1st International Workshop on High Performance Computing for Big Data (HPC4BD 2014)
to be held in conjunction with the 43rd International Conference on Parallel Processing
September 9, 2014, Minneapolis, MN.
Web: http://bmi.osu.edu/~kamer/hpc4bd/hpc4bd.html

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.

Important Dates:
Submission deadline: May 08, 2014
Author notification: June 08, 2014
Camera ready deadline: June 15, 2014

Submission Guidelines: Papers should be formatted according to the IEEE
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.

Templates can be found at http://www.ieee.org/conferences_events/conferences/publishing/templates.html
Papers can be submitted via EasyChair: https://www.easychair.org/conferences/?conf=hpc4bd

Workshop Organizers:
Kamer Kaya, The Ohio State University, USA
Email: kamer@bmi.osu.edu

Buğra Gedik, Bilkent University, Turkey
Email: bgedik@cs.bilkent.edu.tr

Ümit Çatalyürek, The Ohio State University, USA
Email: umit@bmi.osu.edu