Multi-objective optimization applied to unified second level cache memory hierarchy tuning aiming at energy and performance optimization

2016 ◽  
Vol 49 ◽  
pp. 603-610 ◽  
Author(s):  
Filipe Rolim Cordeiro ◽  
Abel Guilhermino da Silva-Filho
Keyword(s):  
Performance Optimization ◽  
Memory Hierarchy ◽  
Cache Memory ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
And Performance

scholarly journals A rapid design space exploration approach for multi-objective optimization of DSP filter designs

2021 ◽  
Author(s):  
Aakriti Tarun Sharma
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Systems Design ◽  
Design Solution ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Time Period ◽  
And Performance ◽  
High Level

The process of converting a behavioral specification of an application to its equivalent system architecture is referred to as High Level-Synthesis (HLS). A crucial stage in embedded systems design involves finding the trade off between resource utilization and performance. An exhaustive search would yield the required results, but would take a huge amount of time to arrive at the solution even for smaller designs. This would result in a high time complexity. We employ the use of Design Space Exploration (DSE) in order to reduce the complexity of the design space and to reach the desired results in less time. In reality, there are multiple constraints defined by the user that need to be satisfied simultaneously. Thus, the nature of the task at hand is referred to as Multi-Objective Optimization. In this thesis, the design process of DSP benchmarks was analyzed based on user defined constraints such as power and execution time. The analyzed outcome was compared with the existing approaches in DSE and an optimal design solution was derived in a shorter time period.

Multi-objective optimization design for the blade angles of hydraulic torque converter with adjustable pump

2020 ◽  
Vol 234 (13) ◽  
pp. 2523-2536
Author(s):  
Zhi-Ying Zheng ◽  
Quan-Zhong Liu ◽  
Yong-Kang Deng ◽  
Biao Li
Keyword(s):  
Performance Optimization ◽  
Optimization Design ◽  
High Efficiency ◽  
Influencing Factor ◽  
Torque Converter ◽  
Multi Objective Optimization ◽  
Trailing Edge ◽  
Multi Objective ◽  
Second Stage ◽  
Hydraulic Torque Converter

To improve the efficiency of a hydraulic torque converter with adjustable pump at low load and thus increase the operation scope of high efficiency, multi-objective optimization design is carried out for the blade angles by incorporating three-dimensional steady computational fluid dynamics numerical simulation, design of experiments, Kriging surrogate model and multi-objective genetic algorithm. The results show that the angle of blade trailing edge in first-stage stator is the main influencing factor of the efficiency of hydraulic torque converter with adjustable pump. All the peak efficiencies of hydraulic torque converter with adjustable pump at three openings of the pump are improved after optimization, and the increased extent increases with decreasing opening of the pump. The operation scope of high efficiency consequently increases from 2.46 to 2.67. Besides, the improvement for the efficiency of hydraulic torque converter with adjustable pump is achieved by increasing the efficiency of the pump. The increase of angle of blade trailing edge in first-stage stator and the decrease of angle of blade leading edge in second-stage turbine after optimization induce the positive angle of attack at the inlet of second-stage turbine, thus realizing the performance optimization of hydraulic torque converter with adjustable pump. This also explains the increased proportion of the torque of second-stage turbine at larger speed ratios after optimization and the fact that the angle of blade trailing edge in first-stage stator is the main influencing factor of the efficiency of hydraulic torque converter with adjustable pump. The established multi-objective optimization method provides a reference solution for the optimization design of blade angles and for the improvement of integrated efficiency of hydraulic torque converter.

Cognitive Radio Decision Engine Based on Multi-Objective Genetic Algorithm

2011 ◽  
Vol 48-49 ◽  
pp. 314-317
Author(s):  
Di Wu ◽  
Sheng Yao Yang ◽  
J.C. Liu
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Performance Optimization ◽  
Optimization Problem ◽  
Simulation Analysis ◽  
Multi Objective Optimization ◽  
Weighting Method ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Decision Engine

The performance optimization of cognitive radio is a multi-objective optimization problem. Existing genetic algorithms are difficult to assign the weight of each objective when the linear weighting method is used to simplify the multi-objective optimization problem into a single objective optimization problem. In this paper, we propose a new cognitive decision engine algorithm using multi-objective genetic algorithm with population adaptation. A multicarrier system is used for simulation analysis, and experimental results show that the proposed algorithm is effective and meets the real-time requirement.

scholarly journals A rapid design space exploration approach for multi-objective optimization of DSP filter designs

2021 ◽  
Author(s):  
Aakriti Tarun Sharma
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Systems Design ◽  
Design Solution ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Time Period ◽  
And Performance ◽  
High Level

The process of converting a behavioral specification of an application to its equivalent system architecture is referred to as High Level-Synthesis (HLS). A crucial stage in embedded systems design involves finding the trade off between resource utilization and performance. An exhaustive search would yield the required results, but would take a huge amount of time to arrive at the solution even for smaller designs. This would result in a high time complexity. We employ the use of Design Space Exploration (DSE) in order to reduce the complexity of the design space and to reach the desired results in less time. In reality, there are multiple constraints defined by the user that need to be satisfied simultaneously. Thus, the nature of the task at hand is referred to as Multi-Objective Optimization. In this thesis, the design process of DSP benchmarks was analyzed based on user defined constraints such as power and execution time. The analyzed outcome was compared with the existing approaches in DSE and an optimal design solution was derived in a shorter time period.

Patch size setup and performance/cost trade-offs in multi-objective EM-driven antenna optimization using sequential domain patching

2017 ◽  
Vol 34 (4) ◽  
pp. 1070-1081
Author(s):  
Slawomir Koziel ◽  
Adrian Bekasiewicz
Keyword(s):  
Control Parameter ◽  
Computational Cost ◽  
Design Procedure ◽  
Simulation Models ◽  
Multi Objective Optimization ◽  
Computationally Efficient ◽  
Content Type ◽  
Multi Objective ◽  
Trade Offs ◽  
And Performance

Purpose This paper aims to assess control parameter setup and its effect on computational cost and performance of deterministic procedures for multi-objective design optimization of expensive simulation models of antenna structures. Design/methodology/approach A deterministic algorithm for cost-efficient multi-objective optimization of antenna structures has been assessed. The algorithm constructs a patch connecting extreme Pareto-optimal designs (obtained by means of separate single-objective optimization runs). Its performance (both cost- and quality-wise) depends on the dimensions of the so-called patch, an elementary region being relocated in the course of the optimization process. The cost/performance trade-offs are studied using two examples of ultra-wideband antenna structures and the optimization results are compared to draw conclusions concerning the algorithm robustness and determine the most advantageous control parameter setups. Findings The obtained results indicate that the investigated algorithm is very robust, i.e. its performance is weakly dependent on the control parameters setup. At the same time, it is found that the most suitable setups are those that ensure low computational cost, specifically non-uniform ones generated on the basis of sensitivity analysis. Research limitations/implications The study provides recommendations for control parameter setup of deterministic multi-objective optimization procedure for computationally efficient design of antenna structures. This is the first study of this kind for this particular design procedure, which confirms its robustness and determines the most suitable arrangement of the control parameters. Consequently, the presented results permit full automation of the surrogate-assisted multi-objective antenna optimization process while ensuring its lowest possible computational cost. Originality/value The work is the first comprehensive validation of the sequential domain patching algorithm under various scenarios of its control parameter setup. The considered design procedure along with the recommended parameter arrangement is a robust and computationally efficient tool for fully automated multi-objective optimization of expensive simulation models of contemporary antenna structures.

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