The 3rd workshop on Many-Task Computing on Grids and Supercomputers (MTAGS10) 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.



November 15th, 2010 Best Paper Award:
Timothy Armstrong, Mike Wilde, Daniel Katz, Zhao Zhang, Ian Foster. "Scheduling Many-Task Workloads on Supercomputers: Dealing with Trailing Tasks", 3rd IEEE Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS10) 2010
November 15th, 2010 Attendee Prize (Apple iPad 16GB):
Justin Luitjens, University of Utah
November 15th, 2010 We had an excellent turnout, with about 80 people attending throughout the day (9AM - 6:15PM).
November 12th, 2010 Papers are online
November 11th, 2010 New Workshop: The Second ACM Scientific Cloud Computing (ScienceCloud) 2011 Workshop, co-located with ACM HPDC 2011
November 1st, 2010 Keynote speaker: Roger Barga, PhD, Architect, Extreme Computing Group, Microsoft Research
October 29th, 2010 Workshop is sponsored by Illinois Institute of Technology, College of Science and Letters & Graduate College; we plan to have a best paper award and prizes for the attendees. Attend the workshop, and win an Apple iPad!
October 21st, 2010 Program is online
October 21st, 2010

Accepted papers:

October 13th, 2010 11 papers accepted (34% acceptance rate)
21 papers rejected
September 16th, 2010 41 abstract submissions received
32 full paper submissions received and under review
Final decisions will be announced by October 15th, 2010
August 26th, 2010 Deadline extension: Final papers are due September 15th, 2010
Due to numerous requests, we have extended the final paper deadline to September 15th, 2010
August 20th, 2010 New Workshop: The First International Workshop on Data Intensive Computing in the Clouds (DataCloud) 2011, co-located with IEEE IPDPS 2011
August 20th, 2010 The IEEE Transactions on Parallel and Distributed Systems journal, special issue on Many-Task Computing, has made its final decisions to include 10 papers of the 42 submitted papers, with an acceptance rate of 24%. The SI is planned to appear in print in January 2011.



The advent of computation can be compared, in terms of the breadth and depth of its impact on research and scholarship, to the invention of writing and the development of modern mathematics. Scientific Computing has already begun to change how science is done, enabling scientific breakthroughs through new kinds of experiments that would have been impossible only a decade ago. Today's science is generating datasets that are increasing exponentially in both complexity and volume, making their analysis, archival, and sharing one of the grand challenges of the 21st century. The support for data intensive computing is critical to advancing modern science as storage systems have experienced an increasing gap between its capacity and its bandwidth by more than 10-fold over the last decade. There is an emerging need for advanced techniques to manipulate, visualize and interpret large datasets. Scientific Computing is the key to many domains' "holy grail" of new knowledge, and comes in many shapes and forms, from high-performance computing (HPC) which is heavily focused on compute-intensive applications, high-throughput computing (HTC) which focuses on using many computing resources over long periods of time to accomplish its computational tasks, many-task computing (MTC) which aims to bridge the gap between HPC and HTC by focusing on using many resources over short periods of time, to data-intensive computing which is heavily focused on data distribution and harnessing data locality by scheduling of computations close to the data.

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). These High-End Computing (HEC) systems have traditionally been HPC systems, as they are efficient at executing tightly coupled parallel jobs within a particular machine with low-latency interconnects; applications running on them 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 HTC paradigm.

MTC aims to bridge the gap between the 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 typically 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 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.

This workshop encourages interaction and cross-pollination between those developing applications, algorithms, software, hardware and networking, emphasizing many-task computing for large-scale distributed systems. We believe the workshop will be an excellent place to help the community define the current state-of-the-art, determine future goals, and define architectures and services for future high-end computing infrastructure. 

For more information about the workshop, please see http://www.cs.iit.edu/~iraicu/MTAGS10/. 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, and it 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.



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):

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 IEEE 8.5 x 11 manuscript guidelines; document templates can be found at ftp://pubftp.computer.org/Press/Outgoing/proceedings/instruct8.5x11.pdf and ftp://pubftp.computer.org/Press/Outgoing/proceedings/instruct8.5x11.doc. We are also seeking position papers of no more than 5 pages in length. A 250 word abstract as well as the full paper submission (PDF format) must be submitted online at https://cmt.research.microsoft.com/MTAGS2010/ before the extended deadline of September 15th, 2010 at 11:59PM PST. Papers will be peer-reviewed, and accepted papers will be published in the workshop proceedings as part of the IEEE digital library (pending approval). Notifications of the paper decisions will be sent out by October 15th, 2010. Selected excellent work may be eligible for additional post-conference publication as journal articles or book chapters; see this year's ongoing 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://www.cs.iit.edu/~iraicu/MTAGS10/


Important Dates

Abstract Due:                                             August 25th, 2010 September 15th, 2010

Papers Due:                                               September 1st, 2010 September 15th, 2010

Notification of Acceptance:                   October 1st, 2010 October 15th, 2010

Camera Ready Papers Due:                  November 11th, 2010

Workshop Date:                                        November 15th, 2010


Committee Members

Workshop Chairs

Steering Committee

Technical Committee



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