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Can I read Algorithm 967: A Distributed-Memory Fast Multipole Method for Volume Potentials on EtoBox?
Algorithm 967: A Distributed-Memory Fast Multipole Method for Volume Potentials by Dhairya Malhotra; George Biros is a Computer Science article available to read on EtoBox.
What is Algorithm 967: A Distributed-Memory Fast Multipole Method for Volume Potentials about?
The solution of a constant-coefficient elliptic Partial Differential Equation (PDE) can be computed using an integral transform: A convolution with the fundamental solution of the PDE, also known as a volume potential. We present a Fast Multipole Method (FMM) for computing volume potentials and use them to construct spatially adaptive solvers for the Poisson, Stokes, and low-frequency Helmholtz problems. Conventional N-body methods apply to discrete particle interactions. With volume potentials, one replaces the sums with volume integrals. Particle N-body methods can be used to accelerate such integrals. but it is more efficient to develop a special FMM. In this article, we discuss the efficient implementation of such an FMM. We use high-order piecewise Chebyshev polynomials and an octree data structure to represent the input and output fields and enable spectrally accurate approximation of the near-field and the Kernel Independent FMM (KIFMM) for the far-field approximation. For distributed-memory parallelism, we use space-filling curves, locally essential trees, and a hypercube-like communication scheme developed previously in our group. We present new near and far interaction tr
Who reads Algorithm 967: A Distributed-Memory Fast Multipole Method for Volume Potentials?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Dhairya Malhotra; George Biros
- Publisher
- Association for Computing Machinery; Association for Computing Machinery (ACM) (ISSN 0098-3500)
- Published
- 2016
- Language
- EN
- Field
- Computer Science (Physical Sciences)