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8th Workshop on Many-Task Computing on Clouds, Grids, and Supercomputers (MTAGS) 2015
Co-located with Supercomputing/SC 2015Austin, Texas -- November 15th, 2015
News
- Location: Hilton Salon G (4th floor)
- Keynote from Daniel S. Katz on "Application Skeletons: Constructing and Using Abstract Many Task Applications in eScience"
- Workshop program has been posted!
- Deadline extension for paper submission to Friday September 18th, 2015
- Call for Papers: ACM MTAGS 2015 -- abstracts due September 4th, 2015
- The 7th Workshop on Many-Task Computing on Clouds, Grids, and Supercomputers (MTAGS) 2014 attracts over 70 attendees
Overview
The 8th workshop on Many-Task Computing on Clouds, 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, clouds, grids, and supercomputers. MTC, the theme of the workshop encompasses loosely coupled applications, which are generally composed of many 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 in theoretical, simulations, and systems topics with special consideration to papers addressing the intersection of petascale/exascale challenges with large-scale cloud computing. We invite the submission of original research work of 6 pages.
Scope
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.
As computing becomes a pervasive part of the scientific process,
there is a great opportunity to make powerful computing techniques,
previously reserved for projects with only the largest investments,
available to a broad scientific community.
The massive increase in concurrency provided by modern hardware presents
a challenge to scientific applications with large existing investments
in previously developed software and limited ability to redesign from
scratch using the latest programming models. Many-task computing (MTC)
studies technologies, simple and advanced, to rapidly compose highly
scalable applications from existing sequential codes. MTC encompasses
loosely coupled applications, which are generally composed of many tasks
(both independent and dependent tasks) to achieve some larger
application goal. Growing from the successes of Globus, Condor, and
national-scale grid computing infrastructures, MTC techniques have been
deployed on many systems from single many-core systems (leveraging
GPGPUs and Intel MIC accelerators), to the largest multi-petascale
high-performance computing (HPC) systems. The development and deployment
of these MTC systems have expanded the utility of the underlying
technologies and fed back to improve the performance and usability of
the technologies themselves. Similarly, technologies developed for cloud
computing (including MapReduce-based models) can provide additional
connections and innovations in computing techniques.
MTAGS is a unique venue
to promote HPC-related concepts to the broader scientific and cloud
computing communities.
We are entering into a “big data” era, as advances in networking,
instrumentation, simulation technologies, Internet computing and social
networks are producing data at an unprecedented rate.
The collection, storage, analysis and sharing of this data are
thus one of the greatest challenges in the 21st century. 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.
While commonly associated with Hadoop and related systems, technologies
from HPC and MTC are also applicable. This provides an opportunity to
exchange large-scale data management technologies between scientific
applications and industrial techniques, which is another emphasis of
MTAGS.
Scientific Computing is the key to many domains' "holy grail" of new
knowledge, and comes in many shapes and forms.
Exchange of ideas from HPC, MTC, and cloud communities is a
critical path to the adoption of advanced techniques to best utilize
emerging, highly concurrent systems.
Underlying techniques for concurrency and data processing
originating in the HPC space must be delivered to the broader community
to promote future investment in HPC research programs and, more
generally, advance scientific investigations.
The 8th workshop on Many-Task Computing on Clouds, Grids, and
Supercomputers (MTAGS15)
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. 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/distributed file system contention and scalability, data
management, I/O management, reliability at scale, and application
scalability. 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 series, see
http://datasys.cs.iit.edu/events/MTAGS. For this year’s workshop,
see
http://datasys.cs.iit.edu/events/MTAGS15. To see last year’s
workshop program agenda, and accepted papers and presentations, please
see
http://datasys.cs.iit.edu/events/MTAGS14. For the prior year
workshops, please see
http://datasys.cs.iit.edu/events/MTAGS13,
http://datasys.cs.iit.edu/events/MTAGS12,
http://datasys.cs.iit.edu/events/MTAGS11/,
http://datasys.cs.iit.edu/events/MTAGS10,
http://datasys.cs.iit.edu/events/MTAGS09 and http://datasys.cs.iit.edu/events/MTAGS08.
We also ran a special issue on Many-Task Computing in the IEEE
Transactions on Parallel and Distributed Systems (TPDS) which appeared
in June 2011, and it can be found at
http://datasys.cs.iit.edu/events/TPDS_MTC; the proceedings can be
found online at
http://www.computer.org/portal/web/csdl/abs/trans/td/2011/06/ttd201106toc.htm.
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, both of which have been highly cited, with 136 and 237
citations respectively.
