[hpc-announce] deadline extended to 9/18/2015: IEEE CG&A special issue on High Performance Visualization and Analysis

Wes Bethel ewbethel at lbl.gov
Sun Aug 30 08:10:31 CDT 2015


CFP URL: http://www.computer.org/web/computingnow/cgacfp3

IEEE Computer Graphics and Applications

IEEE CG&A Special Issue on High Performance Visualization and Analysis

*Extended deadline for final submissions* : 18 September 2015
Publication date: May/June 2016

(Note: the submission web page above is in the process of being updated.
It may continue to show the original submission date of 9/1/2015 for a
short while longer. The new extended deadline is 9/18/2015. Sorry for
any confusion.)

In the 27 years since the groundbreaking report by McCormick, DeFanti,
and Brown that coined the phrase “visualization in scientific
computing,” we have witnessed a dramatic growth in our ability to
collect and generate data. Concurrently, computing technology has
rapidly evolved from single-processor systems to large scale,
multi-petaflop systems comprised of 10Ks to 100Ks processors, with
processors having upwards of 100s of cores per chip. The confluence of
larger HPC systems, data sets of unprecedented size and complexity, and
complex lines of inquiry, gives rise to diverse and difficult research
challenges and opportunities for visualization and analysis that were
only dimly visible at the dawn of the field of scientific visualization.

We define high performance visualization and analysis as those methods
that are, by their design, capable of taking advantage of modern
computational platforms, either in whole or in part. “In whole” refers
to techniques that are capable of effectively using all computational
resources on today’s largest computational platforms. “In part” refers
to techniques that are specifically designed and implemented to take
advantage of new processor or system architectures in one way or another.

The upcoming Special Issue of IEEE Computer Graphics and Applications
will focus on High Performance Visualization and Analysis (HPVA). For
this special issue, we solicit papers presenting original research that
span a diversity of visualization and analysis topics including:

New algorithms and methods for knowledge discovery suitable for use on
modern computational platforms, methods that leverage the extreme-scale
concurrency of these platforms to solve a problem of extreme scale or
complexity.

Examples of new methods for visualization and analysis that are designed
to take advantage of new architectural features, such as deepening
memory hierarchies, extreme-scale concurrency, etc.; methods that
overcome the challenges inherent to modern HPC platforms where, for
example, it is increasingly expensive to move data through the memory
hierarchy and increasingly intractable to save full-resolution data to
persistent storage for subsequent analysis.
Case studies/applications of HPVA methods to solve knowledge discovery
problems in physical or social science, engineering, medicine, etc.
where there is a thematic element of size and/or complexity that is made
tractable through the use of new scalable methods making use of modern
HPC-class platforms.

Submission Guidelines

Articles should be no more than eight magazine pages, where a page is
800 words and a quarter-page image counts as 200 words. Please cite only
the 12 most relevant references, and consider providing technical
background in sidebars for nonexpert readers. Color images are
preferable and should be limited to 10. Visit the CG&A style and length
guidelines at www.computer.org/web/peerreviewmagazines/cga. We also
strongly encourage you to submit multimedia (videos, podcasts, and so
on) to enhance your article. Visit the CG&A supplemental guidelines at
www.computer.org/web/peerreviewmagazines/accga#supplemental.

Papers that do not follow these guidelines will result in publication
delays or administrative rejection. Thank you for your attention.

See http://www.computer.org/web/computingnow/cgacfp3 for additional
information.


-- 
Wes Bethel -- voice (510) 486-7353 -- fax (510) 486-5812 -- vis.lbl.gov


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