A Comparison of Multi-objective Algorithms for the Automatic Design Space Exploration of a Superscalar System

Calborean, Horia; Jahr, Ralf; Ungerer, Theo; Vintan, Lucian

doi:10.1007/978-3-642-32548-9_35

Cited by 12 publications

(12 citation statements)

References 16 publications

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“…SPEA-2 seems to provide better solutions in terms of convergence and diversity but at the expense of computational time [106]. However, a clear ultimate winner between NSGA-II and SPEA2 cannot be determined [107], so both methods can be considered equivalent.…”

Section: Multi Objectivementioning

confidence: 99%

Optimizing Exoskeleton Design with Evolutionary Computation: An Intensive Survey

Stroppa,

Soylemez,

Yuksel

et al. 2023

Robotics

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Exoskeleton devices are designed for applications such as rehabilitation, assistance, and haptics. Due to the nature of physical human–machine interaction, designing and operating these devices is quite challenging. Optimization methods lessen the severity of these challenges and help designers develop the device they need. In this paper, we present an extensive and systematic literature search on the optimization methods used for the mechanical design of exoskeletons. We completed the search in the IEEE, ACM, and MDPI databases between 2017 and 2023 using the keywords “exoskeleton”, “design”, and “optimization”. We categorized our findings in terms of which limb (i.e., hand, wrist, arm, or leg) and application (assistive, rehabilitation, or haptic) the exoskeleton was designed for, the optimization metrics (force transmission, workspace, size, and adjustability/calibration), and the optimization method (categorized as evolutionary computation or non-evolutionary computation methods). We discuss our observations with respect to how the optimization methods have been implemented based on our findings. We conclude our paper with suggestions for future research.

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Section: Multi Objectivementioning

confidence: 99%

Optimizing Exoskeleton Design with Evolutionary Computation: An Intensive Survey

Stroppa,

Soylemez,

Yuksel

et al. 2023

Robotics

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“…Since the optimisation problem addresses multiple objectives such as performance and area, there is usually no single solution, but a Pareto-set of non-dominated solutions. An introduction to DSE techniques and a comparison of optimisation algorithms can be found in [20,21]. In this framework, the strength of the countermeasures against SCA, together with the choice of a specific cryptographic algorithm, can be counted as a parameter exposed by the platform.…”

Section: Sca Countermeasuresmentioning

confidence: 99%

“…Since the optimisation problem addresses multiple objectives such as performance and area, there is usually no single solution, but a Pareto‐set of non‐dominated solutions. An introduction to DSE techniques and a comparison of optimisation algorithms can be found in [20, 21].…”

Section: Extending the Design Space With The Security Dimensionmentioning

confidence: 99%

Design space extension for secure implementation of block ciphers

Agosta

Barenghi

Maggi

et al. 2014

IET Computers & Digital Techniques

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Security has been identified as a critical dimension in the design of embedded systems for almost a decade. A wellrecognised critical threat against the security of embedded systems is represented by 'side-channel attacks (SCAs)', which mandate the application of specially tailored countermeasures. These countermeasures are significantly demanding in terms of computation effort, and have traditionally been applied by hand. The recent introduction of a methodology to gauge the security margins provided by software cipher implementations, allows the integration of the automated application of countermeasures into platform-based system-level design methodologies. The authors introduce in the design space of block cipher implementations a new metric concerning the resistance against SCAs, provide a systematic method for the selection of the most appropriate cipher given the security and performance trade-offs, and point out the performance requirements for the random number generator. Moreover, they discuss the implications of the design space extension on system runtime adaptivity. The experimental evaluation demonstrates that a single cipher does not cover optimally a range of convenient operating points and that ciphers like a Serpent, which are considered slow in non-protected implementations, can outperform primitives like the Advanced Encryption Standard when implementations with equal security guarantees against SCAs are considered.

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“…Empirical studies in recent years have shown that the PSO algorithms achieved high convergence speed for the multiobjective optimization problems [33]. Apart from this, it has been performed to apply to the automatic space exploration on the superscalar computer systems successfully [34,35]. More notably, it is suggested that PSO has been exercised to greatly improve the implicit SML algorithm through convergence speed and accuracy in consideration of the financial model calibration problems.…”

Section: Introductionmentioning

confidence: 99%

Using Particle Swarm Optimization Algorithm to Calibrate the Term Structure Model

Zhou

Liu

Tian

et al. 2021

Mathematical Problems in Engineering

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One of the advantages of stochastic differential equations (SDE) is that they can follow a variety of different trends so that they can establish complex dynamic systems in the economic and financial fields. Although some estimation methods have been proposed to identify the unknown parameters in virtue of the results in the SDE model to speed up the process, these solutions only focus on using explicit approach to solve SDEs, and therefore they are not reliable to deal with data source merged being large and varied. Thus, this study makes progress in creating a new implicit way to fill in the gaps of accurately calibrating the unknown parameters in the SDE model. Essentially, the primary goal of the article is to generate rigid SDE simulation. Meanwhile, the particle swarm optimization method serves a purpose to search and simultaneously obtain the optimal estimation of the model unknown parameters in the complicated experiment of parameter space in an effective way. Finally, in an interest rate term structure model, it is verified that the method effectively deals with parameter estimation in the SDE model.

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A Comparison of Multi-objective Algorithms for the Automatic Design Space Exploration of a Superscalar System

Cited by 12 publications

References 16 publications

Optimizing Exoskeleton Design with Evolutionary Computation: An Intensive Survey

Optimizing Exoskeleton Design with Evolutionary Computation: An Intensive Survey

Design space extension for secure implementation of block ciphers

Using Particle Swarm Optimization Algorithm to Calibrate the Term Structure Model

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