• [held online] CFP: Big Data & Deep Learning in HPC (IEEE XPlore) @Porto

    From Carlos Ferreira@21:1/5 to All on Wed May 13 02:49:32 2020
    Workshop on BIG DATA & DEEP LEARNING in HIGH PERFORMANCE COMPUTING (https://sbac2020.dcc.fc.up.pt/bdl2020/)

    in conjunction with the IEEE 32nd International Symposium on Computer Architecture and High
    Performance Computing (SBAC-PAD 2020)

    September 9, 2020, Porto, Portugal

    ** NEW ** BDL2020 will be held online (synchronous and/or asynchronous) ----------------------------------------------------------------------------

    We are monitoring the Coronavirus disease (COVID-19) outbreak and
    following the recommendations/guidelines from the World Health
    Organization (WHO) and the European Centre for Disease Prevention and
    Control (ECDC).

    The safety of all conference participants is our main priority. In
    this perspective, regardless of the outbreak outcomes in September, we
    will make BDL2020 an online (synchronous and/or asynchronous)
    event and we will maintain the regular publication activities, i.e.,
    accepted papers will be eligible for publication at the IEEE Xplore.

    The Workshop fee is now 200 euros.


    The number of very large data repositories (big data) is increasing in a rapid pace.
    Analysis of such repositories using the "traditional" sequential implementations of ML
    and emerging techniques, like deep learning, that model high-level abstractions in data
    by using multiple processing layers, requires expensive computational resources and long
    running times. Parallel or distributed computing are possible approaches that can make
    analysis of very large repositories and exploration of high-level representations
    feasible. Taking advantage of a parallel or a distributed execution of a ML/statistical
    system may: i) increase its speed; ii) learn hidden representations; iii) search a larger
    space and reach a better solution or; iv) increase the range of applications where it can
    be used (because it can process more data, for example). Parallel and distributed
    computing is therefore of high importance to extract knowledge from massive amounts of
    data and learn hidden representations.

    The workshop will be concerned with the exchange of experience among academics, researchers
    and the industry whose work in big data and deep learning require high performance
    computing to achieve goals. Participants will present recently developed algorithms/systems,
    on going work and applications taking advantage of such parallel or distributed environments.


    All novel data-intensive computing techniques, data storage and integration schemes, and
    algorithms for cutting-edge high performance computing architectures which targets Big Data
    and Deep Learning are of interest to the workshop. Examples of topics include but not
    limited to:
    - parallel algorithms for data-intensive applications;
    - scalable data and text mining and information retrieval;
    - using Hadoop, MapReduce, Spark, Storm, Streaming to analyze Big Data;
    - energy-efficient data-intensive computing;
    - deep-learning with massive-scale datasets;
    - querying and visualization of large network datasets;
    - processing large-scale datasets on clusters of multicore and manycore processors, and accelerators;
    - heterogeneous computing for Big Data architectures;
    - Big Data in the Cloud;
    - processing and analyzing high-resolution images using high-performance computing;
    - using hybrid infrastructures for Big Data analysis.
    - New algorithms for parallel/distributed execution of ML systems;
    - applications of big data and deep learning to real-life problems.


    Deadline for paper submission: May 25, 2020

    Author notification: July 1, 2020

    Camera-ready version of papers: July 25, 2020


    We invite authors to submit original work to BDL. All papers will be peer reviewed and accepted papers
    will be published in IEEE Xplore.

    Submissions must be in English, limited to 8 pages in the IEEE conference format (see

    All submissions should be made electronically through the EasyChair system: https://easychair.org/conferences/?conf=bdl2020


    A full registration to the workshop and presentation are needed in order to have your paper included
    in the workshop proceedings.

    The Workshop fee is 200 euros.

    Registration system available in https://sbac2020.dcc.fc.up.pt/bdl2020/registration.html


    Department of Computer Science, Faculty of Sciences, University of Porto

    Rua do Campo Alegre 1021/1055
    4169-007 Porto, Portugal

    The city of Porto is famous for its Port wine and beautiful scenery, architecture and cultural events.

    Portugal has again been awarded the best European Tourist Destination by the World Travel Awards, the Oscars equivalent
    in the field of tourism.


    Carlos Ferreira (LIAAD - INESC TEC LA and Polytechnic Institute of Porto)
    João Gama (LIAAD - INESC TEC LA and University of Porto)
    Albert Bifet (Telecom ParisTech)
    Miguel Areias (CRACS - INESC TEC LA and University of Porto)
    Rui Camacho (LIAAD -INESC TEC LA and University of Porto)

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