computational.science November 2017

computational.science@lists.iccsa.org

25 participants
30 discussions

Call for Papers: ScalA@SC 2017 - Papers due August 28
by Engelmann, Christian 04 Nov '20

04 Nov '20

We apologize if you receive multiple copies of this notice. ----------------------------------------------------------------------------- ScalA’17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems held in conjunction with the SC17: The International Conference on High Performance Computing, Networking, Storage and Analysis in cooperation with ACM SIGHPC November 13, 2017, Denver, CO, USA <http://www.csm.ornl.gov/srt/conferences/Scala/2017> Novel scalable scientific algorithms are needed in order to enable key science applications to exploit the computational power of large-scale systems. This is especially true for the current tier of leading petascale machines and the road to exascale computing as HPC systems continue to scale up in compute node and processor core count. These extreme-scale systems require novel scientific algorithms to hide network and memory latency, have very high computation/communication overlap, have minimal communication, and have no synchronization points. Scientific algorithms for multi-petaflop and exa-flop systems also need to be fault tolerant and fault resilient, since the probability of faults increases with scale. Resilience at the system software and at the algorithmic level is needed as a crosscutting effort. Finally, with the advent of heterogeneous compute nodes that employ standard processors as well as GPGPUs, scientific algorithms need to match these architectures to extract the most performance. This includes different system-specific levels of parallelism as well as co-scheduling of computation. Key science applications require novel mathematical models and system software that address the scalability and resilience challenges of current- and future-generation extreme-scale HPC systems. Submission Guidelines Authors are invited to submit manuscripts in English structured as technical papers not exceeding 8 letter size (8.5in x 11in) pages including figures, tables, and references using the ACM format for conference proceedings. Submissions not conforming to these guidelines may be returned without review. Reference style files are available at <http://www.acm.org/sigs/publications/proceedings-templates>. All manuscripts will be reviewed and judged on correctness, originality, technical strength, and significance, quality of presentation, and interest and relevance to the workshop attendees. Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference. Submissions received after the due date, exceeding length limit, or not appropriately structured may also not be considered. At least one author of an accepted paper must register for and attend the workshop. Authors may contact the workshop program chair for more information. Papers should be submitted electronically at: <https://easychair.org/conferences/?conf=scala17>. Full papers will be published with the SC'17 workshop proceedings in the ACM Digital Library and IEEE Xplore. Selected papers will be invited for an extended version in a special issue of the Journal of Computational Science (JoCS). Important Dates - Full paper submission: August 28, 2017 - Notification of acceptance: September 11, 2017 - Final paper submission (firm): October 9, 2017 - Workshop/conference early registration: TBD - Workshop: November 13, 2017 Topics of interest include, but are not limited to: - Novel scientific algorithms that improve performance, scalability, resilience, and power efficiency - Porting scientific algorithms and applications to many-core and heterogeneous architectures - Performance and resilience limitations of scientific algorithms and applications at scale - Crosscutting approaches (system software and applications) in addressing scalability challenges - Scientific algorithms that can exploit extreme concurrency (e.g. 1 billion for exascale by 2020) - Naturally fault tolerant, self-healing, or fault oblivious scientific algorithms - Programming model and system software support for algorithm scalability and resilience Workshop Chairs - Vassil Alexandrov, Barcelona Supercomputing Center, Spain - Al Geist, Oak Ridge National Laboratory, USA - Jack Dongarra, University of Tennessee, Knoxville, USA Workshop Program Chair - Christian Engelmann, Oak Ridge National Laboratory, USA Program Committee - Vassil Alexandrov, Barcelona Supercomputing Center, Spain - Hartwig Anzt, University of Tennessee, Knoxville, USA - Rick Archibald, Oak Ridge National Laboratory, USA - Franck Cappello, Argonne National Laboratory and University of Illinois at Urbana Champaign, USA - Zizhong Chen, University of California, Riverside, USA - James Elliott, Sandia National Laboratories, USA - Nahid Emad, University of Versailles SQ, France - Christian Engelmann, Oak Ridge National Laboratory, USA - Wilfried Gansterer, University of Vienna, Austria - Michael Heroux, Sandia National Laboratories, USA - Kirk E. Jordan, IBM T.J. Watson Research, USA - Dieter Kranzlmueller, Ludwig-Maximilians-University Munich, Germany - Ignacio Laguna, Lawrence Livermore National Laboratory, USA - Piotr Luszczek, University of Tennessee, Knoxville, USA - Michael Mascagni, Florida State University, USA - Ron Perrot, University of Oxford, UK - Yves Robert, ENS Lyon, France - Stuart Slattery, Oak Ridge National Laboratory, USA - Keita Teranishi, Sandia National Laboratories, USA -- Christian Engelmann, Ph.D. R&D Staff Scientist Computer Science Research Group Computer Science and Mathematics Division Oak Ridge National Laboratory Mail: P.O. Box 2008, Oak Ridge, TN 37831-6173, USA Phone: +1 (865) 574-3132 / Fax: +1 (865) 576-5491 e-Mail: engelmannc(a)ornl.gov / Home: www.christian-engelmann.info