Topics
We invite the submission of original work that is related to the topics below. The papers should be 6 pages, including all figures and references. We aim to cover topics related to Many-Task Computing on each of the three major distributed systems paradigms, Cloud Computing, Grid Computing and Supercomputing. Topics of interest include:
Compute resource management
o
Scheduling
o
Job execution frameworks
o
Local resource manager extensions
o
Performance evaluation of resource managers in use on large scale
systems
o
Dynamic resource provisioning
o
Techniques to manage extreme concurrency and accelerators
o
Challenges and opportunities in running many-task workloads on HPC
systems
o
Challenges and opportunities in running many-task workloads on Cloud
Computing infrastructure
Storage architectures and implementations
o
Distributed file systems
o
Parallel file systems
o
Distributed metadata management
o
Content distribution systems for large data
o
Data caching frameworks and techniques
o
Data management within and across data centers
o
Data-aware scheduling
o
Data-intensive computing applications
o
Eventual-consistency storage usage and management
Programming models and tools
o
MapReduce, its generalizations, and implementations
o
Many-task computing middleware and applications
o
Parallel programming frameworks
o
Ensemble MPI
o
Service-oriented science applications
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
High-throughput computing (HTC) applications
o
Data-intensive applications
o
Quasi-supercomputing applications, deployments, and experiences
o
Application coupling, integration, and composition
o
Algorithms for many-task applications- Monte Carlo, parameter
sweep/search, uncertainty quantification
o
Performance evaluation
Performance evaluation
o
Theoretical vs. real systems
o
Simulations
o
Reliability and fault tolerance of large systems
Important Dates
- Full paper due: September 18th, 2015
- Acceptance notification: October 2nd, 2015
- Early Registration deadline: October 15th, 2015
- Final papers due: November 6th, 2015
- Workshop date: November 15th, 2015
Paper Submission
Authors are invited to submit papers with unpublished, original work of not more than 6 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; document templates can be found at http://www.acm.org/sigs/publications/proceedings-templates. The final 6 page papers in PDF format must be submitted online at https://cmt.research.microsoft.com/MTAGS2015/ before the deadline. Papers will be peer-reviewed for novelty, scientific merit, and scope for the workshop. Submission implies the willingness of at least one of the authors to register and present the paper. For more information, please see http://datasys.cs.iit.edu/events/MTAGS15/.
Organization
General Chairs
- Ioan Raicu, Illinois Institute of Technology & Argonne National Laboratory, USA
- Ian Foster, University of Chicago & Argonne National Laboratory, USA
- Yong Zhao, University of Electronic Science and Technology of China, China
- Justin Wozniak, Argonne National Laboratory, USA
Steering Committee
- David Abramson, Monash University, Australia
- Jack Dongarra, University of Tennessee, USA
- Geoffrey Fox, Indiana University, USA
- Manish Parashar, Rutgers University, USA
- Marc Snir, Argonne National Laboratory & University of Illinois at Urbana Champaign, USA
- Xian-He Sun, Illinois Institute of Technology, USA
- Weimin Zheng, Tsinghua University, China
Program Committee
- Hasan Abbasi, Oak Ridge National Laboratory, USA
- Kyle Chard, University of Chicago, USA
- Yong Chen, Texas Tech University, USA
- Evangelinos Constantinos, Massachusetts Institute of Technology, USA
- Azzam Haidar, University of Tennessee, USA
- Florin Isaila, Universidad Carlos III de Madrid, Spain
- Kamil Iskra, Argonne National Laboratory, USA
- Daniel Katz, University of Chicago, USA
- Jik-Soo Kim, KISTI, Korea
- Mike Lang, Los Alamos National Laboratory, USA
- Tonglin Li, Illinois Institute of Technology, USA
- Ketan Maheshwari, Argonne National Laboratory, USA
- Christopher Moretti, Princeton University, USA
- Bogdan Nicolae, IBM Research, Ireland
- David O'Hallaron, Carnegie Mellon University, USA
- Ana-Maria Opresc, University of Amsterdam, Netherlands
- Judy Qui, Indiana University, USA
- Matei Ripeanu, University of British Columbia, Canada
- Iman Sadooghi, Illinois Institute of Technology, USA
- Wei Tang, Argonne National Laboratory, USA
- Ke Wang, Intel, USA
- Mike Wilde, University of Chicago & Argonne National Laboratory, USA
- Xingfu Wu, Texas A&M University, USA
- Zhao Zhang, University of California, Berkeley, USA
- Dongfang Zhao, Pacific Northwest National Laboratory, USA
- Ziming Zheng, HP Vertica, USA
Sponsors
TBA