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The 1st Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS)
http://dsl.cs.uchicago.edu/MTAGS08/
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November 17, 2008
Austin, Texas, USA

Co-located with with IEEE/ACM International Conference for
High Performance Computing, Networking, Storage and Analysis (SC08)

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The 1st workshop on Many-Task Computing on Grids and Supercomputers (MTAGS)
will provide the scientific community a dedicated forum for presenting new
research, development, and deployment efforts of loosely coupled large scale
applications on large scale clusters, Grids, and/or Supercomputers. Many-task
computing, the theme of the workshop encompasses loosely coupled applications,
which are generally composed of many tasks (both independent and dependent
tasks) to achieve some larger application goal. We welcome paper submissions
on all topics related to MTC on large scale systems. Papers will be
peer-reviewed, and accepted papers will be published by IEEE/ACM through the
SC08 proceedings (pending approval). For more information, please visit
http://dsl.cs.uchicago.edu/MTAGS08/.

Scope
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This workshop will focus on the ability to manage and execute large scale
applications on today's largest clusters, Grids, and Supercomputers. Clusters
with 50K+ processor cores are beginning to come online (i.e. TACC Sun
Constellation System - Ranger), Grids (i.e. TeraGrid) with a dozen sites and
100K+ processors, and supercomputers with 160K processors (i.e. IBM BlueGene/P).
Large clusters and supercomputers have traditionally been high performance
computing (HPC) systems, as they are efficient at executing tightly coupled
parallel jobs within a particular machine with low-latency interconnects; the
applications typically use message passing interface (MPI) to achieve the needed
inter-process communication. On the other hand, Grids have been the preferred
platform for more loosely coupled applications that tend to be managed and
executed through workflow systems. In contrast to HPC (tightly coupled
applications), these loosely coupled applications make up a new class of
applications as what we call Many-Task Computing (MTC). MTC systems generally
involve the execution of independent, sequential jobs that can be individually
scheduled on many different computing resources across multiple administrative
boundaries. MTC systems typically achieve this using various grid computing
technologies and techniques, and often times use files to achieve the
inter-process communication as alternative communication mechanisms than MPI.
MTC is reminiscent to High Throughput Computing (HTC); however, MTC differs
from HTC in the emphasis of using many computing resources over short periods
of time to accomplish many computational tasks, where the primary metrics are
measured in seconds (e.g. FLOPS, tasks/sec, MB/s I/O rates). HTC on the other
hand requires large amounts of computing for longer times (months and years,
rather than hours and days, and are generally measured in operations per month).

Today's existing HPC systems are a viable platform to host MTC applications.
However, some challenges arise in large scale applications when run on large
scale systems, which can hamper the efficiency and utilization of these large
scale systems. These challenges vary from local resource manager scalability
and granularity, efficient utilization of the raw hardware, shared file system
contention and scalability, reliability at scale, application scalability, and
understanding the limitations of the HPC systems in order to identify good
candidate MTC applications.

For more information, please visit http://dsl.cs.uchicago.edu/MTAGS08/.

Topics
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MTAGS 2008 topics of interest include, but are not limited to:
* Compute Resource Management in large scale clusters, large Grids, and Supercomputers
o Scheduling
o Job execution frameworks
o Local resource manager extensions
o Performance evaluation of resource managers in use on large scale systems
o Challenges in running many-task workloads on HPC systems
* Data Management in large scale Grid and Supercomputer environments:
o Data-Aware Scheduling
o Shared File System performance and scalability in large deployments
o Distributed file systems
o Data caching frameworks and techniques
* Large-Scale Workflow Systems
o Workflow system performance and scalability analysis
o Scalability of workflow systems
o Workflow infrastructure and e-Science middleware
o Programming Paradigms and Models
* Large-Scale Many-Task Applications
o Large-scale many-task applications
o Large-scale many-task data-intensive applications
o Large-scale high throughput computing (HTC) applications
o Quasi-supercomputing applications, deployments, and experiences

Paper Submission and Publication
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Authors are invited to submit papers with unpublished, original work of not more
than 6/10 pages (6 pages for short papers, and 10 pages for standard papers) of
double column text using single spaced 9 point size on 8.5 x 11 inch pages, as
per ACM 8.5 x 11 manuscript guidelines
(http://www.acm.org/sigs/publications/proceedings-templates).
Papers conforming to the above guidelines (in PDF format) can be submitted via
email to yozha@microsoft.com and iraicu@cs.uchicago.edu before the deadline of
August 15th, 2008; please use the subject "MTAGS paper submission". Accepted
papers from this workshop will be published by IEEE/ACM through the SC08 proceedings
(pending approval). Selected excellent work may be eligible for additional
post-conference publication as journal articles or book chapters. Submission
implies the willingness of at least one of the authors to register and present
the paper. For more information, please visit http://dsl.cs.uchicago.edu/MTAGS08/.

Important Dates
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* Papers Due: August 15th, 2008
* Notification of Acceptance: October 1st, 2008
* Camera Ready Papers Due: October 15th, 2008
* Workshop Date: November 17th, 2008

Committee Members
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Workshop Chairs
* Yong Zhao, Microsoft
* Ian Foster, University of Chicago & Argonne National Laboratory
* Ioan Raicu, University of Chicago

Technical Committee
* Ian Foster, University of Chicago & Argonne National Laboratory
* David Abramson, Monash University
* Dan Ardelean, Google
* Pete Beckman, Argonne National Laboratory
* Bob Grossman, University of Illinois at Chicago
* Indranil Gupta, University of Illinois at Urbana Champaign
* Tevfik Kosar, Louisiana State University
* Chuang Liu, Ask.com
* Shiyong Lu, Wayne State University
* Reagan Moore, University of California at San Diego
* Cristina Nita-Rotaru, Purdue University
* Marlon Pierce, Indiana University
* Ioan Raicu, University of Chicago
* Dan Reed, Microsoft
* Matei Ripeanu, University of British Columbia
* Alex Szalay, The Johns Hopkins University
* Douglas Thain, University of Notre Dame
* Mike Wilde, University of Chicago & Argonne National Laboratory
* Matthew Woitaszek, The University Corporation for Atmospheric Research
* Lingyun Yang, Yahoo Search
* Sherali Zeadally, University of the District of Columbia
* Yong Zhao, Microsoft