From cgf at isep.ipp.pt Sat Jun 6 18:32:24 2020 From: cgf at isep.ipp.pt (Carlos Ferreira) Date: Sat, 6 Jun 2020 19:32:24 +0100 Subject: [openstack-hpc] [held online] CFP: Big Data & Deep Learning in HPC (IEEE Xplore) - Extended deadline: June 28, 2020 Message-ID: Workshop on BIG DATA & DEEP LEARNING in HIGH PERFORMANCE COMPUTING (BDL2020) (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) (https://sbac2020.dcc.fc.up.pt/) 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. ------------------------------------ WORKSHOP ON BIG DATA & DEEP LEARNING IN HIGH PERFORMANCE COMPUTING ------------------------------------ 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. ------------------------------------ LIST OF TOPICS ------------------------------------ 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. ------------------------------------ KEY DATES ------------------------------------ Deadline for paper submission: ***June 28, 2020*** Author notification: July 22, 2020 Camera-ready version of papers: July 25, 2020 ------------------------------------ SUBMISSION ------------------------------------ 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 https://www.ieee.org/conferences/publishing/templates.html) All submissions should be made electronically through the EasyChair system: https://easychair.org/conferences/?conf=bdl2020 ------------------------------------ REGISTRATION ------------------------------------ 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 ------------------------------------ ORGANIZATION ------------------------------------ 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) Carlos Ferreira ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail at isep.ipp.pt | www.isep.ipp.pt From cgf at isep.ipp.pt Tue Jun 16 17:41:28 2020 From: cgf at isep.ipp.pt (Carlos Ferreira) Date: Tue, 16 Jun 2020 18:41:28 +0100 Subject: [openstack-hpc] CFP: IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD2020) - Deadline Extended (June 28, 2020) Message-ID: <7bf08c71-ca51-bcaf-387f-cc754497d1c0@isep.ipp.pt> SBAC-PAD 2020 32nd IEEE International Symposium on Computer Architecture and High Performance Computing September 8-11, 2020 Porto, Portugal sbac2020 at dcc.fc.up.pt https://sbac2020.dcc.fc.up.pt/ http://www2.sbc.org.br/sbac/ (Historical acceptance rate). ---------------------------------------------------------------------------- ** NEW ** ---------------------------------------------------------------------------- SBAC-PAD2020 deadline postponed to June 28, 2020 ---------------------------------------------------------------------------- Following the recommendations/guidelines from the World Health Organization (WHO), regarding the Coronavirus disease (COVID-19) outbreak, SBAC-PAD2020 will be converted to an online event. However, the outbreak's impact led to several requests for postponing significantly the deadlines. Following those requests, the SBAC-PAD2020's organization decided to postpone the deadline for the abstract/paper submission to June 28, 2020. Stay safe! ---------------------------------------------------------------------------- Aims and Scope ---------------------------------------------------------------------------- SBAC-PAD is an international symposium, started in 1987, which has continuously presented an overview of new developments, applications, and trends in parallel and distributed computing technologies. SBAC-PAD is open for faculty members, researchers, specialists and graduate students around the world. In this edition, the symposium will be held at the University of Porto, Porto, Portugal. The city of Porto is famous for its Port wine and beautiful scenery, architecture and cultural events. More information about the conference can be found at https://sbac2020.dcc.fc.up.pt/ ---------------------------------------------------------------------------- Paper Submission ---------------------------------------------------------------------------- Authors are invited to submit original manuscripts on a wide range of high-performance computing areas, including computer architecture, systems software, languages and compilers, algorithms and applications. Topics of interest include (but are not limited to): -Application-specific systems -Architecture and Programming Support for Emerging Domains (Big Data, Deep Learning) -Benchmarking, performance measurements, and analysis -Cloud, Grid, cluster, and peer-to-peer systems -Embedded and pervasive systems -GPUs, FPGAs and other accelerator architectures -Languages, compilers, and tools for parallel and distributed programming -Modeling and simulation methodology -Operating systems and virtualization -Parallel and distributed systems, algorithms, and applications -Power and energy-efficient systems -Processor, cache, memory, storage, and network architecture -Real-world applications and case studies -Reconfigurable, resilient and fault-tolerant systems Submissions must be in English, 8 pages maximum, following the IEEE conference formatting guidelines. To be published in the conference proceedings and to be eligible for publication at the IEEE Xplore, at least one of the authors must register at the full rate and present her/his work. Authors may not use a single registration for multiple papers. Authors of selected papers will be invited to submit extended versions of their papers for publication on the Journal of Parallel and Distributed Computing. Paper submission will be done through EasyChair: https://www.easychair.org/conferences/?conf=sbacpad2020 ---------------------------------------------------------------------------- Important Dates ---------------------------------------------------------------------------- Abstract deadline: June 28, 2020 Paper deadline: June 28, 2020 Reviewing period: June 29 - July 15, 2020 Rebuttal period: July 15 - July 19, 2020 Author notification: July 22, 2020 Camera-ready submission: July 25, 2020 ---------------------------------------------------------------------------- Organizing Committee ---------------------------------------------------------------------------- General Chairs Inês Dutra,ines at dcc.fc.up.pt (University of Porto, Portugal) Jorge Barbosa,jbarbosa at fe.up.pt (University of Porto, Portugal) Miguel Areias,miguel-areias at dcc.fc.up.pt (University of Porto, Portugal) Program Co-chairs Jorge Barbosa (University of Porto, Portugal) Laurent Lefévre (Inria, ENS Lyon, University of Lyon, France) Lucia Drummond (Universidade Federal Fluminense, Brazil) Track Chairs Computer Architecture Chair: José Moreira, IBM Thomas J. Watson Research Center, USA Edson Borin, University of Campinas, Brazil Felipe França, State University of Rio de Janeiro, Brazil Gabriel Falcão, University of Coimbra, Portugal Jairo Panetta, Aeronautics Institute of Technology, Brazil Jean-Luc Gaudiot, University of California, USA Jose Cano, University of Glasgow, UK Leandro Santiago, Federal Fluminense University, Brazil Lluc Alvarez, Barcelona Supercomputing Center, Spain Nuno Roma, University of Lisbon, Portugal Peter Hofstee, IBM Austin Research Laboratory, USA Rodolfo Azevedo, University of Campinas, Brazil Serif Yesil, University of Illinois, USA Wagner Meira, Federal University of Minas Gerais, Brazil Networking and Distributed Systems Chair: Jesús Carretero, University Carlos III of Madrid, Spain Alexey Lastovetsky, University College Dublin, Ireland Angelos Bilas, FORTH-ICS and University of Crete, Greece Bruno Schulze, National Laboratory for Scientific Computing (LNCC), Brazil Carla Osthoff Barros, National Laboratory for Scientific Computing (LNCC), Brazil Domenico Talia, University of Calabria, Italy Emmanuel Jeannot, INRIA, France Jose Luis Gonzalez, Instituto Tecnológico de Ciudad Valles (ITV), México Leonel Sousa, Universidade de Lisboa, Portugal Marco Aldinucci, University of Torino, Italy Silvina Caino, University of Tennessee, USA Parallel Applications and Algorithms Chair: Alba Melo, University of Brasília, Brazil Alfredo Goldman, University of São Paulo, Brazil Ananth Kalyanaraman, Washington State University, USA Anne Benoit, ENS Lyon‐LIP, France Antonio J. Peña, Barcelona Supercomputing Center, Spain Bertil Schmidt, University of Mainz, Germany Cristiana Bentes, State University of Rio de Janeiro, Brazil Cristina Boeres, Federal Fluminense University, Brazil Edson Caceres, Federal University of Mato Grosso do Sul, Brazil George Teodoro, Federal University of Minas Gerais, Brazil Gianfranco Bilardi, University of Padova, Italy Jose Nelson Amaral, University of Alberta, Canada Luciana Arantes, Université Pierre et Marie Curie-Paris, France Ricardo Rocha, University of Porto, Portugal Viktor Prasanna, University of Southern California, USA Performance Evaluation Chair: Ariel Oleksiak, PoznaÅ„ Supercomputing and Networking Center, Poland Altino Sampaio, Instituto Politécnico do Porto, Portugal Aurélien Cavelan, University of Basel, Switzerland Frederic Suter, French National Institute of Nuclear and Particle Physics, France Georges Da Costa, Universite Toulouse III - Paul Sabatier, France Giovanni Agosta, Politecnico di Milano, Italy Hamid Arabnejad, Brunel University, UK Hongyang Sun, Vanderbilt University, USA Lucas Schnorr, Federal University of Rio Grande do Sul, Brazil Martin Schulz Technical University of Munich, Germany System Software Chair: Jidong Zhai, Tsinghua University, China Ang Li, Pacific Northwest National Laboratory, USA Chi Zhou, Shenzhen University, China Christoph Kessler, Linköping University, Sweden Clemens Grelck, University of Amsterdam, Netherlands Dandan Song, Beijing Institute of Technology, China Dazhao Cheng, University of North Carolina at Charlotte, USA Feng Zhang, Renmin University of China, China Guangyu Sun, Peking University, China Haikun Liu, Huazhong University of Science and Technology, China Mingyu Gao, Tsinghua University, China Philippe Navaux, Federal University of Rio Grande do Sul, Brazil Pradeep Kumar, William & Mary, USA Quan Chen, Shanghai Jiaotong University, China Shanjiang Tang, Tianjin University, China Shigang Li, ETH Zurich, Switzerland Teng Yu, Tsinghua University, China Vinod Rebello, Universidade Federal Fluminense, Brazil Zeyi Wen, National University of Singapore, Singapore Zhaoguo Wang, Shanghai Jiaotong University, China Carlos Ferreira ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail at isep.ipp.pt | www.isep.ipp.pt From cgf at isep.ipp.pt Tue Jun 16 17:51:30 2020 From: cgf at isep.ipp.pt (Carlos Ferreira) Date: Tue, 16 Jun 2020 18:51:30 +0100 Subject: [openstack-hpc] [held online] CFP: Big Data & Deep Learning in HPC (IEEE Xplore) - Extended deadline: June 28, 2020 Message-ID: <3bb3a866-dd26-87bb-0cba-c6c1df6d7865@isep.ipp.pt> Workshop on BIG DATA & DEEP LEARNING in HIGH PERFORMANCE COMPUTING (BDL2020) (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) (https://sbac2020.dcc.fc.up.pt/) September 9, 2020, Porto, Portugal BDL2020 will be held online (synchronous and/or asynchronous) ------------------------------------ KEY DATES ------------------------------------ Deadline for paper submission: ***June 28, 2020*** Author notification: July 22, 2020 Camera-ready version of papers: July 25, 2020 Carlos Ferreira ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail at isep.ipp.pt | www.isep.ipp.pt