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Skeleton parallel programming encourages programmers to build a parallel program from ready-made components for which efficient implementations are known to exist, making both the parallel program development and the parallelization process easier. However, programmers often suffer from the difficulty to chooseaproper combination of parallel primitives so as to construct efficient parallel programs. To overcome this difficulty, we propose a new powerful parallel skeleton diff derived from the diffusion theorem, showing how it can be used to naturally code efficient solutions to problems, and how it can be efficiently implementedin parallel using MPI (Message Passing Interface). Keywords: Parallel Skeleton, Bird--Meertens Formalism, Program Transformation, MPI. 1 Introduction Parallel programming has proved to be a difficult task, requiring expert knowledge of both parallel algorithms and hardware architectures to achieve good results. The use of parallel skeletons can help to struc...

this paper, we propose a powerful and general parallel skeleton called accumulate and describe its efficientimplementation in C++ with MPI (Message Passing Interface) (18) as a solution to the above problems. Unlike the approaches that apply such optimizations as loop restructuring to the target program, our approach provides a general recursive computation with accumulation as a library function (skeleton) with an optimized implementation. We are based on the data parallel programming model of BMF, which provides us with a concise way to describe and manipulate parallel programs. The main advantages of accumulate can be summarized as follows

This paper introduces accumulation into list homomorphisms for systematic development of both efficient and correct parallel programs. New parallelizable recursive pattern called is given, and transformations from sequential patterns in the form into (H-)homomorphism are shown. We illustrate the power of our formalization by developing a novel and general parallel program for a class of interesting and challenging problems, known as maximum marking problems. 1.

Skeleton programming enables programmers to build parallel programs easier by providing efficient ready-made parallel algorithms. The diffusion skeleton was proposed (associated with a method for program derivation) to abstract a good combination of primitive skeletons, such as map, parallel reduction and parallel prefix sum (scan).

Trees are useful data structures, but to design e#cient parallel programs over trees is known to be more di#cult than to do over lists. Although several important tree skeletons have been proposed to simplify parallel programming on trees, few studies have been reported on how to systematically use them in solving practical problems; it is neither clear how to make a good combination of skeletons to solve a given problem, nor obvious how to find suitable operators used in a single skeleton. In this paper, we report our first attempt to resolve these problems, proposing two important transformations, the tree di#usion transformation and the tree context preservation transformation. The tree di#usion transformation allows one to use familiar recursive definitions to develop his parallel programs, while the tree context preservation transformation shows how to derive associative operators that are required when using tree skeletons. We illustrate our approach by deriving an e#cient parallel program for solving a nontrivial problem called the party planning problem, the tree version of the famous maximum-weight-sum problem.