Experiences with parallel N-body simulation

Pangfeng Liu, Sandeep N. Bhatt

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

This paper describes our experiences developing high-performance code for astrophysical N-body simulations. Recent N-body methods are based on an adaptive tree structure. The tree must be built and maintained across physically distributed memory; moreover, the communication requirements are irregular and adaptive. Together with the need to balance the computational work-load among processors, these issues pose interesting challenges and tradeoffs for high-performance implementation. Our implementation was guided by the need to keep solutions simple and general. We use a technique for implicitly representing a dynamical global tree across multiple processors which substantially reduces the programming complexity as well as the performance overheads of distributed memory architectures. The contributions include methods to vectorize the computation and minimize communication time which are theoretically and experimentally justified. The code has been tested by varying the number and distribution of bodies on different configurations of the Connection Machine CM-5. The overall performance on instances with 10 million bodies is typically over 48 percent of the peak machine rate, which compares favorably with other approaches.

Original languageEnglish
Pages (from-to)1306-1323
Number of pages18
JournalIEEE Transactions on Parallel and Distributed Systems
Volume11
Issue number12
DOIs
StatePublished - Dec 2000

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