Results 221 to 230 of about 21,831,698 (267)

PROBLEMS WITH DATA PARALLELISM

Parallel Processing Letters, 2001
The gradual evolution of language features and approaches used for the programming of distributed memory machines underwent substantial advances in the 1990s. One of the most promising and widely praised approaches was based on data parallelism and resulted in High Performance Fortran. This paper reports on an experiment using that approach based on a
C. PHILLIPS, R. PERROTT
openaire   +1 more source

Data Parallelism, Control Parallelism, and Related Issues

2000
This Chapter focuses on the differences between control parallelism and data parallelism, which are important to understand the discussion about parallel data mining in later Chapters of this book. After an introduction to control and data parallelism, we discuss the effect of exploiting these two kinds of parallelism in three important issues, namely ...
Alex A. Freitas, Simon H. Lavington
openaire   +1 more source

Kernel-control parallel versus data parallel

ACM SIGPLAN Notices, 1993
The dusty deck problem is the problem of how to automatically transform large existing serial/vector codes into a form suitable for efficient execution on new parallel architectures. Kernel-control parallel (KCP) methods provide a promising approach to solving the dusty deck problem for MIMD ...
openaire   +1 more source

Data Parallel Fortran

[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation, 1992
The authors present Data Parallel Fortran (DPF), a set of extensions to Fortran aimed at programming scientific applications on a variety of parallel machines. DPF portrays a global name space to programmers and allows programs to be written in a clear, data-parallel style.
P.M. Elustondo, L.A. Vazquez, O.J. Nestares, J.S. Avalos, G.A. Alvarez, C.-T. Ho, J.L.C. Sanz   +6 more
openaire   +1 more source

Data parallel Haskell

Proceedings of the 2007 workshop on Declarative aspects of multicore programming, 2007
We describe the design and current status of our effort to implement the programming model of nested data parallelism into the Glasgow Haskell Compiler. We extended the original programming model and its implementation, both of which were first popularised by the NESL language, in terms of expressiveness as well as efficiency.
Manuel M. T. Chakravarty, Roman Leshchinskiy, Simon Peyton Jones, Gabriele Keller, Simon Marlow   +4 more
openaire   +1 more source

On Parallelizing the MRRR Algorithm for Data-Parallel Coprocessors

2010
The eigenvalues and eigenvectors of a symmetric matrix are of interest in a myriad of applications. One of the fastest and most accurate numerical techniques for the eigendecomposition is the Algorithm of Multiple Relatively Robust Representations (MRRR), the first stable algorithm that computes the eigenvalues and eigenvectors of a tridiagonal ...
Christian Lessig, Paolo Bientinesi
openaire   +1 more source

Data-parallel, volumerendering algorithms

The Visual Computer, 1995
In this presentation, we consider the image-composition scheme for parallel volume rendering in which each processor is assigned a portion of the volume. A processor renders its data by using any existing volume-rendering algorithm. We describe one such parallel algorithm that also takes advantage of vector-processing capabilities. The resulting images
Roni Yagel, Raghu Machiraju
openaire   +1 more source

Parallel Data Mining

2002
Data mining refers to a process on nontrivial extraction of implicit, previously unknown and potential useful information (such as knowledge rules, constraints, regularities) from data in databases. With the availability of inexpensive storage and the progress in data capture technology, many organizations have created ultra-large databases of business
David Taniar, J. Wenny Rahayu
openaire   +1 more source

Data parallelism and Linda

1993
Is the owner-computes style of parallelism, captured in a variety of data parallel languages, attractive as a paradigm for designing explicitly parallel codes? This question gives rise to a number of others. Will such use be unwieldy? Will the resulting code run well?
N. Carriero, D. Gelernter
openaire   +1 more source

Data parallelism in Haskell

Proceedings of the 2nd ACM SIGPLAN workshop on Functional high-performance computing, 2013
The implicit data parallelism in collective operations on aggregate data structures constitutes an attractive parallel programming model for functional languages. Beginning with our work on integrating nested data parallelism into Haskell, we explored a variety of different approaches to array-centric data parallel programming in Haskell, experimented ...
openaire   +1 more source