Improving Automatic Design Space Exploration by Integrating Symbolic Techniques into Multi-Objective Evolutionary Algorithms

2006 ◽  
Vol 2 (3) ◽  
Author(s):  
Christian Haubelt ◽  
Thomas Schlichte ◽  
Jürgen Teich
Keyword(s):  
Evolutionary Algorithms ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Automatic Design ◽  
Multi Objective

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.

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

Design-Space Exploration with Multi-Objective Resource-Aware Modulo Scheduling

2019 ◽  
pp. 170-183 ◽  
Author(s):  
Julian Oppermann ◽  
Patrick Sittel ◽  
Martin Kumm ◽  
Melanie Reuter-Oppermann ◽  
Andreas Koch ◽  
...  
Keyword(s):  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Modulo Scheduling ◽  
Multi Objective ◽  
Resource Aware

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.

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