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1st ACM Workshop on Scientific Cloud Computing (ScienceCloud) 2010
http://dsl.cs.uchicago.edu/ScienceCloud2010/
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June 21st, 2010
Chicago, Illinois, USA

Co-located with with ACM High Performance Distributed Computing Conference (HPDC) 2010

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Workshop Overview
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.

The 1st workshop on Scientific Cloud Computing (ScienceCloud) will provide the scientific
community a dedicated forum for discussing new research, development, and deployment
efforts in running these kinds of scientific computing workloads on Cloud Computing
infrastructures. The ScienceCloud workshop will focus on the use of cloud-based
technologies to meet new compute intensive and data intensive scientific challenges that
are not well served by the current supercomputers, grids or commercial clouds. What
architectural changes to the current cloud frameworks (hardware, operating systems,
networking and/or programming models) are needed to support science? Dynamic information
derived from remote instruments and coupled simulation and sensor ensembles are both
important new science pathways and tremendous challenges for current HPC/HTC/MTC
technologies. How can cloud technologies enable these new scientific approaches? How
are scientists using clouds? Are there scientific HPC/HTC/MTC workloads that are suitable
candidates to take advantage of emerging cloud computing resources with high efficiency?
What benefits exist by adopting the cloud model, over clusters, grids, or supercomputers?
What factors are limiting clouds use or would make them more usable/efficient?
This workshop encourages interaction and cross-pollination between those developing
applications, algorithms, software, hardware and networking, emphasizing scientific
computing for such cloud platforms. We believe the workshop will be an excellent place
to help the community define the current state, determine future goals, and define
architectures and services for future science clouds.

Topics of Interest
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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 Cloud Computing):
* scientific computing applications
o case studies on cloud computing
o case studies comparing clouds, cluster, grids, and/or supercomputers
o performance evaluation
* performance evaluation
o real systems
o cloud computing benchmarks
o reliability of large systems
* programming models and tools
o map-reduce and its generalizations
o many-task computing middleware and applications
o integrating parallel programming frameworks with storage clouds
o message passing interface (MPI)
o service-oriented science applications
* storage cloud architectures and implementations
o distributed file systems
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
* compute resource management
o dynamic resource provisioning
o scheduling
o techniques to manage many-core resources and/or GPUs
* high-performance computing
o high-performance I/O systems
o interconnect and network interface architectures for HPC
o multi-gigabit wide-area networking
o scientific computing tradeoffs between clusters/grids/supercomputers and clouds
o parallel file systems in dynamic environments
* models, frameworks and systems for cloud security
o implementation of access control and scalable isolation

Paper Submission and Publication
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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,
(including all text, figures, and references) as per ACM 8.5 x 11 manuscript guidelines
(http://www.acm.org/publications/instructions_for_proceedings_volumes); document
templates can be found at http://www.acm.org/sigs/publications/proceedings-templates.
A 250 word abstract (PDF format) must be submitted online at
https://cmt.research.microsoft.com/ScienceCloud2010/ before the deadline of February 1st,
2010 at 11:59PM PST; the final 10 page papers in PDF format will be due on March 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. Notifications of the paper
decisions will be sent out by April 1st, 2010. Selected excellent work will be invited to
submit extended versions of the workshop paper to a special issue journal. 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/ScienceCloud2010/.

Important Dates
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* Abstract Due: February 22nd, 2010
* Papers Due: March 1st, 2010
* Notification of Acceptance: April 1st, 2010
* Workshop Date: June 21st, 2010



Committee Members
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Workshop Chairs
* Pete Beckman, University of Chicago & Argonne National Laboratory
* Ian Foster, University of Chicago & Argonne National Laboratory
* Ioan Raicu, Northwestern University

Steering Committee
* Jeff Broughton, Lawrence Berkeley National Lab., USA
* Alok Choudhary, Northwestern University, USA
* Dennis Gannon, Microsoft Research, USA
* Robert Grossman, University of Illinois at Chicago, USA
* Kate Keahey, Nimbus, University of Chicago, Argonne National Laboratory, USA
* Ed Lazowska, University of Washington, USA
* Ignacio Llorente, Open Nebula, Universidad Complutense de Madrid, Spain
* David E. Martin, Argonne National Laboratory, Northwestern University, USA
* Gabriel Mateescu, Linkoping University, Sweden
* David O'Hallaron, Carnegie Mellon University, Intel Labs, USA
* Rich Wolski, Eucalyptus, University of California, Santa Barbara, USA
* Kathy Yelick, University of California at Berkeley, Lawrence Berkeley National Lab., USA

Technical Committee
* David Abramson, Monash University, Australia
* Roger Barga, Microsoft Research, USA
* Roy Campbell, University of Illinois at Urbana Champaign, USA
* Henri Casanova, University of Hawaii at Manoa, USA
* Brian Cooper, Yahoo! Research, USA
* Peter Dinda, Northwestern University, USA
* Geoffrey Fox, Indiana University, USA
* Adriana Iamnitchi, University of South Florida, USA
* Alexandru Iosup, Delft University of Technology, Netherlands
* James Hamilton, Amazon Web Services, USA
* Tevfik Kosar, Louisiana State University, USA
* Shiyong Lu, Wayne State University, USA
* Ruben S. Montero, Universidad Complutense de Madrid, Spain
* Reagan Moore, University of North Carolina, Chappel Hill, USA
* Lavanya Ramakrishnan, Lawrence Berkeley National Laboratory
* Matei Ripeanu, University of British Columbia, Canada
* Larry Rudolph, VMware, USA
* Marc Snir, University of Illinois at Urbana Champaign, USA
* Xian-He Sun, Illinois Institute of Technology, USA
* Mike Wilde, University of Chicago & Argonne National Laboratory, USA
* Alec Wolman, Microsoft Research, USA
* Yong Zhao, Microsoft, USA