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Dynamic Programming is an important problem-solving technique used for solving a wide variety of optimization problems. Dynamic Programming programs are commonly designed as individual applications and software tools are usually tailored to specific classes of recurrences and methodologies. That contrasts with some other algorithmic techniques where a single generic program may solve all the instances. We have developed a general skeleton tool providing support for a wide range of dynamic programming methodologies on different parallel architectures. Genericity, flexibility and efficiency are basic issues of the design strategy. Parallelism is supplied to the user in a transparent manner through a common sequential interface. A set of test problems representative of different classes of Dynamic Programming formulations has been used to validate our skeleton on an IBM-SP.

Dynamic Programming is an important problem-solving technique used for solving a wide variety of optimizations problems. Dynamic programs are commonly designed as individual applications and, software tools are usually tailored for specific classes of recurrences and methodologies. We presented in [9] a methodological proposal that allowed us to develop a generic tool [DPSKEL] that supports a wide range of Dynamic Programming formalizations for different parallel paradigms. In this paper we extent this work by including a new layer between the end users and the tool in order to reduce the development complexity. This new layer consists in a XML specification language to describe Dynamic Programming problems in an easy manner.

SUMMARYThe arrival of multicore systems, along with the speed‐up potential available in graphics processing units, has given us unprecedented low‐cost computing power. These systems address some of the known architecture problems but at the expense of considerably increased programming complexity. Heterogeneity, at both the architectural and programming levels, poses a great challenge to programmers. Many proposals have been put forth to facilitate the job of programmers. Leaving aside proposals based on the development of new programming languages because of the effort this represents for the user (effort to learn and reuse code), the remaining proposals are based on transforming sequential code into parallel code, or on transforming parallel code designed for one architecture into parallel code designed for another. A different approach relies on the use of skeletons. The programmer has available set of parallel standards that comprise the basis for developing parallel code while programming sequential code. In this context, we propose a methodology for developing an automatic source‐to‐source transformation in a specific domain. This methodology is instantiated in a framework aimed at solving dynamic programming problems. Using this framework, the final user (a physician, mathematician, biologist, etc.) can express her problem using an equation in Latex, and the system will automatically generate the optimal parallel code for homogeneous or heterogeneous architectures. This approach allows for great portability toward these new emerging architectures and for great productivity, as evidenced by the computational results.Copyright © 2012 John Wiley & Sons, Ltd.

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