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7th Workshop on Many-Task Computing on Clouds, Grids, and Supercomputers (MTAGS) 2014
Co-located with Supercomputing/SC 2014In cooperation with ACM SIGHPC
New Orleans, Louisiana -- November 16th, 2014
News
- Program posted
- Panel announced: Many-Task Computing in a Big Data World
- Accepted papers
- "BoscoR: Extending R from the desktop to the Grid", Derek Weitzel, Jaime Frey, Marco Mambelli, Dan Fraser, Miha Ahronovitz, David Swanson
- "Energy Prediction for I/O Intensive Workflow Applications", Hao Yang, Lauro Costa, Matei Ripeanu
- "Overhead-Aware-Best-Fit (OABF) Resource Allocation Algorithm for Minimizing VM Launching Overhead", Hao Wu, Shangping Ren, Steven Timm, Gabriele Garzoglio, Seo-Young Noh
- "A Many-Task Parallel Approach for Multiscale Simulations of Subsurface Flow and Reactive Transport", Timothy Scheibe, Xiaofan Yang, Karen Schuchardt, Jared Chase, Bruce Palmer, Alexandre Tartakovsky
- "Lightweight Superscalar Task Execution in Distributed Memory", Asim YarKhan, Jack Dongarra
- Deadline extension to September 8th, 2014
- Confirmed keynote speakers:
- Dr. Owen O'Malley, Co-founder Hortonworks Inc.
- Michael Wilde, Fellow at University of Chicago and Software Architect at Argonne National Laboratory
- Call for Papers: ACM MTAGS 2014 -- abstracts due August 18th, 2014
- Call for Papers: Special Issue on Many-Task Computing in the Cloud, in the IEEE Transaction on Cloud Computing -- papers due February 2015
- Call for Papers: Special Issue on Scientific Cloud Computing in the IEEE Transactions on Cloud Computing -- papers due July 31st, 2014
- MTAGS14 PC posted
- The 6th Workshop on Many-Task Computing on Clouds, Grids, and Supercomputers (MTAGS) 2013 attracts over 100 attendees.
Overview
The 7th 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 7th workshop on Many-Task Computing on Clouds, Grids, and
Supercomputers (MTAGS14)
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.
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
- Paper submission: August 25th, 2014 September 8th, 2014
- Acceptance notification: September 29th, 2014
- Final papers due: October 6th, 2014
- Workshop date: November 16th, 2014
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/MTAGS2014/ before the deadline of September 8th, 2014 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 (in cooperation with SIGHPC). Notifications of the paper decisions will be sent out by September 29th, 2014. Accepted workshop papers will be eligible for additional post-conference publication as journal articles in the IEEE Transaction on Cloud Computing, Special Issue on Many-Task Computing in the Cloud (papers will be due in February 2015). 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/MTAGS14/.
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 Labs, USA
- Tim Armstrong, University of Chicago, USA
- Roger Barga, Microsoft, USA
- Mihai Budiu, Microsoft Research, USA
- Rajkumar Buyya University of Melbourne, Australia
- Kyle Chard, University of Chicago, USA
- Evangelinos Constantinos, Massachusetts Institute of Technology, USA
- Catalin Dumitrescu, Fermi National Labs, USA
- Haryadi Gunawi, University of Chicago, USA
- Indranil Gupta, University of Illinois at Urbana Champaign, USA
- Alexandru Iosup, Delft University of Technology, Netherlands
- Florin Isaila, Universidad Carlos III de Madrid, Spain & Argonne National Laboratory, USA
- Kamil Iskra, Argonne National Laboratory, USA
- Daniel S. Katz, University of Chicago, USA
- Jik-Soo Kim, Kristi, Korea
- Scott A. Klasky, Oak Ridge National Labs, USA
- Mike Lang, Los Alamos National Laboratory, USA
- Tonglin Li, Illinois Institute of Technology, USA
- Chris Moretti, Princeton University, USA
- David O'Hallaron, Carnegie Mellon University, USA
- Marlon Pierce, Indiana University, USA
- Judy Qiu, Indiana University, USA
- Lavanya Ramakrishnan, Lawrence Berkeley National Laboratory, USA
- Matei Ripeanu, University of British Columbia, Canada
- Iman Sadooghi, Illinois Institute of Technology, USA
- Wei Tang, Argonne National Laboratory, USA
- Edward Walker, Whitworth University, USA
- Ke Wang, Illinois Institute of Technology, USA
- Matthew Woitaszek, Walmart Labs, USA
- Rich Wolski, University of California, Santa Barbara, USA
- Zhifeng Yun, University of Houston, USA
- Zhao Zhang, University of California at Berkeley, USA
- Ziming Zheng, University of Chicago, USA
Sponsors
