Speaker: Paul Mullowney, Tech-X Corporation, Boulder, CO.
Abstract:
The computational demand of many scientific modeling problems is growing
at a considerable rate. Until recently, this growing need was satisfied
primarily through the use of cluster or supercomputing. But for many
scientists and other end users, it would be more desirable to have high
performance code in their very own desktop or laptop computer. Modern
graphics processing units (GPUs) offer substantial power at very low
cost, however advanced programming skills and detailed hardware
knowledge are required to take advantage of these devices. In this talk,
we first discuss a library that allows GPU hardware to be accessed from
within High Level Languages like MATLAB, IDL, or Python. By abstracting
the GPU as a vector co-processor, computationally demanding data
analysis and simulation tasks can be accelerated by an order of
magnitude or more. Then, we switch gears and discuss more recent
GPU-based implementations of an advanced physics simulation, DSMC-PIC
(Direct Simulation Monte Carlo Particle-In-Cell). This simulation type
contains a number of challenging issues that must be overcome in order
to make effective use of the hardware. However, we shall see that even
in the most naive implementation, benefit can be obtained. We finish
with a discussion of possible future developments including
Electromagnetic and Electrostatic PIC.