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CFP: Resilience@Euro-Par 2017 - Papers due May 5
by Christian Engelmann 08 May '19

08 May '19

We apologize if you receive multiple copies of this call for papers. -------------------------------------------------------------------------------- 10th Workshop on Resiliency in High Performance Computing (Resilience) in Clusters, Clouds, and Grids <http://www.csm.ornl.gov/srt/conferences/Resilience/2017> in conjunction with the 23rd International European Conference on Parallel and Distributed Computing (Euro-Par), Santiago de Compostela, Spain, August 28 - September 1, 2017 <http://europar2017.usc.es> Overview: Resilience is a critical challenge as high performance computing (HPC) systems continue to increase component counts, individual component reliability decreases (such as due to shrinking process technology and near-threshold voltage (NTV) operation), and software complexity increases. Application correctness and execution efficiency, in spite of frequent faults, errors, and failures, is essential to ensure the success of the extreme-scale HPC systems, cluster computing environments, Grid computing infrastructures, and Cloud computing services. While a fault (e.g., a bug or stuck bit) is the cause of an error, its manifestation as a state change is considered an error (e.g., a bad value or incorrect execution), and the transition to an incorrect service is observed as a failure (e.g., an application abort or system crash). A failure in a computing system is typically observed through an application abort or a full/partial service or system outage. A detectable correctable error is often transparently handled by hardware, such as a single bit flip in memory that is protected with single-error correction double-error detection (SECDED) error correcting code (ECC). A detectable uncorrectable error (DUE) typically results in a failure, such as multiple bit flips in the same addressable word that escape SECDED ECC correction, but not detection, and ultimately cause an application abort. An undetectable error (UE) may result in silent data corruption (SDC), e.g., an incorrect application output. There are many other types of hardware and software faults, errors, and failures in computing systems. Resilience for HPC systems encompasses a wide spectrum of fundamental and applied research and development, including theoretical foundations, fault detection and prediction, monitoring and control, end-to-end data integrity, enabling infrastructure, and resilient solvers and algorithm-based fault tolerance. This workshop brings together experts in the community to further research and development in HPC resilience and to facilitate exchanges across the computational paradigms of extreme-scale HPC, cluster computing, Grid computing, and Cloud computing. Submission Guidelines: Authors are invited to submit papers electronically in English in PDF format. Submitted manuscripts should be structured as technical papers and BETWEEN 10 AND 12 PAGES, including figures, tables and references, using Springer's Lecture Notes in Computer Science (LNCS) format at <http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0>. Papers with less than 10 or more than 12 pages will not be accepted due to publisher guidelines. Submissions should include abstract, key words and the e-mail address of the corresponding author. Papers not conforming to these guidelines may be returned without review. All manuscripts will be reviewed and will be judged on correctness, originality, technical strength, significance, quality of presentation, and interest and relevance to the conference attendees. Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference. Submissions received after the due date or not appropriately structured may also not be considered. The proceedings will be published in Springer's LNCS as post-conference proceedings. At least one author of an accepted paper must register for and attend the workshop for inclusion in the proceedings. Authors may contact the workshop program chairs for more information. Important websites: - Resilience 2017 Website: <http://www.csm.ornl.gov/srt/conferences/Resilience/2017> - Resilience 2017 Submissions: <https://easychair.org/conferences/?conf=europar2017workshops> - Euro-Par 2017 website: <http://europar2017.usc.es> Topics of interest include, but are not limited to: - Theoretical foundations for resilience: - Metrics and measurement - Statistics and optimization - Simulation and emulation - Formal methods - Efficiency modeling and uncertainty quantification - Fault detection and prediction: - Statistical analyses - Machine learning - Anomaly detection - Data and information collection - Visualization - Monitoring and control for resilience: - Platform and application monitoring - Response and recovery - RAS theory and performability - Application and platform knobs - Tunable fidelity and quality of service - End-to-end data integrity: - Fault tolerant design - Degraded modes - Forward migration and verification - Fault injection - Soft errors - Silent data corruption - Enabling infrastructure for resilience: - RAS systems - System software and middleware - Programming models - Tools - Next-generation architectures - Resilient solvers and algorithm-based fault tolerance: - Algorithmic detection and correction of hard and soft faults - Resilient algorithms - Fault tolerant numerical methods - Robust iterative algorithms - Scalability of resilient solvers and algorithm-based fault tolerance Important Dates: - Workshop papers due: May 5, 2017 - Workshop author notification: June 16, 2017 - Workshop early registration: TBD - Workshop paper (for informal workshop proceedings): July 21, 2017 - Workshop camera-ready papers: October 3, 2017 General Co-Chairs: - Stephen L. Scott Senior Research Scientist - Systems Research Team Tennessee Tech University and Oak Ridge National Laboratory, USA scottsl(a)ornl.gov - Chokchai (Box) Leangsuksun, SWEPCO Endowed Associate Professor of Computer Science Louisiana Tech University, USA box(a)latech.edu Program Co-Chairs: - Patrick G. Bridges University of New Mexico, USA bridges(a)cs.unm.edu - Christian Engelmann Oak Ridge National Laboratory , USA engelmannc(a)ornl.gov Program Committee: - Ferrol Aderholdt, Oak Ridge National Laboratory, USA - Dorian Arnold, University of New Mexico, USA - Rizwan Ashraf, Oak Ridge National Laboratory, USA - Wesley Bland, Intel Corporation, USA - Hans-Joachim Bungartz, Technical University of Munich, Germany - Franck Cappello, Argonne National Laboratory and University of Illinois at Urbana-Champaign, USA - Marc Casas, Barcelona Supercomputer Center, Spain - Zizhong Chen, University of California at Riverside, USA - Robert Clay, Sandia National Laboratories, USA - Miguel Correia, Universidade de Lisboa, Portugal - Nathan DeBardeleben, Los Alamos National Laboratory, USA - James Elliott, Sandia National Laboratories, USA - Kurt Ferreira, Sandia National Laboratories, USA - Michael Heroux, Sandia National Laboratories, USA - Saurabh Hukerikar, Oak Ridge National Laboratory, USA - Dieter Kranzlmueller, Ludwig-Maximilians University of Munich, Germany - Sriram Krishnamoorthy, Pacific Northwest National Laboratory, USA - Ignacio Laguna, Lawrence Livermore National Laboratory, USA - Scott Levy, University of New Mexico, USA - Kathryn Mohror, Lawrence Livermore National Laboratory, USA - Christine Morin, INRIA Rennes, France - Dirk Pflueger, University of Stuttgart, Germany - Nageswara Rao, Oak Ridge National Laboratory, USA - Alexander Reinefeld, Zuse Institute Berlin, Germany - Rolf Riesen, Intel Corporation, USA - Yves Robert, ENS Lyon, France - Thomas Ropars, Universite Grenoble Alpes, France - Martin Schulz, Lawrence Livermore National Laboratory, USA - Keita Teranishi, Sandia National Laboratories, USA -- Christian Engelmann, Ph.D. R&D Staff Scientist Computer Science Research Group Computer Science and Mathematics Division Oak Ridge National Laboratory Mail: P.O. Box 2008, Oak Ridge, TN 37831-6173, USA Phone: +1 (865) 574-3132 / Fax: +1 (865) 576-5491 e-Mail: engelmannc(a)ornl.gov / Home: www.christian-engelmann.info

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IEEE HPCS Workshop on High Performance Computing Systems for Bioinformatics and Life Sciences (BILIS 2017) - Ext Deadline
by Mario Cannataro 03 Oct '18

