HPC4BD 2015 : 2nd International Workshop on High Performance Computing for Big Data
Call For Papers
2nd International Workshop on High Performance Computing for Big Data (HPC4BD 2015)
to be held in conjunction with the 45th International Conference on Parallel Processing
September 1-4, 2015, Beijing, China.
Scope and Topics of Interest: Processing large datasets for extracting information and knowledge has always been a fundamental problem. Today this problem is further exacerbated, as the data a researcher or a company needs to cope with can be immense in terms of volume, distributed in terms of location, and unstructured in terms of format. Recent advances in computer hardware and storage technologies have allowed us to gather, store, and analyze such large-scale data. However, without scalable and cost effective algorithms that utilize the resources in an efficient way, neither the resources nor the data itself can serve to science and society at its full potential.
Analyzing Big Data requires a vast amount of storage and computing resources. We need to untangle the big, puzzling information we have and while doing this, we need to be fast and robust: the information we need may be crucial for a life-or-death situation. We need to be accurate: a single misleading information extracted from the data can cause an avalanche effect. Each problem has its own characteristic and priorities. Hence, the best algorithm and architecture combination is different for different applications.
This workshop aims to bring people who work on data-intensive and high performance computing in industry, research labs, and academia together to share their problems posed by the Big Data in various application domains and knowledge required to solve them.
All novel data-intensive computing techniques, data storage and integration schemes, and algorithms for cutting-edge high performance computing architectures which targets the utilization of Big Data 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 and MapReduce to analyze Big Data,
- energy-efficient data-intensive computing,
- 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.
- Berkant Barla Cambazoğlu, Yahoo Research
- Marco Canini, Université Catholique de Louvain
- Zhihui Du, Tsinghua University
- Xiaoliang Fan, Lanzhou University
- Yu Huashan, Peking University
- Vana Kalogeraki, Athens Uni. of Economics and Business
- Kamesh Madduri, Pennsylvania State University
- Fernando Pedone, University of Lugano
- Peter R. Pietzuch, Imperial College London
- Siva Rajamanickam, Sandia National Laboratories
- Erik Saule, University of North Carolina Charlotte
- Robert Soule, University of Lugano
- Weiqin Tong, Shanghai University
- Ata Türk, Boston University
- Bora Uçar, CNRS and LIP, ENS Lyon
Submission Guidelines: Paper submissions should be formatted according to the CPS standard double-column format with a font size 10pt or larger. Each paper is strictly limited to 10 pages in length. Submissions should represent original, substantive research results.
Instructions can be found at http://icpp2015.tsinghua.edu.cn/files/instruct8.5x11x2.pdf
Templates can be found at
- Latex: http://icpp2015.tsinghua.edu.cn/files/IEEECS_confs_LaTeX.ZIP
- Word: http://icpp2015.tsinghua.edu.cn/files/instruct8.5x11x2.doc
Papers can be submitted via EasyChair: https://easychair.org/conferences/?conf=hpc4bd2015
- Submission deadline: May 15, 2015
- Notification deadline: June 8, 2015
- Camera ready deadline: June 15, 2015
Kamer Kaya, Sabancı University, Turkey
Buğra Gedik, Bilkent University, Turkey
Ümit Çatalyürek, The Ohio State University, USA