TY - JOUR
T1 - Dynamic Pipeline Mapping (DPM)
AU - Moreno, A.
AU - César, E.
AU - Guevara, A.
AU - Sorribes, J.
AU - Margalef, T.
AU - Luque, E.
N1 - Funding Information:
This work was supported by MEC under contract TIN2007-64974.
PY - 2008
Y1 - 2008
N2 - Parallel/distributed application development is an extremely difficult task for non-expert programmers, and support tools are therefore needed for all phases of the development cycle of this kind of applications. In particular, dynamic performance tuning tools can take advantage of the knowledge about the application's structure given by a skeleton based programming tool. This study shows the definition of a strategy for dynamically improving the performance of pipeline applications. This strategy, which has been called Dynamic Pipeline Mapping, improves the application's throughput by gathering the pipe's fastest stages and replicating its slowest ones. We have evaluated the new algorithm by experimentation and simulation, and results show that DPM leads to significant performance improvements.
AB - Parallel/distributed application development is an extremely difficult task for non-expert programmers, and support tools are therefore needed for all phases of the development cycle of this kind of applications. In particular, dynamic performance tuning tools can take advantage of the knowledge about the application's structure given by a skeleton based programming tool. This study shows the definition of a strategy for dynamically improving the performance of pipeline applications. This strategy, which has been called Dynamic Pipeline Mapping, improves the application's throughput by gathering the pipe's fastest stages and replicating its slowest ones. We have evaluated the new algorithm by experimentation and simulation, and results show that DPM leads to significant performance improvements.
UR - https://www.scopus.com/pages/publications/51849105208
U2 - 10.1007/978-3-540-85451-7_32
DO - 10.1007/978-3-540-85451-7_32
M3 - Article
AN - SCOPUS:51849105208
SN - 0302-9743
SP - 295
EP - 304
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -