A parallel adaptive fast multipole method
- Stanford Univ., CA (United States). Computer Systems Lab.
The authors present parallel versions of a representative N-body application that uses Greengard and Rokhlin`s adaptive Fast Multipole Method (FMM). While parallel implementations of the uniform FMM are straightforward and have been developed on different architectures, the adaptive version complicates the task of obtaining effective parallel performance owing to the nonuniform and dynamically changing nature of the problem domains to which it is applied. They propose and evaluate two techniques for providing load balancing and data locality, both of which take advantage of key insights into the method and its typical applications. Using the better of these techniques, they demonstrate 45-fold speedups on galactic simulations on a 48-processor Stanford DASH machine, a state-of-the-art shared address space multiprocessor, even for relatively small problems. They also show good speedups on a 2-ring Kendall Square Research KSR-1. Finally, they summarize some key architectural implications of this important computational method.
- OSTI ID:
- 46206
- Report Number(s):
- CONF-931115-; TRN: IM9522%%207
- Resource Relation:
- Conference: Supercomputing conference on high performance computing and communications, Portland, OR (United States), 15-19 Nov 1993; Other Information: PBD: 1993; Related Information: Is Part Of Supercomputing `93: Proceedings; PB: 961 p.
- Country of Publication:
- United States
- Language:
- English
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