03 Oct '18

I apologize for any cross-posting of this announcement. ======================================================================================== Int. Workshop on High Performance Computing Systems for Bioinformatics and Life Sciences (BILIS 2017) http://hpcs2017.cisedu.info/conference/workshops---hpcs2017/workshop17-bilis July 17 – July 21, 2017 Genoa, Italy held in conjunction with International Conference on High Performance Computing & Simulation (HPCS 2017) http://hpcs17.cisedu.info/ ======================================================================================== * * * CALL FOR PAPERS * * * EXTENDED Submission Deadline: April 15, 2017 Submissions could be for full papers, short papers, poster papers, or posters ======================================================================================== IMPORTANT DATES Paper Submissions: --------------------------------- April 15, 2017 - Extended Acceptance Notification: --------------------------- April 28, 2017 Camera Ready Papers and Registration Due by: ------- May 11, 2017 Conference Dates: --------------------------------- July 17 – 21, 2017 ======================================================================================== SCOPE AND OBJECTIVES Incorporating new advancements of Information Technology (IT) in general and High Performance Computing (HPC) in particular in the domain of Life Sciences and Biomedical Research continues to receive tremendous attention of researchers, biomedical institutions and the rest of the biomedical community. Although medical instruments have benefited a great deal from the technological advances of the couple of decades, the impact of integrating IT advancements in addressing critical problems in biomedical research remains limited and the process of penetrating IT tools in the medical profession continues to be a very challenging problem. For example, the use of electronic medical records and Hospital Information Systems in improving health care remains fragmented. Similarly, the use of advanced computational tools seamlessly in the biomedical research cycle continues to be minimal. Due to the computational intensive problems in life sciences, the marriage between the Bioinformatics domain and high performance computing is critical to the advancement of Biosciences. In addition, the problems in this domain tend to be highly parallelizable and deal with large datasets, hence using HPC is a natural fit. The Bioinformatics domain is rich in applications that require extracting useful information from very large and continuously growing sequence of databases. Most methods used for analyzing DNA/Protein sequences are known to be computationally intensive, providing motivation for the use of powerful computational systems with high throughput characteristics. Moreover, high-throughput wet lab platforms such as next generation sequencing, microarray and mass spectrometry, are producing a huge amount of experimental "omics" data. The increasing availability of omics data poses new challenges to bioinformatics applications that need to face in a semi-automatic way an overwhelming availability of raw data. Main challenges regard: 1) the efficient storage, retrieval and integration of experimental data; 2) their efficient and high-throughput preprocessing and analysis; 3) the building of reproducible "in silico" experiments; 4) the integration of analysis results with pre-existing knowledge usually stored into ontologies. As the storage, preprocessing and analysis of raw experimental data is becoming the main bottleneck of the analysis pipeline, parallel computing is playing an important role in all steps of the life sciences research pipeline, from raw data management and processing, to data integration and analysis, and to data exploration and visualization. Moreover, Cloud Computing is becoming the key technology to hide the complexity of computing infrastructures, to reduce the cost of the data analysis task, and especially to change the overall business model of biomedical research and health provision. Considering the complex analysis pipeline of the biomedical research, the bottleneck is more and more moving toward the storage, integration, and analysis of experimental data, as well as their correlation and integration with publicly available data banks In such a scenario, large-scale distributed databases and parallel bioinformatics tools are key tools for organizing and exploring biological and biomedical data with the aim to discover new knowledge in biology and medicine. In the current Information age, further progress of Medical Sciences requires successful integration with Computational and Information Sciences. The workshop attempts to attract innovative ways of how such integration can be achieved via Bioinformatics and Biomedical Informatics research, particularly in taking advantage of the new advancements in HPC systems. The focus of data analysis and data mining tools in biomedical research highlights the current state of research in the key biomedical research areas such as bioinformatics, medical informatics and biomedical imaging. Addressing performance concerns in managing and accessing medical data, while facilitating the ability to integrate and correlate different biomedical databases remains an outstanding problem in biomedical research. The