**by Rio Yokota**

### Abstract

Fast multipole methods (FMM) were originally developed for accelerating *N*-body problems in astrophysics and other particle based methods. A recent trend in HPC has been to use FMM in unconventional application areas. For example, the 2010 ACM Gordon Bell prize peak-performance paper applied the FMM to the deformation of red blood cells, while the 2009 price/performance paper used it for a turbulence simulation. The fact that the FMM is *O*(*N*), compute bound, and requires very little synchronization, makes it a favorable algorithm for next-generation architectures.

At the same time it has a wide range of applications and plenty of room for mathematical intervention, which makes it an interesting algorithm to study.

### Speaker Bio

Rio Yokota obtained his PhD in Mechanical Engineering from Keio University, Japan, in 2009, and was a postdoctoral researcher at the Department of Mathematics at Univeristy of Bristol from 2009-2010, and also at Mechanical Engineering Department at Boston University from 2010-2011. During his PhD, he worked on the implementation of fast multipole methods on special purpose machines such as MDGRAPE-3, and then on GPUs after CUDA was released. During his post-doc he has continued to work on fast multipole methods, and has recently developed a massively parallel auto-tuning FMM library, ExaFMM. His applications of interest range from turbulence to molecular dynamics. You can contact him at rio.yokota@kaust.edu.sa.