
A systolic algorithm rhythmically computes and passes data through a network of processors. We investigate the performance of systolic algorithms for implementing the gravitational N-body problem on distributed-memory computers. Systolic algorithms minimize memory requirements by distributing the particles between processors. We show that the performance of systolic routines can be greatly enhanced by the use of non-blocking communication, which allows particle coordinates to be communicated at the same time that force calculations are being carried out. Hyper-systolic algorithms reduce the communication complexity at the expense of increased memory demands. As an example of an application requiring large N, we use the systolic algorithm to carry out direct-summation simulations using 10^6 particles of the Brownian motion of the supermassive black hole at the center of the Milky Way galaxy. We predict a 3D random velocity of 0.4 km/s for the black hole.
33 pages, 10 postscript figures
FOS: Computer and information sciences, supermassive black hole, Astrophysics (astro-ph), systolic algorithm, gravitational \(N\)-body problem, FOS: Physical sciences, Equations of motion in general relativity and gravitational theory, Computational Physics (physics.comp-ph), Astrophysics, Milky Way galaxy, Numerical algorithms for specific classes of architectures, Computer Science - Distributed, Parallel, and Cluster Computing, Computational methods for problems pertaining to relativity and gravitational theory, Analysis of algorithms, distributed-memory computers, Distributed, Parallel, and Cluster Computing (cs.DC), Brownian motion, Physics - Computational Physics
FOS: Computer and information sciences, supermassive black hole, Astrophysics (astro-ph), systolic algorithm, gravitational \(N\)-body problem, FOS: Physical sciences, Equations of motion in general relativity and gravitational theory, Computational Physics (physics.comp-ph), Astrophysics, Milky Way galaxy, Numerical algorithms for specific classes of architectures, Computer Science - Distributed, Parallel, and Cluster Computing, Computational methods for problems pertaining to relativity and gravitational theory, Analysis of algorithms, distributed-memory computers, Distributed, Parallel, and Cluster Computing (cs.DC), Brownian motion, Physics - Computational Physics
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