 |
|
| |
Intelligent Optimization of Parallel and Distributed Applications
Bhupesh Bansal
Catalyurek, U.
Chame, J.
Chen, C.
Deelman, E.
Gil, Y.
Hall, M.
Vijay Kumar
Kurc, T.
Lerman, K.
Nakano, A.
Nelson, Y.-J.L.
Saltz, J.
Ashish Sharma
Priya Vashishta
Dept. of Phys. & Astron., Univ. of Southern California, Los Angeles, CA;
This paper appears in: Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
Publication Date: 26-30 March 2007
On page(s): 1-6
Location: Long Beach, CA,
ISBN: 1-4244-0910-1
INSPEC Accession Number: 9516783
Digital Object Identifier: 10.1109/IPDPS.2007.370490
Current Version Published: 2007-06-11
|
|
|
|
This paper describes a new project that systematically addresses the enormous complexity of mapping applications to current and future parallel platforms. By integrating the system layers - domain-specific environment, application program, compiler, run-time environment, performance models and simulation, and workflow manager - and through a systematic strategy for application mapping, our approach exploit the vast machine resources available in such parallel platforms to dramatically increase the productivity of application programmers. This project brings together computer scientists in the areas represented by the system layers (i.e., language extensions, compilers, run-time systems, workflows) together with expertise in knowledge representation and machine learning. With expert domain scientists in molecular dynamics (MD) simulation, we are developing our approach in the context of a specific application class which already targets environments consisting of several hundreds of processors. In this way, we gain valuable insight into a generalizable strategy, while simultaneously producing performance benefits for existing and important applications.
|
|
|
|
Index
Terms
Available to subscribers and IEEE members. |
|
|
|
References
Available to subscribers and IEEE members. |
|
|
|
Citing Documents
Available to subscribers and IEEE members. |
|
|
Cart
