maximize


@inproceedings{RuSt01a,
  author = {Rumpf, M. and Strzodka, R.},
  title = {Using Graphics Cards for Quantized FEM Computations},
  booktitle = {VIIP Conference on Visualization and Image Processing},
  year = {2001},
  abstract = {Graphics cards exercise increasingly more computing power and are
	highly optimized for high data transfer volumes. In contrast typical
	workstations perform badly when data exceeds their processor caches.
	Performance of scientific computations very often is wrecked by this
	deficiency. Here we present a novel approach by shifting the computational
	load from the CPU to the graphics card. We represent data in images
	and operations on vectors in graphics operations on images. Broad
	access to graphics memory and parallel processing of image operands
	thus turns the graphics card into an ultrafast vector coprocessor.
	The presented strategy opens up a wide area of numerical applications
	for hardware acceleration. The implementations of Finite Element
	solvers for the linear heat equation and the anisotropic diffusion
	method in image processing underline its practicability. We explain
	the vector processor usage of graphics cards in detail. An extensive
	correspondence of vector and graphics operations is given and the
	decomposition of complex operations into hardware supported is explicated.
	We also sketch the realization of arbitrary number formats in graphics
	hardware and the consequences of the restricted precision. Finally,
	we propose slight modification and extensions which would further
	improve computational benefits and extend the range of applicability
	of the proposed approach. Computing in image processing is exemplarily
	depicted as an ideal field, where Finite Element methods are applied
	to images and ultimate number precision is not required.},
  pdf = {http://numod.ins.uni-bonn.de/research/papers/public/RuSt01a.pdf 1},
  html = {http://numerik.math.uni-duisburg.de/people/strzodka/projects/PPDE/}
}