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CALL FOR PAPERS

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BDL 2022

Workshop on Big Data & Deep Learning in High Performance Computing

in conjunction with IEEE SBAC-PAD 2022


Bordeaux, France, November 2-5, 2022

https://www.dcc.fc.up.pt/bdl2022/

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Aims and scope of BDL

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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 Machine Learning (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.



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Topics

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BDL 2022 invites papers on all topics in 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.

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Program Chairs

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João Gama, University of Porto, Portugal

Carlos Ferreira, Polytechnic Institute of Porto, Portugal

Miguel Areias, University of Porto, Portugal

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Program Committee

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TBA

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Important dates

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Submission deadline: July 30, 2022(AoE)

Author notification: September 2, 2022

Camera-ready: September 12, 2022

Registration deadline: September 14, 2022

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Paper submission

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Papers submitted to BDL 2022 must describe original research results

and must not have been published or simultaneously submitted anywhere

else.



Manuscripts must follow the IEEE conference formatting guidelines and

submitted via the EasyChair Conference Management System as one pdf

file. The strict page limit for initial submission and camera-ready

version is 8 pages in the aforementioned format.



Each paper will receive a minimum of three reviews by members of the

international technical program committee. Papers will be selected

based on their originality, relevance, technical clarity and quality

of presentation. At least one author of each accepted paper must

register for the BDL 2022 workshop and present the paper.

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Proceedings

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All accepted papers will be published at IEEE Xplore.

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