@article{LGH97,
author={Christian Lengauer and Sergei Gorlatch and
Christoph A. Herrmann},
title={The Static Parallelization of Loops and
Recursions},
journal={J. Supercomputing},
volume=11,
number=4,
month=dec,
year=1997,
pages={\mbox{333--353}},
abstract={
We demonstrate approaches to the static parallelization of loops and
recursions on the example of the polynomial product. Phrased as a loop
nest, the polynomial product can be parallelized automatically by
applying a space-time mapping technique based on linear algebra and
linear programming. One can choose a parallel program that is optimal
with respect to some objective function like the number of execution
steps, processors, channels, etc. However, at best, linear execution
time complexity can be attained. Through phrasing the polynomial product
as a divide-and-conquer recursion, one can obtain a parallel program
with sublinear execution time. In this case, the target program is not
derived by an automatic search but given as a program skeleton, which
can be deduced by a sequence of equational program transformations.
We discuss the use of such skeletons, compare and assess the models in
which loops and divide-and-conquer recursions are parallelized and
comment on the performance properties of the resulting parallel
implementations.}
Christoph Herrmann