Evaluation of design space exploration strategies

Moya, Francisco; Moya, José Manuel Huidobro; López, Juan Carlos

doi:10.1109/eurmic.1999.794512

Cited by 9 publications

(5 citation statements)

References 10 publications

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“…Therefore a recursive modification of the V-Model ( Figure 1) design process is necessary: the top level requirements stay constant but a loop between system, module and component design is needed to find all potential solutions. Along with a proper search algorithm the entire solution space could be analyzed [7][8][9]. Our conclusion is an automated process ( Figure 2) for DSE which consists of three main components: A key element in this automated loop is block number two.…”

Section: The Need For Design Space Explorationmentioning

confidence: 99%

Energy management strategy to be used in design space exploration for electric powertrain optimization

Vaillant

Eckert

Gauterin

2014

2014 Ninth International Conference on Ecological Vehicles and Renewable Energies (EVER)

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Electric vehicle (EV) design offers additional degrees of freedom in powertrain layout. A tremendous number of topologies have to be compared to find the best one for a given set of requirements. An integrated approach is needed to increase powertrain efficiency not only on component level. In this paper a design space exploration (DSE) method is presented to study interdependencies of all involved components. The research is done for topologies with multiple motors (AWD) combined with multiple-speed gearboxes. The objective is a holistic topology optimization to increase driving range. The DSE's key element which defines the energy management strategy (EMS) and computes consumption is discussed in detail. Dynamic programming (DP) is used to determine the most energy efficient operation strategy for the respective topology. Different methods for EMS definition are compared in terms of predicted load collectives, energy efficiency and computing time. Measures to reduce the prediction error for a fast backwards simulation are presented.

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Section: The Need For Design Space Explorationmentioning

confidence: 99%

Energy management strategy to be used in design space exploration for electric powertrain optimization

Vaillant

Eckert

Gauterin

2014

2014 Ninth International Conference on Ecological Vehicles and Renewable Energies (EVER)

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“…We are not aware of any related work using Tabu search in the context of electronics design. Moya et al [84] compare Tabu search with simulated annealing for an artificial, two dimensional optimization scenario. Tabu search appears to be more robust against discontinuities and errors in the cost function and more effectively covers "bumpy" terrain than simulated annealing.…”

Section: Strategies For Covering the Design Spacementioning

confidence: 99%

Methods for evaluating and covering the design space during early design development

Gries

2004

Integration, the VLSI Journal

115

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This paper gives an overview of methods used for Design Space Exploration (DSE) at the system-and micro-architecture levels. The DSE problem is considered to be two orthogonal issues: (I) How could a single design point be evaluated, (II) how could the design space be covered during the exploration process? The latter question arises since an exhaustive exploration of the design space by evaluating every possible design point is usually prohibitive due to the sheer size of the design space. We therefore reveal trade-offs linked to the choice of appropriate evaluation and coverage methods. The designer has to balance the following issues: the accuracy of the evaluation, the time it takes to evaluate one design point (including the implementation of the evaluation model), the precision/granularity of the design space coverage, and last but not least the possibilities for automating the exploration process. We also list common representations of the design space and compare current system and micro-architecture level design frameworks. This review thus eases the choice of a decent exploration policy by providing a comprehensive survey and classification of recent related work. It is focused on System-on-a-Chip designs, particularly those used for network processors. These systems are heterogeneous in nature using multiple computation, communication, memory, and peripheral resources.Keywords: Design space exploration, design space pruning, system-level design, micro-architecture design, design frameworks, benchmarking, multi-objective search. NoteWe focus on related work which applies methods in the context of design space exploration. Discussing the theory of optimization methods and the fundamentals of design evaluation is beyond the scope of this survey.

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“…Design space exploration research can be classified as addressing aspects of representation, estimation, and exploration algorithms [11]. Our proposed technique supports estimation by providing a rapid performance evaluation of component-based architectures suitable for use in an existing framework that generates candidate architectures.…”

Section: Related Workmentioning

confidence: 99%

Architecture-level performance evaluation of component-based embedded systems

Russell

Jacome

2003

Proceedings of the 40th Annual Design Automation Conference

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A static performance evaluation technique is proposed to support early, architecture-level design space exploration for component-based embedded systems. The novel contribution is the use of a designer-specified evaluation scenario to identify a characteristic subset of system functionality that serves as a context for a rapid performance evaluation between candidate architectures. Fidelity is demonstrated with a case study that compares performance estimates of several candidate architectures to measurements from respective implementations.

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Evaluation of design space exploration strategies

Cited by 9 publications

References 10 publications

Energy management strategy to be used in design space exploration for electric powertrain optimization

Energy management strategy to be used in design space exploration for electric powertrain optimization

Methods for evaluating and covering the design space during early design development

Architecture-level performance evaluation of component-based embedded systems

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