The Bridge from Present (Sequential) Systems to Future (Parallel) Systems: The Parallel Programming Environments Express and CSTools

1990 ◽  
pp. 175-194
Author(s):  
Patrick Van Renterghem
Keyword(s):  
Parallel Programming ◽  
Parallel Systems ◽  
Programming Environments ◽  
Sequential Systems

scholarly journals Run-Time and Compiler Support for Programming in Adaptive Parallel Environments

1997 ◽  
Vol 6 (2) ◽  
pp. 215-227 ◽  
Author(s):  
Guy Edjlali ◽  
Gagan Guyagrawal ◽  
Alan Sussman ◽  
Jim Humphries ◽  
Joel Saltz
Keyword(s):  
Parallel Programming ◽  
High Performance ◽  
Navier Stokes ◽  
Programming Environments ◽  
Data Parallel ◽  
Adaptive Environment ◽  
Run Time ◽  
Time Required ◽  
The Cost ◽  
Performance Results

For better utilization of computing resources, it is important to consider parallel programming environments in which the number of available processors varies at run-time. In this article, we discuss run-time support for data-parallel programming in such an adaptive environment. Executing programs in an adaptive environment requires redistributing data when the number of processors changes, and also requires determining new loop bounds and communication patterns for the new set of processors. We have developed a run-time library to provide this support. We discuss how the run-time library can be used by compilers of high-performance Fortran (HPF)-like languages to generate code for an adaptive environment. We present performance results for a Navier-Stokes solver and a multigrid template run on a network of workstations and an IBM SP-2. Our experiments show that if the number of processors is not varied frequently, the cost of data redistribution is not significant compared to the time required for the actual computation. Overall, our work establishes the feasibility of compiling HPF for a network of nondedicated workstations, which are likely to be an important resource for parallel programming in the future.

scholarly journals Native and generic parallel programming environments on a transputer and a PowerPC platform

1996 ◽  
Vol 8 (1) ◽  
pp. 19-46 ◽  
Author(s):  
A.G. Hoekstra ◽  
P.M.A. Sloot ◽  
F. van der Linden ◽  
M. van Muiswinkel ◽  
J.J.J. Vesseur ◽  
...  
Keyword(s):  
Parallel Programming ◽  
Programming Environments

scholarly journals Performance Comparison of Parallel Programming Environments for Implementing AIAC Algorithms

2006 ◽  
Vol 35 (3) ◽  
pp. 227-244 ◽  
Author(s):  
Jacques M. Bahi ◽  
Sylvain Contassot-Vivier ◽  
Raphaël Couturier
Keyword(s):  
Parallel Programming ◽  
Performance Comparison ◽  
Programming Environments

scholarly journals Temporal Interaction Diagrams for Multi-Process Environments

2003 ◽  
pp. 143-155
Author(s):  
T. Y. Chen ◽  
Iyad Rahwan ◽  
Yun Yang
Keyword(s):  
Parallel Programming ◽  
Linear Form ◽  
Temporal Order ◽  
Parallel Systems ◽  
Interaction Diagram ◽  
Parallel Processes ◽  
Order Constraints ◽  
Graphical View ◽  
Temporal Interaction ◽  
Design And Testing

This chapter introduces a novel notion of temporal interaction diagrams for distributed and parallel programming. An interaction diagram is a graphical view of computation processes and communication between different entities in distributed and parallel processes. It can be used for the specification, implementation and testing of interaction policies in distributed and parallel systems. Expressing interaction diagrams in a linear form, known as fragmentation, facilitate automation of design and testing of such systems. Existing interaction diagram formalisms lack the flexibility and capability of describing more general temporal order constraints. They only support rigid temporal order, and, hence, have limited semantic expressiveness. We propose an improved interaction diagram formalism in which more general temporal constraints can be expressed. This enables us to capture multiple valid interaction sequences using a single interaction diagram.

Mixed Parallel Programming Models Using Parallel Tasks

2010 ◽  
pp. 246-275 ◽  
Author(s):  
Joerg Duemmler ◽  
Thomas Rauber ◽  
Gudula Ruenger
Keyword(s):  
Parallel Programming ◽  
Heterogeneous Systems ◽  
Parallel Systems ◽  
Programming Models ◽  
Medium Size ◽  
Data Parallelism ◽  
Communication Structure ◽  
Parallel Tasks ◽  
Parallel Programming Models ◽  
The Future

Parallel programming models using parallel tasks have shown to be successful for increasing scalability on medium-size homogeneous parallel systems. Several investigations have shown that these programming models can be extended to hierarchical and heterogeneous systems which will dominate in the future. In this chapter, the authors discuss parallel programming models with parallel tasks and describe these programming models in the context of other approaches for mixed task and data parallelism. They discuss compiler-based as well as library-based approaches for task programming and present extensions to the model which allow a flexible combination of parallel tasks and an optimization of the resulting communication structure.

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