Abstract
The present work attempts to integrate the independent efforts in the fast N-body community to create the fastest N-body library for many-core and heterogenous architectures. Focus is placed on low accuracy optimizations, in response to the recent interest to use FMM as a preconditioner for sparse linear solvers. A direct comparison with other state-of-the-art fast N-body codes demonstrates that orders of magnitude increase in performance can be achieved by careful selection of the optimal algorithm and low-level optimization of the code. The current N-body solver uses a fast multipole method with an efficient strategy for finding the list of cell-cell interactions by a dual tree traversal. A task-based threading model is used to maximize thread-level parallelism and intra-node load-balancing. In order to extract the full potential of the SIMD units on the latest CPUs, the inner kernels are optimized using AVX instructions.
Original language | English (US) |
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Pages (from-to) | 301-324 |
Number of pages | 24 |
Journal | Journal of Algorithms & Computational Technology |
Volume | 7 |
Issue number | 3 |
DOIs | |
State | Published - Sep 2013 |
ASJC Scopus subject areas
- Numerical Analysis
- Computational Mathematics
- Applied Mathematics