amount of available biomedical data continues to grow in an exponential rate; however, the impact of utilizing such resources remains minimal. The development of innovative tools in HPC environments to integrate, analyze and mine such data sources is a key step towards achieving large impact levels. The workshop focuses on topics related to the utilization of HPC systems and new models of parallel computing and cloud computing in problems related to Biomedical Informatics and Life Sciences, along with the use of data integration and data mining tools to support biomedical research and Health Care. The BILIS Workshop topics include (but are not limited to) the following: HPC for the Analysis of Biological Data Bioinformatics Tools for Health Care Parallel Algorithms for Bioinformatics Applications Ontologies in Biology and Medicine Integration and Analysis of Molecular and Clinical Data Parallel Bioinformatics Algorithms Algorithms and Tools for Biomedical Imaging and Medical Signal Processing Energy Aware Scheduling Techniques for Large Scale Biomedical Applications HPC for analyzing Biological Networks Next Generation Sequencing and Advanced Tools for DNA Assembly HPC for Gene, Protein/RNA Analysis and Structure Prediction Identification of Biomarkers Biomedical Visualization Tools Efficient Clustering and Classification Algorithms Correlation Networks in Biomedical Research Data Mining Techniques in Biomedical Applications Heterogeneous Data Integration HPC systems for Ontology and Database Integration Pattern Recognition and Search Tools in Biological and Clinical Databases Ubiquitous Medical Knowledge Discovery and Exchange HPC for Monitoring and Treatment Facilities Drug Design and Modeling Computer Assisted Surgery and Medical Procedures Remote Patient Monitoring, Homecare Applications Mobile and Wireless Healthcare and Biomedical Applications Cloud Computing for Bioinformatics, Medicine, and Health Systems INSTRUCTIONS FOR PAPER SUBMISSIONS You are invited to submit original and unpublished research works on above and other topics related to HPC for Bioinformatics, Healthcare and Life Sciences. Submitted papers must not have been published or simultaneously submitted elsewhere. For Regular papers, please submit a PDF copy of your full manuscript, not to exceed 8 double-column formatted pages per template, and include up to 6 keywords and an abstract of no more than 400 words. Additional pages will be charged additional fee. Submission should include a cover page with authors' names, affiliation addresses, fax numbers, phone numbers, and all authors email addresses. Please, indicate clearly the corresponding author(s) although all authors are equally responsible for the manuscript. Short papers (up to 4 pages), poster papers and posters (please refer to http://hpcs2017.cisedu.info/1-call-for-papers-and-participation/call-for-po… for posters submission details) will also be considered. Please specify the type of submission you have. Please include page numbers on all preliminary submissions to make it easier for reviewers to provide helpful comments. Submit a PDF copy of your full manuscript to the workshop organizers via email as attachments to Hesham Ali: hali(a)unomaha.edu, Mario Cannataro: cannataro(a)unicz.it. Acknowledgement will be sent within 48 hours of submission. Only PDF files will be accepted, uploaded to the submission link above. Each paper will receive a minimum of three reviews. Papers will be selected based on their originality, relevance, significance, technical clarity and presentation, language, and references. Submission implies the willingness of at least one of the authors to register and present the paper, if accepted. At least one of the authors of each accepted paper will have to register and attend the HPCS 2017 conference to present the paper at the workshop. PROCEEDINGS Accepted papers will be published in the Conference proceedings. Instructions for final manuscript format and requirements will be posted on the HPCS 2017 Conference web site. It is our intent to have the proceedings formally published in hard and soft copies and be available at the time of the conference. The proceedings is projected to be included in the IEEE or ACM Digital Library and indexed in all major indexing services accordingly. SPECIAL ISSUE Plans are underway to have the best papers, in extended version, selected for possible publication in a journal as special issue. Detailed information will soon be announced and will be made available on the conference website. If you have any questions about paper submission or the workshop, please contact the workshop organizers. IMPORTANT DATES Paper Submissions: ------------------------------------ April 15, 2017 - Extended Acceptance Notification: ------------------------------ April 28, 2017 Camera Ready Papers and Registration Due by: ---------- May 11, 2017 Conference Dates: ------------------------------------ July 17 – 21, 2017 WORKSHOP ORGANIZERS Prof. Hesham H. Ali Department of Computer Science College of Information Science and Technology University of Nebraska at Omaha Omaha, NE 68182 USA Email: hesham(a)unomaha.edu Prof. Mario Cannataro Department of Medical and Surgical Sciences University "Magna Græcia" of Catanzaro Viale Europa (Località Germaneto) 88100 Catanzaro, Italy Email: cannataro(a)unicz.it

