Speedup for Multi-Level Parallel Computing

This paper studies the speedup for multi-level parallel computing. Two models of parallel speedup are considered, namely, fixed-size speedup and fixed-time speedup. Based on these two models, we start with the speedup formulation that takes into account uneven allocation and communication latency, a...

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Vydáno v:2012 26th IEEE International Parallel and Distributed Processing Symposium Workshops s. 537 - 546
Hlavní autoři: Shanjiang Tang, Bu-Sung Lee, Bingsheng He
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2012
Témata:
Abstracts
Computational modeling
E-Amdahl's Law
E-Gustafsons Law
Hardware
Multi-Level Parallel Computing
Optimization
Parallel processing
Programming
Resource management
ISBN:1467309745, 9781467309745
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Shrnutí:This paper studies the speedup for multi-level parallel computing. Two models of parallel speedup are considered, namely, fixed-size speedup and fixed-time speedup. Based on these two models, we start with the speedup formulation that takes into account uneven allocation and communication latency, and gives an accurate estimation. Next, we propose a high-level abstract case with providing a global view of possible performance enhancement, namely E-Amdahl's Law for fixed-size speedup and E-Gustafson's Law for fixed-time speedup. These two laws demonstrate seemingly opposing views about the speedup of multi-level parallel computing. Our study illustrates that they are not contradictory but unified and complementary. The results lead to a better understanding in the performance and scalability of multi-level parallel computing. The experimental results show that E-Amdahl's Law can be applied as a prediction model as well as a guide for the performance optimization in multi-level parallel computing.
ISBN:1467309745
9781467309745
DOI:10.1109/IPDPSW.2012.72