MTAGS 2010 - 3rd ACM Workshop on Many-Task Computing on Grids and Supercomputers 2010 (MTAGS 2010)

The 3rd ACM Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS) 2010
http://dsl.cs.uchicago.edu/MTAGS10/

November 15th, 2010
New Orleans, Louisiana, USA

Co-located with with IEEE/ACM International Conference for
High Performance Computing, Networking, Storage and Analysis (SC10)


The 3rd 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 large-scale many-task computing (MTC) applications on large scale
clusters, Grids, Supercomputers, and Cloud Computing infrastructure. MTC, 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. This workshop will cover challenges that can hamper efficiency and utilization in
running applications on large-scale systems, such as local resource manager scalability
and granularity, efficient utilization of raw hardware, parallel file system contention
and scalability, data management, I/O management, reliability at scale, and application
scalability. 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 in the
workshop proceedings as part of the ACM digital library (pending approval). The workshop
will be co-located with the IEEE/ACM Supercomputing 2010 Conference in New Orleans
Louisiana on November 15th, 2010. For more information, please see
http://dsl.cs.uchicago.edu/MTAGS010/.

Scope

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 now online (e.g. TACC Sun Constellation System - Ranger), Grids (e.g. TeraGrid)
with a dozen sites and 100K+ processors, and supercomputers with 150K~200K processors
(e.g. IBM BlueGene/P, Cray XT5); furthermore, new supercomputers are scheduled to come
online with 300K processor-cores and more than 1M threads (e.g. IBM Blue Waters). 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, commonly known to fit in the
high-throughput computing (HTC) paradigm.

Many-task computing (MTC) aims to bridge the gap between two computing paradigms, HTC and
HPC. MTC is reminiscent to HTC, but it differs in the emphasis of using many computing
resources over short periods of time to accomplish many computational tasks (i.e. including
both dependent and independent tasks), where the primary metrics are measured in seconds
(e.g. FLOPS, tasks/s, MB/s I/O rates), as opposed to operations (e.g. jobs) per month. MTC
denotes high-performance computations comprising multiple distinct activities, coupled via
file system operations. Tasks may be small or large, uniprocessor or multiprocessor,
compute-intensive or data-intensive. The set of tasks may be static or dynamic, homogeneous
or heterogeneous, loosely coupled or tightly coupled. The aggregate number of tasks,
quantity of computing, and volumes of data may be extremely large. MTC includes loosely
coupled applications that are generally communication-intensive but not naturally expressed
using standard message passing interface commonly found in HPC, drawing attention to the
many computations that are heterogeneous but not "happily" parallel.

There is more to HPC than tightly coupled MPI, and more to HTC than embarrassingly parallel
long running jobs. Like HPC applications, and science itself, applications are becoming
increasingly complex opening new doors for many opportunities to apply HPC in new ways if
we broaden our perspective. Some applications have just so many simple tasks that managing
them is hard. Applications that operate on or produce large amounts of data need
sophisticated data management in order to scale. There exist applications that involve many
tasks, each composed of tightly coupled MPI tasks. Loosely coupled applications often have
dependencies among tasks, and typically use files for inter-process communication. Efficient
support for these sorts of applications on existing large scale systems will involve
substantial technical challenges and will have big impact on science.

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,
parallel file system contention and scalability, data management, I/O management, reliability
at scale, application scalability, and understanding the limitations of the HPC systems in order
to identify good candidate MTC applications. Furthermore, the MTC paradigm can be naturally
applied to the emerging Cloud Computing paradigm due to its loosely coupled nature, which is
being adopted by industry as the next wave of technological advancement to reduce operational
costs while improving efficiencies in large scale infrastructures.

To see last year's workshop program agenda, and accepted papers and presentations, please see
http://dsl.cs.uchicago.edu/MTAGS09/; for the initial workshop we ran in 2008, please see
http://dsl.cs.uchicago.edu/MTAGS08/. We also ran a special issue on Many-Task Computing in the
IEEE Transactions on Parallel and Distributed Systems (TPDS) which will appear in November 2010,
which can be found at http://dsl.cs.uchicago.edu/TPDS_MTC/. We, the workshop organizers, also
published two papers that are highly relevant to this workshop. One paper is titled "Toward
Loosely Coupled Programming on Petascale Systems", and was published in SC08; the second paper
is titled "Many-Task Computing for Grids and Supercomputers", which was published in MTAGS08.

Topics

We invite the submission of original work that is related to the topics below. The papers can be
either short (5 pages) position papers, or long (10 pages) research papers. Topics of interest
include (in the context of Many-Task Computing):
* Compute Resource Management
* Scheduling
* Job execution frameworks
* Local resource manager extensions
* Performance evaluation of resource managers in use on large scale systems
* Dynamic resource provisioning
* Techniques to manage many-core resources and/or GPUs
* Challenges and opportunities in running many-task workloads on HPC systems
* Challenges and opportunities in running many-task workloads on Cloud Computing infrastructure
* Storage architectures and implementations
* Distributed file systems
* Parallel file systems
* Distributed meta-data management
* Content distribution systems for large data
* Data caching frameworks and techniques
* Data management within and across data centers
* Data-aware scheduling
* Data-intensive computing applications
* Eventual-consistency storage usage and management
* Programming models and tools
* Map-reduce and its generalizations
* Many-task computing middleware and applications
* Parallel programming frameworks
* Ensemble MPI techniques and frameworks
* Service-oriented science applications
* Large-Scale Workflow Systems
* Workflow system performance and scalability analysis
* Scalability of workflow systems
* Workflow infrastructure and e-Science middleware
* Programming Paradigms and Models
* Large-Scale Many-Task Applications
* High-throughput computing (HTC) applications
* Data-intensive applications
* Quasi-supercomputing applications, deployments, and experiences
* Performance Evaluation
* Performance evaluation
* Real systems
* Simulations
* Reliability of large systems

Paper Submission and Publication

Authors are invited to submit papers with unpublished, original work of not more than 10 pages of
double column text using single spaced 10 point size on 8.5 x 11 inch pages, as per ACM 8.5 x 11
manuscript guidelines (http://www.acm.org/publications/instructions_for_p...);
document templates can be found at http://www.acm.org/sigs/publications/proceedings-t.... We
are also seeking position papers of no more than 5 pages in length. A 250 word abstract (PDF
format) must be submitted online at https://cmt.research.microsoft.com/MTAGS2010/ before the
deadline of August 25th, 2010 at 11:59PM PST; the final 5/10 page papers in PDF format will be
due on September 1st, 2010 at 11:59PM PST. Papers will be peer-reviewed, and accepted papers will
be published in the workshop proceedings as part of the ACM digital library (pending approval).
Notifications of the paper decisions will be sent out by October 1st, 2010. Selected excellent
work may be eligible for additional post-conference publication as journal articles or book
chapters; see last year's special issue in the IEEE Transactions on Parallel and Distributed
Systems (TPDS) at http://dsl.cs.uchicago.edu/TPDS_MTC/. 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/MTAGS10/.

Important Dates

* Abstract Due: August 25th, 2010
* Papers Due: September 1st, 2010
* Notification of Acceptance: October 1st, 2010
* Camera Ready Papers Due: November 1st, 2010
* Workshop Date: November 15th, 2010

Committee Members

Workshop Chairs
* Ioan Raicu, Illinois Institute of Technology
* Ian Foster, University of Chicago & Argonne National Laboratory
* Yong Zhao, Microsoft

Steering Committee
* Alok Choudhary, Northwestern University, USA
* Jack Dongara, University of Tennessee, USA
* Geoffrey Fox, Indiana University, USA
* Robert Grossman, University of Illinois at Chicago, USA
* Arthur Maccabe, Oak Ridge National Labs, USA
* Xian-He Sun, Illinois Institute of Technology, USA
* Manish Parashar, Rutgers University, USA

Technical Committee
* Mihai Budiu, Microsoft Research, USA
* Rajkumar Buyya, University of Melbourne, Australia
* Catalin Dumitrescu, Fermi National Labs, USA
* Alexandru Iosup, Delft University of Technology, Netherlands
* Florin Isaila, Universidad Carlos III de Madrid, Spain
* Daniel Katz, University of Chicago, USA
* Tevfik Kosar, Louisiana State University, USA
* Zhiling Lan, Illinois Institute of Technology, USA
* Ignacio Llorente, Universidad Complutense de Madrid, Spain
* Reagan Moore, University of North Carolina, Chappel Hill, USA
* Jose Moreira, IBM Research, USA
* Marlon Pierce, Indiana University, USA
* Lavanya Ramakrishnan, Lawrence Berkeley National Laboratory, USA
* Matei Ripeanu, University of British Columbia, Canada
* Alain Roy, University of Wisconsin Madison, USA
* Edward Walker, Texas Advanced Computing Center, USA
* Mike Wilde, University of Chicago & Argonne National Laboratory, USA
* Matthew Woitaszek, The University Coorporation for Atmospheric Research, USA
* Ken Yocum, University of California San Diego, USA