828 research outputs found
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
Compiling vector pascal to the XeonPhi
Intel's XeonPhi is a highly parallel x86 architecture chip made by Intel. It has a number of novel features which make it a particularly challenging target for the compiler writer. This paper describes the techniques used to port the Glasgow Vector Pascal Compiler to this architecture and assess its performance by comparisons of the XeonPhi with 3 other machines running the same algorithms
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
A new parallelisation technique for heterogeneous CPUs
Parallelization has moved in recent years into the mainstream compilers, and the demand
for parallelizing tools that can do a better job of automatic parallelization is higher than
ever. During the last decade considerable attention has been focused on developing programming
tools that support both explicit and implicit parallelism to keep up with the
power of the new multiple core technology. Yet the success to develop automatic parallelising
compilers has been limited mainly due to the complexity of the analytic process
required to exploit available parallelism and manage other parallelisation measures such
as data partitioning, alignment and synchronization.
This dissertation investigates developing a programming tool that automatically parallelises
large data structures on a heterogeneous architecture and whether a high-level programming
language compiler can use this tool to exploit implicit parallelism and make use
of the performance potential of the modern multicore technology. The work involved the
development of a fully automatic parallelisation tool, called VSM, that completely hides
the underlying details of general purpose heterogeneous architectures. The VSM implementation
provides direct and simple access for users to parallelise array operations on the
Cellās accelerators without the need for any annotations or process directives. This work
also involved the extension of the Glasgow Vector Pascal compiler to work with the VSM
implementation as a one compiler system. The developed compiler system, which is called
VP-Cell, takes a single source code and parallelises array expressions automatically.
Several experiments were conducted using Vector Pascal benchmarks to show the validity
of the VSM approach. The VP-Cell system achieved significant runtime performance
on one accelerator as compared to the master processorās performance and near-linear
speedups over code runs on the Cellās accelerators. Though VSM was mainly designed for
developing parallelising compilers it also showed a considerable performance by running
C code over the Cellās accelerators
Development of an MSC language and compiler, volume 1
Higher order programming language and compiler for advanced computer software system to be used with manned space flights between 1972 and 198
Flight program language requirements. Volume 1: Executive summary
The activities and results of a study for the definition of flight program language requirements are described. A set of detailed requirements are presented for a language capable of supporting onboard application programming for the Marshall Space Flight Center's anticipated future activities in the decade of 1975-85. These requirements are based, in part, on the evaluation of existing flight programming language designs to determine the applicability of these designs to flight programming activities which are anticipated. The coding of benchmark problems in the selected programming languages is discussed. These benchmarks are in the form of program kernels selected from existing flight programs. This approach was taken to insure that the results of the study would reflect state of the art language capabilities, as well as to determine whether an existing language design should be selected for adaptation
Mainstream parallel array programming on cell
We present the E] compiler and runtime library for the āFā subset of
the Fortran 95 programming language. āFā provides first-class support for arrays,
allowing E] to implicitly evaluate array expressions in parallel using the SPU coprocessors
of the Cell Broadband Engine. We present performance results from
four benchmarks that all demonstrate absolute speedups over equivalent āCā or
Fortran versions running on the PPU host processor. A significant benefit of this
straightforward approach is that a serial implementation of any code is always
available, providing code longevity, and a familiar development paradigm
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