July 25, 2011
Co-located with Supercomputing/SC 2011
Seattle Washington -- November 14th, 2011
Applications and experiments in all areas of science are becoming increasingly complex and more demanding in terms of their computational and data requirements. Some applications generate data volumes reaching hundreds of terabytes and even petabytes. As scientific applications become more data intensive, the management of data resources and dataflow between the storage and compute resources is becoming the main bottleneck. Analyzing, visualizing, and disseminating these large data sets has become a major challenge and data intensive computing is now considered as the “fourth paradigm” in scientific discovery after theoretical, experimental, and computational science.
The second international workshop on Data-intensive Computing in the Clouds (DataCloud-SC11) will provide the scientific community a dedicated forum for discussing new research, development, and deployment efforts in running data-intensive computing workloads on Cloud Computing infrastructures. The DataCloud-SC11 workshop will focus on the use of cloud-based technologies to meet the new data intensive scientific challenges that are not well served by the current supercomputers, grids or compute-intensive clouds. We believe the workshop will be an excellent place to help the community define the current state, determine future goals, and present architectures and services for future clouds supporting data intensive computing.
For more information about the workshop, please see http://datasys.cs.iit.edu/events/DataCloud-SC11/. To see the 1st workshop's program agenda, and accepted papers and presentations, please see http://www.cse.buffalo.edu/faculty/tkosar/datacloud2011/. We are also running a Special Issue on Data Intensive Computing in the Clouds in the Springer Journal of Grid Computing with a paper submission deadline of August 16th 2011, which will appear in print in June 2012.
Authors are invited to submit papers with unpublished, original work of not more than 10 pages of double column text using single spaced 10 point size on 8.5 x 11 inch pages, as per ACM 8.5 x 11 manuscript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_proceedings_volumes); document templates can be found at http://www.acm.org/sigs/publications/proceedings-templates. 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/DataCloud_SC11/ before the deadline of September 2nd, 2011 at 11:59PM PST; the final 5/10 page papers in PDF format will be due on September 9th, 2011 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 7th, 2011. Selected excellent work may be eligible for additional post-conference publication as journal articles. We are currently running a Special Issue on Data Intensive Computing in the Clouds in the Springer Journal of Grid Computing. 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/DataCloud-SC11/ or send email to firstname.lastname@example.org.
General Chairs (email@example.com)
The ever-growing complexity of scientific and engineering problems continues to pose new computational challenges. Thus, we present a novel federation model that enables end-users with the ability to aggregate heterogeneous resource scale problems. The feasibility of this federation model has been proven, in the context of the UberCloud HPC Experiment, by gathering the most comprehensive information to date on the effects of pillars on microfluid channel flow.
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
May 10, 2013 |
Australian visual effects company, Animal Logic, is considering a move to the public cloud.
May 10, 2013 |
Program provides cash awards up to $10,000 for the best open-source end-user applications deployed on 100G network.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.