA Laurence T. Yang, St Francis Xavier University, Canada Program Committee (to be completed): ==================================== A. Bendjoudi, CERIST, Algiers, Algeria J.-N. Cao, Hong-Kong Polytechnic University, China J. J. Durillo, University of Innsbruck, Austria S. Fujita, Hiroshima University, Japan M. Halappanavar, Pacific Northwest National Laboratory, USA K. Li, State University of New York, USA N. Melab, University of Lille, France M. Menai, King Saud University, Saudi Arabia A. Nakib, University Paris 12, France S. Nesmachnow, Universidad de la República, Uruguay S. Nikoletseas, University of Patras and CTI, Greece C. Phillips, Sandia National Laboratories, USA T. Saadi, University of Picardie, France M. Seredynski, Luxembourg Institute of Science and Technology, Luxembourg G. Ch. Sirakoulis, Democritus University of Thrace, Greece G. Spezzano, University of Calabria, Italy A. Tchernykh, CICESE Research Center, Mexico B. Ucar, CNRS and ENS Lyon, France F. Xhafa, Polytechnic University of Catalonia, Spain L.T. Yang, St Francis Xavier University, Canada Submission : ============ Papers in the Proceedings of the workshops will be indexed in the IEEE Xplore Digital Library after the conference. Prospective authors should submit their papers through Workshop PDCO 2017 submission system: i.e. EasyChair: https://easychair.org/conferences/?conf=pdco2018 Abstract and paper can be uploaded until December 15, 2017. Authors should preferably follow the manuscript specifications of IEEE IPDPS, i.e. submitted manuscripts may not exceed 10 single-spaced double-column pages using 10-point size font on 8.5x11 inch pages (IEEE conference style), including figures, tables and references. Style templates are available at the IPDPS web site. Important Dates: ================ - Submission Deadline: December 15, 2017 - Notification of acceptance: February 16, 2018 - Workshop: May 21, 2018 Contact: ======== For questions regarding the Workshop, please contact the conference organizers at pdco2018(a)sciencesconf.org <mailto:pdco2018@sciencesconf.org>

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