TY - GEN
T1 - Intelligent optimization of parallel and distributed applications
AU - Bansal, Bhupesh
AU - Catalyurek, Umit
AU - Chame, Jacqueline
AU - Chen, Chun
AU - Deelman, Ewa
AU - Gil, Yolanda
AU - Hall, Mary
AU - Kumar, Vijay
AU - Kure, Tahsin
AU - Lerman, Kristina
AU - Nakano, Aiichiro
AU - Nelson, Yoon Ju Lee
AU - Saltz, Joel
AU - Sharma, Ashish
AU - Vashishta, Priya
PY - 2007
Y1 - 2007
N2 - 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 will 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.
AB - 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 will 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.
UR - https://www.scopus.com/pages/publications/34548714046
U2 - 10.1109/IPDPS.2007.370490
DO - 10.1109/IPDPS.2007.370490
M3 - Conference contribution
AN - SCOPUS:34548714046
SN - 1424409101
SN - 9781424409105
T3 - Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM
BT - Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM
T2 - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007
Y2 - 26 March 2007 through 30 March 2007
ER -