4 research outputs found
A compiler extension for parallelizing arrays automatically on the cell heterogeneous processor
This paper describes the approaches taken to extend an array
programming language compiler using a Virtual SIMD Machine (VSM)
model for parallelizing array operations on Cell Broadband Engine heterogeneous
machine. This development is part of ongoing work at the
University of Glasgow for developing array compilers that are beneficial
for applications in many areas such as graphics, multimedia, image processing
and scientific computation. Our extended compiler, which is built
upon the VSM interface, eases the parallelization processes by allowing
automatic parallelisation without the need for any annotations or process
directives. The preliminary results demonstrate significant improvement
especially on data-intensive applications
Array languages and the N-body problem
This paper is a description of the contributions to the SICSA multicore challenge on many body
planetary simulation made by a compiler group at the University of Glasgow. Our group is part of
the Computer Vision and Graphics research group and we have for some years been developing array
compilers because we think these are a good tool both for expressing graphics algorithms and for
exploiting the parallelism that computer vision applications require.
We shall describe experiments using two languages on two different platforms and we shall compare
the performance of these with reference C implementations running on the same platforms. Finally
we shall draw conclusions both about the viability of the array language approach as compared to
other approaches used in the challenge and also about the strengths and weaknesses of the two, very
different, processor architectures we used
Two alternative implementations of automatic parallelisation
This paper is a description of the recent parallelising compilers
from our group at the University of Glasgow. Our group is part of
the Computer Vision and Graphics research group and we have for some
years been developing array compilers because we think these are a good
tool both for expressing graphics algorithms and for exploiting the parallelism
that computer vision applications require. We shall describe the
implementation of two different languages on two different platforms and
we shall compare the performance of these with reference C implementations
running on the same platforms. Finally we shall draw conclusions
both about the viability of the array language approach as compared to
other approaches used in the challenge and also about the strengths and
weaknesses of the two, very different, processor architectures we used