We survey parallel programming models and languages using 6 criteria [:] should be easy to program, have a software development methodology, be architecture-independent, be easy to understand, guranatee performance, and provide info about the cost of programs. ... We consider programming models in 6 categories, depending on the level of abstraction they provide.

. In this paper we propose a methodology for structured parallel programming using functional skeletons to compose and coordinate concurrent activities written in a standard imperative language. Skeletons are higher order functional forms with built-in parallel behaviour. We show how such forms can be used uniformly to abstract all aspects of a parallel program's behaviour including data partitioning, placement and re-arrangement (communication) as well as computation. Skeletons are naturally data parallel and are capable of expressing computation and co-ordination at a higher level of abstraction than other process oriented co-ordination notations. Examples of the application of this methodology are given and an implementation technique outlined. 1 Introduction This paper proposes the use of skeletons as a coordination language for programming parallel architectures. The coordination language model, as proposed by Gelernter and Carriero, builds parallel programs out of two...

Portability, efficiency, and ease of coding are all important considerations in choosing the programming model for a scalable parallel application. The message-passing programming model is widely used because of its portability, yet some applications are too complex to code in it while also trying to maintain a balanced computation load and avoid redundant computations. The shared-memory programming model simplifies coding, but it is not portable and often provides little control over interprocessor data transfer costs.This paper describes a new approach, called Global Arrays (GA), that combines the better features of both other models, leading to both simple coding and efficient execution. The key concept of GA is that it provides a portable interface through which each process in a MIMD parallel program can asynchronously access logical blocks of physically distributed matrices, with no need for explicit cooperation by other processes. We have implemented GA libraries on a variety of...

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Portability, efficiency, and ease of coding are all important considerations in choosing the programming model for a scalable parallel application. The message-passing programming model is widely used because of its portability, yet some applications are too complex to code in it while also trying to maintain a balanced computation load and avoid redundant computations. The shared-memory programming model simplifies coding, but it is not portable and often provides little control over interprocessor data transfer costs. This paper describes an approach, called Global Arrays (GA), that combines the better features of both other models, leading to both simple coding and efficient execution. The key concept of GA is that it provides a portable interface through which each process in a MIMD parallel program can asynchronously access logical blocks of physically distributed matrices, with no need for explicit cooperation by other processes. We have implemented GA libraries on a variety of computer systems, including the Intel DELTA and Paragon, the IBM SP-1 and SP-2 (all message-passers), the Kendall Square KSR-1/2, Convex SPP-1200 (nonuniform access shared-memory machines), the Cray T3D (a globally-addressable distributed-memory computer) and networks of Unix workstations. We discuss the design and implementation of these libraries, report their performance, illustrate the use of GA in the context of computational chemistry applications, and describe the use of a GA performance visualization tool.

We present an overview of research at the CRPC designed to provide an efficient, portable programming model for scientific applications possessing both task and data parallelism. Fortran M programs exploit task parallelism by providing language extensions for user-defined process management and typed communication channels. A combination of compiler and run-time system support ensures modularity, safety, portability, and efficiency. Fortran D and High Performance Fortran programs exploit data parallelism by providing language extensions for user-defined data decomposition specifications, parallel loops, and parallel array operations. Compile-time analysis and optimization yield efficient, portable programs. We design an interface for using a task-parallel language to coordinate concurrent data-parallel computations. The interface permits concurrently executing data-parallel computations to interact through messages. A key notion underlying the proposed interface is the integration of F...

this paper, we discuss alternative approaches to the realization of this principle, which holds that properties of program components should be preserved when those components are composed in parallel with other program components. We review two programming languages, Strand and Program Composition Notation, that support compositionality via a small number of simple concepts, namely monotone operations on shared objects, a uniform addressing mechanism, and parallel composition. Both languages have been used extensively for large-scale application development, allowing us to provide an informed assessment of their strengths and weaknesses. We observe that while compositionality simplifies development of complex applications, the use of specialized languages hinders reuse of existing code and tools, and the specification of domain decomposition strategies. This suggests an alternative approach based on small extensions to existing sequential languages. We conclude the paper with a discussion of two languages that realize this strategy. Categories and Subject Descriptors: D.3.2 [Programming Languages]: Language Classifications ---Concurrent, distributed, and parallel languages; D.3.3 [Programming Languages]: Language Constructs and Features---Concurrent programming structures General Terms: Languages Additional Key Words and Phrases: Compositionality, Parallel Languages, Parallel Programming ACM Transactions on Programming Languages and Systems, Vol. 8, No. 1, January 1999. Compositional Parallel Programming Languages \Delta 113 1. INTRODUCTION Parallel programming is widely regarded as difficult: more difficult than sequential programming, and perhaps (at least this is our view) more difficult than it needs to be. In addition to the normal programming concerns, the para...

this paper we report on a project at Argonne National Laboratory to parallelize the Penn State/NCAR Mesoscale Model version 5 using a fine grain decomposition dynamically mapped and managed under PCN.

Montelius, J., 1997. Exploiting Fine-grain Parallelism in Concurrent Constraint Languages, 220 pp. Uppsala Thesis in Computing Science 28, ISSN 0283-359X, ISBN 91-506-1215-8. SICS Dissertation Series 25, ISSN 1101-1335, ISRN SICS/D-- 25--SE T his dissertation presents the design, implementation, and evaluation of a system that exploits fine-grain implicit parallelism in concurrent constraint programming language. The system is able to outperform a C implementation of an algorithm with complex dependencies without any user annotations. The concurrent constraint programming language AKL is used as a source programming language. A program is divided during runtime into tasks that are distributed over available processors. The system is unique in that it handles both and-parallel execution of goals as well as or-parallel execution of encapsulated search. A parallel binding scheme for a hierarchical constraint store is presented. The binding scheme allows encapsulated search to be performe...

Portability, efficiency, and ease of coding are all important considerations in choosing the programming model for a scalable parallel application. The message-passing programming model is widely used because of its portability, yet some applications are too complex to code in it while also trying to maintain a balanced computation load and avoid redundant computations. The shared-memory programming model simplifies coding, but it is not portable and often provides little control over interprocessor data transfer costs.This paper describes a new approach, called Global Arrays (GA), that combines the better features of both other models, leading to both simple coding and efficient execution. The key concept of GA is that it provides a portable interface through which each process in a MIMD parallel program can asynchronously access logical blocks of physically distributed matrices, with no need for explicit cooperation by other processes. We have implemented GA libraries on a variety of...