An Evolutionary Multi-Architecture Multi-Objective Optimization Algorithm for Design Space Exploration

2016 ◽  
Author(s):  
Christopher Frank ◽  
Renaud Marlier ◽  
Olivia J. Pinon-Fischer ◽  
Dimitri N. Mavris
Keyword(s):  
Optimization Algorithm ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Multi Objective Optimization ◽  
Multi Objective

Multi-objective optimization and analysis for the design space exploration of analog circuits and solar cells

2017 ◽  
Vol 62 ◽  
pp. 373-383 ◽  
Author(s):  
Andrea Patanè ◽  
Andrea Santoro ◽  
Piero Conca ◽  
Giovanni Carapezza ◽  
Antonino La Magna ◽  
...  
Keyword(s):  
Solar Cells ◽  
Analog Circuits ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Multi Objective Optimization ◽  
Multi Objective

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.

scholarly journals A Case for Security-Aware Design-Space Exploration of Embedded Systems

2020 ◽  
Vol 10 (3) ◽  
pp. 22
Author(s):  
Andy D. Pimentel
Keyword(s):  
Embedded Systems ◽  
Embedded System ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Systems Design ◽  
Design System ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Trade Offs

As modern embedded systems are becoming more and more ubiquitous and interconnected, they attract a world-wide attention of attackers and the security aspect is more important than ever during the design of those systems. Moreover, given the ever-increasing complexity of the applications that run on these systems, it becomes increasingly difficult to meet all security criteria. While extra-functional design objectives such as performance and power/energy consumption are typically taken into account already during the very early stages of embedded systems design, system security is still mostly considered as an afterthought. That is, security is usually not regarded in the process of (early) design-space exploration of embedded systems, which is the critical process of multi-objective optimization that aims at optimizing the extra-functional behavior of a design. This position paper argues for the development of techniques for quantifying the ’degree of secureness’ of embedded system design instances such that these can be incorporated in a multi-objective optimization process. Such technology would allow for the optimization of security aspects of embedded systems during the earliest design phases as well as for studying the trade-offs between security and the other design objectives such as performance, power consumption and cost.

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 of a Regenerative Rotorcraft Powerplant: Trade-off Between Overall Engine Weight and Fuel Economy

2015 ◽  
Vol 137 (12) ◽  
Author(s):  
Fakhre Ali ◽  
Konstantinos Tzanidakis ◽  
Ioannis Goulos ◽  
Vassilios Pachidis ◽  
Roberto d'Ippolito
Keyword(s):  
Fuel Economy ◽  
Pareto Front ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Design Parameters ◽  
Optimization Strategy ◽  
Multi Objective Optimization ◽  
Trade Off ◽  
Multi Objective

A computationally efficient and cost effective simulation framework has been implemented to perform design space exploration and multi-objective optimization for a conceptual regenerative rotorcraft powerplant configuration at mission level. The proposed framework is developed by coupling a comprehensive rotorcraft mission analysis code with a design space exploration and optimization package. The overall approach is deployed to design and optimize the powerplant of a reference twin-engine light rotorcraft, modeled after the Bo105 helicopter, manufactured by Airbus Helicopters. Initially, a sensitivity analysis of the regenerative engine is carried out to quantify the relationship between the engine thermodynamic cycle design parameters, engine weight, and overall mission fuel economy. Second, through the execution of a multi-objective optimization strategy, a Pareto front surface is constructed, quantifying the optimum trade-off between the fuel economy offered by a regenerative engine and its associated weight penalty. The optimum sets of cycle design parameters obtained from the structured Pareto front suggest that the employed heat effectiveness is the key design parameter affecting the engine weight and fuel efficiency. Furthermore, through quantification of the benefits suggested by the acquired Pareto front, it is shown that the fuel economy offered by the simple cycle rotorcraft engine can be substantially improved with the implementation of regeneration technology, without degrading the payload-range capability and airworthiness (one-engine-inoperative) of the rotorcraft.

scholarly journals Towards Multi-objective Optimization of Automatic Design Space Exploration for Computer Architecture through Hyper-heuristic

2019 ◽  
Vol 9 (3) ◽  
pp. 4292-4297
Author(s):  
M. Latif ◽  
M. A. Ismail
Keyword(s):  
Computer Architecture ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Automatic Design ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Heuristic Technique ◽  
Np Hard Problem

Multi-objective optimization is an NP-hard problem. ADSE (automatic design space exploration) using heuristics has been proved to be an appropriate method in resolving this problem. This paper presents a hyper-heuristic technique to solve the DSE issue in computer architecture. Two algorithms are proposed. A hyper-heuristic layer has been added to the FADSE (framework for automatic design space exploration) and relevant algorithms have been implemented. The benefits of already existing multi-objective algorithms have been joined in order to strengthen the proposed algorithms. The proposed algorithms, namely RRSNS (round-robin scheduling NSGA-II and SPEA2) and RSNS (random scheduling NSGA-II and SPEA2) have been evaluated for the ADSE problem. The results have been compared with NSGA-II and SPEA2 algorithms. Results show that the proposed methodologies give competitive outcomes in comparison with NSGA-II and SPEA2.

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