Hardware/software co-design (HSCD) aims at automating the design of complex embedded systems with functionality in both hardware and software. The central task of HSCD is hardware/software partitioning, i.e., deciding which components of the system to implement in hardware and which ones in software. During partitioning, the conflicting requirements on performance, costs, energy consumption, etc., have to be taken into account. This book addresses the hardware/software partitioning problem from an algorithmic point of view. It proposes a novel formal framework for the definition of different variants of the problem. Most variants are shown to be NP-hard, but there are also important cases that can be solved optimally in polynomial time. Furthermore, the book describes three new heuristics for the NP-hard versions of the problem: a genetic algorithm, an adaptation of the Kernighan-Lin heuristic, and a completely new algorithm based on the combinatorial properties of the hardware/software partitioning problem. It is demonstrated with empirical results how the three algorithms can cope with industrial benchmarks as well as large random problem instances.
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Hardware/software co-design (HSCD) aims at automating the design of complex embedded systems with functionality in both hardware and software. The central task of HSCD is hardware/software partitioning, i.e., deciding which components of the system to implement in hardware and which ones in software. During partitioning, the conflicting requirements on performance, costs, energy consumption, etc., have to be taken into account. This book addresses the hardware/software partitioning problem from an algorithmic point of view. It proposes a novel formal framework for the definition of different variants of the problem. Most variants are shown to be NP-hard, but there are also important cases that can be solved optimally in polynomial time. Furthermore, the book describes three new heuristics for the NP-hard versions of the problem: a genetic algorithm, an adaptation of the Kernighan-Lin heuristic, and a completely new algorithm based on the combinatorial properties of the hardware/software partitioning problem. It is demonstrated with empirical results how the three algorithms can cope with industrial benchmarks as well as large random problem instances.
Zoltán Ádám Mann obtained a PhD in Computer Science from Budapest University of Technology and Economics (Hungary). Now he is Associate Professor at the Department of Computer Science and Information Theory at Budapest University of Technology and Economics. He is also Principal Consultant at Capgemini.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Hardware/software co-design (HSCD) aims at automating the design of complex embedded systems with functionality in both hardware and software. The central task of HSCD is hardware/software partitioning, i.e., deciding which components of the system to implement in hardware and which ones in software. During partitioning, the conflicting requirements on performance, costs, energy consumption, etc., have to be taken into account. This book addresses the hardware/software partitioning problem from an algorithmic point of view. It proposes a novel formal framework for the definition of different variants of the problem. Most variants are shown to be NP-hard, but there are also important cases that can be solved optimally in polynomial time. Furthermore, the book describes three new heuristics for the NP-hard versions of the problem: a genetic algorithm, an adaptation of the Kernighan-Lin heuristic, and a completely new algorithm based on the combinatorial properties of the hardware/software partitioning problem. It is demonstrated with empirical results how the three algorithms can cope with industrial benchmarks as well as large random problem instances. 120 pp. Englisch. Nº de ref. del artículo: 9783845405933
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Hardware/software co-design (HSCD) aims at automating the design of complex embedded systems with functionality in both hardware and software. The central task of HSCD is hardware/software partitioning, i.e., deciding which components of the system to implement in hardware and which ones in software. During partitioning, the conflicting requirements on performance, costs, energy consumption, etc., have to be taken into account. This book addresses the hardware/software partitioning problem from an algorithmic point of view. It proposes a novel formal framework for the definition of different variants of the problem. Most variants are shown to be NP-hard, but there are also important cases that can be solved optimally in polynomial time. Furthermore, the book describes three new heuristics for the NP-hard versions of the problem: a genetic algorithm, an adaptation of the Kernighan-Lin heuristic, and a completely new algorithm based on the combinatorial properties of the hardware/software partitioning problem. It is demonstrated with empirical results how the three algorithms can cope with industrial benchmarks as well as large random problem instances. Nº de ref. del artículo: 9783845405933
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Taschenbuch. Condición: Neu. Neuware -Hardware/software co-design (HSCD) aims at automating the design of complex embedded systems with functionality in both hardware and software. The central task of HSCD is hardware/software partitioning, i.e., deciding which components of the system to implement in hardware and which ones in software. During partitioning, the conflicting requirements on performance, costs, energy consumption, etc., have to be taken into account. This book addresses the hardware/software partitioning problem from an algorithmic point of view. It proposes a novel formal framework for the definition of different variants of the problem. Most variants are shown to be NP-hard, but there are also important cases that can be solved optimally in polynomial time. Furthermore, the book describes three new heuristics for the NP-hard versions of the problem: a genetic algorithm, an adaptation of the Kernighan-Lin heuristic, and a completely new algorithm based on the combinatorial properties of the hardware/software partitioning problem. It is demonstrated with empirical results how the three algorithms can cope with industrial benchmarks as well as large random problem instances.Books on Demand GmbH, Überseering 33, 22297 Hamburg 120 pp. Englisch. Nº de ref. del artículo: 9783845405933
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