With the increasing popularity of parallel programming environments such as PC clusters, more and more sequential programmers, with little knowledge about parallel architectures and parallel programming, are hoping to write parallel programs. Numerous attempts have been made to develop high-level parallel programming libraries that use abstraction to hide low-level concerns and reduce difficulties in parallel programming. Among them, libraries of parallel skeletons have emerged as a promising way towards this direction. Unfortunately, these libraries are not well accepted by sequential programmers, because of incomplete elimination of lower-level details, ad-hoc selection of library functions, unsatisfactory performance, or lack of convincing application examples. This paper addresses principle of designing skeleton libraries of parallel programming and reports implementation details and practical applications of a skeleton library SkeTo. The SkeTo library is unique in its feature that it has a solid theoretical foundation based on the theory of Constructive Algorithmics, and is practical to be used to describe various parallel computations in a sequential manner. 1.

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High performance architectures are increasingly heterogeneous with shared and distributed memory components. Programming such architectures is complicated and performance portability is a major issue as the architectures evolve. This paper proposes a new architectural cost model that accounts for cache size and improves on heterogeneous architectures, and demonstrates a skeleton-based programming model that simplifies programming heterogeneous architectures. We further demonstrate that the cost model can be exploited by skeletons to improve load balancing on heterogeneous architectures. The heterogeneous skeleton model facilitates performance portability, using the architectural cost model to automatically balance load across heterogeneous components of the architecture. For both a data parallel benchmark, and realistic image processing program we obtain good performance for the heterogeneous skeleton on homogeneous shared and distributed memory architectures, and on three heterogeneous architectures. We also show that taking cache size into account in the model leads to improved balance and performance.

Generative parallel design patterns is a proven technique to improve the productivity of parallel program development. However many of the generative design-pattern systems are developed for target languages that are not widely used by the high performance computing community. This paper describes an initial e#ort to develop a system that will hopefully answer the question in the title in the a#rmative.

We present an overview of eSkel, a library for skeletal parallel programming. eSkel aims to maximise the conceptual flexibility a#orded by its component skeletons and to facilitate dynamic selection of skeleton compositions. We present simple examples which illustrate these properties, and discuss the implementation challenges which the model poses.

Parallel Computing:

We present an application of the eSkel skeletal programming library to the multiple baseline stereo problem. We compare its performance to that of a direct MPI implementation of the same algorithm. 1.