Rapid changes in parallel computing technology are causing significant changes in the strategies being used for parallel algorithm development. One approach is simply to write computer code in a standard language like FORTRAN 77 or with the expectation that the compiler will produce executable code that will run in parallel. The alternatives are: (1) to build explicit message passing directly into the source code; or (2) to write source code without explicit reference to message passing or parallelism, but use a general communications library to provide efficient parallel execution. Application of these strategies is illustrated with examples of codes currently under development
Two basic technology gaps in today's parallel computers are: 1) too much latency in accessing o...
Abstract. The emerging discipline of algorithm engineering has primarily focussed on transforming pe...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/19...
In order to utilize parallel computers, four approaches, broadly speaking, to the provision of paral...
Parallel software development must face the fact that different architectures require different impl...
It is today's general wisdom that the productive use of parallel architectures depends cruciall...
Over the past few decades, scientific research has grown to rely increasingly on simulation and othe...
Abstract: Some approaches to choosing parallel features for computing systems are discusse...
The most important features that a parallel programming language should provide are portability, mod...
It has been suggested that non-scientific code has very little parallelism not already exploited by ...
Fortran and C++ are the dominant programming languages used in scientific computation. Consequently,...
We describe parallel extensions of sequential programming languages for writing pro-grams that integ...
Parallel programming is increasingly important for embedded systems as well as scientific computing ...
Parallel programming is designed for the use of parallel computer systems for solving time-consuming...
With the advent of Distributed Memory Machines (DMMs) numerous work have been undertaken to ease the...
Two basic technology gaps in today's parallel computers are: 1) too much latency in accessing o...
Abstract. The emerging discipline of algorithm engineering has primarily focussed on transforming pe...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/19...
In order to utilize parallel computers, four approaches, broadly speaking, to the provision of paral...
Parallel software development must face the fact that different architectures require different impl...
It is today's general wisdom that the productive use of parallel architectures depends cruciall...
Over the past few decades, scientific research has grown to rely increasingly on simulation and othe...
Abstract: Some approaches to choosing parallel features for computing systems are discusse...
The most important features that a parallel programming language should provide are portability, mod...
It has been suggested that non-scientific code has very little parallelism not already exploited by ...
Fortran and C++ are the dominant programming languages used in scientific computation. Consequently,...
We describe parallel extensions of sequential programming languages for writing pro-grams that integ...
Parallel programming is increasingly important for embedded systems as well as scientific computing ...
Parallel programming is designed for the use of parallel computer systems for solving time-consuming...
With the advent of Distributed Memory Machines (DMMs) numerous work have been undertaken to ease the...
Two basic technology gaps in today's parallel computers are: 1) too much latency in accessing o...
Abstract. The emerging discipline of algorithm engineering has primarily focussed on transforming pe...
This work was also published as a Rice University thesis/dissertation: http://hdl.handle.net/1911/19...