Lorena A. Barba group
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Submitted: Inexact Krylov iterations and relaxation strategies with fast-multipole boundary element method
Submitted: 19 June 2015 This paper presents a method to algorithmically accelerate boundary element methods. The fast multipole method (FMM) is already used in this context to obtain O(N) computational complexity while solving a dense linear system. Using relaxed-accuracy matrix-vector multiplications in a Krylov solver, we can achieve speed-ups in the order of 4x... Continue »
Probing protein orientation near charged surfaces
First version submitted: 31 March 2015. Submission of split papers: June 7 & June 12. Accepted: 4 Sept. & 26 Dec. 2015. UPDATE: The material in the original manuscript was split in two papers, submitted to different peer-reviewed journals. The editorial decision on the first submission was that the paper was out of scope... Continue »
Finding the Force—Consistent Particle Seeding for Satellite Aerodynamics
At AIAA SciTech 2014 —the "largest event for aerospace research, development and technology in the world"—, this paper is part of the AIAA Modeling and Simulation Technologies Conference, in the session "Modeling and Simulation of Space Systems" (MST-07), to be held Jan. 17 (8:00 AM to 12:00 PM). The first author and speaker, J. Brent Parham, was a... Continue »
New paper published: CiSE journal
A new paper authored by Rio Yokota and Lorena Barba has appeared (published online 3 Jan. 2012) in Computing in Science and Engineering, the joint publication of the IEEE Computer Society and he American Institute of Physics. This paper presents a new hybrid treecode/FMM formulation that has been implemented in the ExaFMM code, recently released... Continue »
First exaFMM paper accepted
The first publication reporting our work towards advancing fast multipole methods (FMM) to be a prime algorithm for exascale systems has been accepted by the International Journal of High-Performance Computing Applications, IJHPCA. Our previous recent work showed scaling of an FMM on GPU clusters, with problem sizes in the order of billions of unknowns (Yokota... Continue »