Shortest Path Method for Hardware/Software Partitioning Problems

Shortest Path Method for Hardware/Software Partitioning Problems

Adil Iguider, Oussama Elissati, Abdeslam En-Nouaary, Mouhcine Chami
Copyright: © 2021 |Pages: 18
DOI: 10.4018/IJISSC.2021070104
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Abstract

Smart systems are becoming more present in every aspect of our daily lives. The main component of such systems is an embedded system; this latter assures the collection, the treatment, and the transmission of the accurate information in the right time and for the right component. Modern embedded systems are facing several challenges; the objective is to design a system with high performance and to decrease the cost and the development time. Consequently, some robust methodologies like the Codesign were developed to fulfill those requirements. The most important step of the Codesign is the partitioning of the systems' functionalities between a hardware set and a software set. This article deals with this problem and uses a heuristic approach based on shortest path optimizations to solve the problem. The aim is to minimize the total hardware area and to respect a constraint on the overall execution time of the system. Experiments results demonstrate that the proposed method is very fast and gives better results compared to the genetic algorithm.
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Background

The problem of Hardware/Software Partitioning (HSP) is influenced by several parameters related to non-functional requirements (NFR). Many approaches were proposed to tackle this problem, and they are categorized into two families, the family of exact algorithms and the family of heuristic algorithms.

Exact algorithms are principally composed of ‘branch and bound’ method (BB), ‘integer linear programming (ILP)’ and ‘dynamic programming’ (DP).Branch and bound is defined in (Jens, 1999), the algorithm relies on binary tree, at each level of the tree, each variable can take the values 0 or 1, the objective is to find the best path from the top to the bottom of the tree which has the optimal cost under the given constraints; an example of its application to hardware software partitioning problem is presented in (Mann et al., 2007). Linear program formulation is composed of a set of variables, a set of inequalities (linear), and an objective function (linear), ILP was used to deal with the hardware software partitioning problem in (Ralf & Peter, 1996). Dynamic programming, by definition, is a method, in which big problems are divided into smaller problems, and then, the solution of the problem is discovered through solving the smaller problems; an example of using dynamic programming in HW/SW partitioning problem is described in (Knudsen & Madsen, 1996).

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