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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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Announcement - NICO Hosts International Conference on Computational Social Science
by Northwestern Institute on Complex Systems 21 Nov '17

21 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. I have attached a PDF with further information. Feel free to forward this email to others if interested as well. Sincerely, Yasmeen Khan Business Coordinator, NICO?????????? [cid:image001.jpg@01D362AD.C692A580]

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1st CfP: international Metaheuristics Summer School - MESS 2018
by Mario Pavone 21 Nov '17

21 Nov '17

1st Call for Participation (apologies for multiple copies) ----------------------------------------------------------------------- MESS 2018 - Metaheuristics Summer School - from Design to Implementation - 21-25 July 2018, Taormina, Italy https://www.ANTs-lab.it/mess2018/ mess.school(a)ANTs-lab.it ----------------------------------------------------------------------- ** APPLICATION DEADLINE: 15th April 2018 ** MESS 2018 is aimed at qualified and strongly motivated MSc and PhD students; post-docs; young researchers, and both academic and industrial professionals to provide an overview on the several metaheuristics techniques, and an in-depth analysis of the state-of-the-art. As first edition, MESS 2018 wants to analyze all metaheuristics from its designing to its implementation. In particular, in MESS 2018 will be analyzed modern heuristic methods for search and optimization problems, as well as the classical exact optimization methods, seen also in the metaheuristics context. All participants will have plenty of opportunities for debate and work with leaders in the field, benefiting from direct interaction and discussions in a stimulating environment. They will also have the possibility to present their recently results and/or their working in progress through oral or poster presentations, and interact with their scientific peers, in a friendly and constructive environment. ** Confirmed Speakers + Christian Blum, IIIA-CSIC, Barcelona, Spain + Salvatore Greco, University of Catania, Italy & University of Portsmouth, UK + Gunther Raidl, Technische Universitat Wien, Austria + Celso Ribeiro, Universidade Federal Fluminense, Brazil + El-Ghazali Talbi, University of Lille 1, France + Daniele Vigo, University of Bologna, Italy More Speakers will be announced soon!! ** Short Talk and Poster Presentation All participants may submit an abstract of their recent results, or works in progress, for presentation and having the opportunities for debate and interact with leaders in the field. Mini-Workshop Organizers and Scientific Committee will review the abstracts and will recommend for the format of the presentation (oral or poster). All abstracts will be published on the electronic hands-out book of the summer school. The Abstracts must be submitted by *April 15, 2018*. ** School Directors + Salvatore Greco, University of Catania, Italy + Panos Pardalos, University of Florida, USA + Mario Pavone, University of Catania, Italy + El-Ghazali Talbi, University of Lille 1, France + Daniele Vigo, University of Bologna, Italy ** Oral & Poster Presentation Organizers + Luca Di Gaspero, Unviersity of Udine, Italy + Paola Festa, University of Naples "Federico II", Italy https://www.ANTs-lab.it/mess2018/ -- mess.school(a)ANTs-lab.it Facebook Group: https://www.facebook.com/groups/MetaheuristicsSchool/ Twitter: https://twitter.com/MESS_school -- Dr. Mario Pavone (PhD) Assistant Professor Department of Mathematics and Computer Science University of Catania V.le A. Doria 6 - 95125 Catania, Italy tel: 0039 095 7383034 fax: 0039 095 330094 Email: mpavone(a)dmi.unict.it http://www.dmi.unict.it/mpavone/ =========================================================== MESS 2018 - Metaheuristics Summer School 21-25 July 2018, Taormina, Italy W: https://www.ANTs-lab.it/mess2018/ E: mess.school(a)ANTs-lab.it FB: https://www.facebook.com/groups/MetaheuristicsSchool/ Twitter: https://twitter.com/MESS_school ===========================================================

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CFP- Complexis 2018: 3rd International Conference on Complexity, Future Information Systems and Risk Extended Deadline
by Anna Kobusińska 20 Nov '17

20 Nov '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: *Submission Deadline of POSITiON PAPERS: NOVEMBER 22, 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 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 ---------------------------- IMPORTANT DATES ---------------------------- Early registrations are accepted until: Conference Regular Papers: October 30, 2018 Conference Position Papers: January 24, 2018 Doctoral Consortium: February 7, 2018 Non-Speakers: February 7, 2018 Late registrations are accepted until: Non-Speakers: February 23, 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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computational.science November 2017