HPC4BD 2016 : 3rd International Workshop on High Performance Computing for Big Data
Call For Papers
3rd International Workshop on High Performance Computing for Big Data (HPC4BD 2016) to be held in conjunction with the 45rd International Conference on Parallel Processing (ICPP), August 16-19, 2016.
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, 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.
- Alfredo Buttari, CNRS and IRIT
- Marco Canini, Université catholique de Louvain
- Zhihui Du, Tsinghua University
- Yu Huashan, Peking University
- Tahsin Kurç, Stony Brook University
- Siva Rajamanickam, Sandia National Laboratories
- A. Erdem Sarıyüce, Sandia National Laboratories
- Erik Saule, University of North Carolina Charlotte
- Robert Soule, University of Lugano
- Hongyang Sun, ENS Lyon, INRIA
- Weiqin Tong, Shanghai University
- Ata Türk, Boston University
- Bora Uçar, CNRS and LIP, ENS Lyon
- Submission deadline: April 24, 2016
- Notification deadline: May 22, 2016
- Camera ready deadline: June 3, 2016
- Workshop data: August 16, 2016
Submission Guidelines: Paper submissions should be formatted according to the CPS standard double-column format with a font size 10 pt or larger. Each paper is strictly limited to 10 pages in length. Submissions should represent original, substantive research results. See the link for electronic paper submission instructions.
Proceedings of the conference and workshops will be available on CD or USB at the conference and will be submitted to IEEE Xplore and CSDL for EI indexing. No-show Policy: An accepted paper which is not presented in the conference will be excluded from the final proceedings submitted to IEEE Xplore and CSDL.
Papers can be submitted via EasyChair:
Kamer Kaya, Sabancı University, Turkey
Buğra Gedik, Bilkent University, Turkey
Ümit Çatalyürek, The Ohio State University, USA