January 05, 2011
The Object Oriented Data Technology (OODT) architecture, which was first developed at the NASA Jet Propulsion Laboratory as a way to make use of metadata to seek out distributed computing and data resources, has been selected as one of a small handful of projects that will receive management and resource support from the Apache Software Foundation.
As NASA notes, the OODT architecture was first intended “to build a national framework for data sharing, but soon other applications in physical science, medical research and ground data systems became apparent.”
It has already been used for a number of Earth-based scientific missions as well as a number of ongoing projects at the Jet Propulsion Laboratory (JPL) in the areas of astrophysics and climate change research.
There are a number of benefits that several at the JPL see by offering OODT as an open source package, including the fact that it will be opened to a wide base of developers who can build on the existing code, speed development and provide the “peer review process that pushes a certain development standard for the package.”
According to Chris Mattmann, one of the lead developers at JPL and Vice President of OODT at the Apache Software Foundation, “we regularly used open software in our daily JPL tasks and were impressed with the quality of code and vibrant nature of free and open source software communities…it was then decided that OODT should be released as an open source software package.
Full story at NASA
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.
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