Proposals:GridComputing: Difference between revisions
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There is an increasing trend to deploy grid computing infrastructures to support computations on extremely large datasets like those found in the Visible Human Project. We therefore believe that it is important for critical aspects of the architecture of ITK revisited and refined to support the emerging standards in the grid computing community and to develop example applications to demonstrate the power of the ITK/grid combination in real-world research computing scenarios. | There is an increasing trend to deploy grid computing infrastructures to support computations on extremely large datasets like those found in the Visible Human Project. We therefore believe that it is important for critical aspects of the architecture of ITK revisited and refined to support the emerging standards in the grid computing community and to develop example applications to demonstrate the power of the ITK/grid combination in real-world research computing scenarios. | ||
Task 1: Survey of existing grid infrastructure software including the Globus Toolkit and associated middleware. Needs analysis of the bottlenecks in the current ITK as applied to collaborator projects within the SPL. Creation of initial ITK on grid computing examples using task-level parallelization of large population data sets (n > 1000). | '''Task 1:''' Survey of existing grid infrastructure software including the Globus Toolkit and associated middleware. Needs analysis of the bottlenecks in the current ITK as applied to collaborator projects within the SPL. Creation of initial ITK on grid computing examples using task-level parallelization of large population data sets (n > 1000). | ||
Other examples of task level parallelism include parametric search in which an algorithm is applied to a single or small number of data sets many times (n > 1000) with different parameter settings. | |||
Task | '''Task 2:''' Focus on optimizing the current ITK inner-loops and threading model for CPU architectures and compilers deployed as compute grid nodes. Work with computer science collaborators to identify bottlenecks that can benefit from machine-level code optimizations to accommodate issues such as cache size, special instruction sets, and memory bandwidth hierarchies in the context of a heterogeneous compute grid environment. | ||
Task 4: Ongoing support of ITK grid tools at the task, threading, and message passing layers. Review of any newly developed grid middleware emerging during the project period and rework of ITK architecture to accommodate same. | |||
'''Task 3:''' Integrate message passing parallelism using the globus compatible MPI implementations (mpich-g2 or its successors) first to distribute ITK processing pipelines to among grid processing nodes and second to break individual algorithms across nodes. | |||
'''Task 4:''' Ongoing support of ITK grid tools at the task, threading, and message passing layers. Review of any newly developed grid middleware emerging during the project period and rework of ITK architecture to accommodate same. | |||
== Compute platforms == | |||
We would like to get feedback about the compute platforms used in the ITK community. In particular, we would like to know what effort on which hardware platforms would have the largest impact on the community. | |||
CPU model family, user count: | |||
Intel : 1 | |||
AMD : 0 | |||
SPARC : 0 | |||
Revision as of 14:12, 7 August 2005
Development and extension of ITK to be applied to grid computing
For more information contact: Simon Warfield, Steve Pieper, Ron Kikinis
There is an increasing trend to deploy grid computing infrastructures to support computations on extremely large datasets like those found in the Visible Human Project. We therefore believe that it is important for critical aspects of the architecture of ITK revisited and refined to support the emerging standards in the grid computing community and to develop example applications to demonstrate the power of the ITK/grid combination in real-world research computing scenarios.
Task 1: Survey of existing grid infrastructure software including the Globus Toolkit and associated middleware. Needs analysis of the bottlenecks in the current ITK as applied to collaborator projects within the SPL. Creation of initial ITK on grid computing examples using task-level parallelization of large population data sets (n > 1000).
Other examples of task level parallelism include parametric search in which an algorithm is applied to a single or small number of data sets many times (n > 1000) with different parameter settings.
Task 2: Focus on optimizing the current ITK inner-loops and threading model for CPU architectures and compilers deployed as compute grid nodes. Work with computer science collaborators to identify bottlenecks that can benefit from machine-level code optimizations to accommodate issues such as cache size, special instruction sets, and memory bandwidth hierarchies in the context of a heterogeneous compute grid environment.
Task 3: Integrate message passing parallelism using the globus compatible MPI implementations (mpich-g2 or its successors) first to distribute ITK processing pipelines to among grid processing nodes and second to break individual algorithms across nodes.
Task 4: Ongoing support of ITK grid tools at the task, threading, and message passing layers. Review of any newly developed grid middleware emerging during the project period and rework of ITK architecture to accommodate same.
Compute platforms
We would like to get feedback about the compute platforms used in the ITK community. In particular, we would like to know what effort on which hardware platforms would have the largest impact on the community.
CPU model family, user count: Intel : 1 AMD : 0 SPARC : 0
