Parallel iteration of high-order Runge-Kutta methods with stepsize control
Journal of Computational and Applied Mathematics
The ADDAP system on the iPSC/860: automatic data distribution and parallelization
Journal of Parallel and Distributed Computing
A Programming Methodology for Dual-Tier Multicomputers
IEEE Transactions on Software Engineering - Special issue on architecture-independent languages and software tools for parallel processing
A Transformation Approach to Derive Efficient Parallel Implementations
IEEE Transactions on Software Engineering - Special issue on architecture-independent languages and software tools parallel processing
Deriving Array Distributions by Optimization Techniques
The Journal of Supercomputing
Approaches for Integrating Task and Data Parallelism
IEEE Concurrency
Irregular Coarse-Grain Data Parallelism under LPARX
Scientific Programming
| Hi-index | 0.00 |
We consider a generalization of the SPMD programming model to orthogonal processor groups. In this model different partitions of the processors into disjoint processor groups can be exploited simultaneously in a single parallel implementation. The parallel programming model is appropriate for grid based applications working in horizontal or vertical directions as well as and for mixed task and data parallel computations [2]. For those applications we propose a systematic development process for message-passing programs using orthogonal processor groups. The development process starts with a specification of tasks indicating horizontal and vertical sections. A mapping to orthogonal processor groups realizes a group SPMD execution model and a final transformation step generates the corresponding message-passing program.