scholarly journals Performance Driven Design Space Exploration for Multi-Objective Optimization Using Stability in Competition

Author(s):  
Summit Sehgal

Multi Parametric Design Space Exploration (DSE) for optimal micro-architecture synthesis is an extremely complex yet crucial stage in embedded systems development. Often it is very time complex to find the best suitable configuration to map the inherently contradictory performance parameters into systems silicon real estate. Owing to its exponentially exploding design space and multi way combinatorial mapping, DSE has proven to be notoriously hard and intractable for VLSI CAD tools. The presented work introduces a highly scalable and generalized analytical approach to identify the best configuration of systems architecture while maintaining prime accuracy resolution. This DSE approach coupled with

2021 ◽  
Author(s):  
Summit Sehgal

Multi Parametric Design Space Exploration (DSE) for optimal micro-architecture synthesis is an extremely complex yet crucial stage in embedded systems development. Often it is very time complex to find the best suitable configuration to map the inherently contradictory performance parameters into systems silicon real estate. Owing to its exponentially exploding design space and multi way combinatorial mapping, DSE has proven to be notoriously hard and intractable for VLSI CAD tools. The presented work introduces a highly scalable and generalized analytical approach to identify the best configuration of systems architecture while maintaining prime accuracy resolution. This DSE approach coupled with


2021 ◽  
Author(s):  
Summit Sehgal

Multi Parametric Design Space Exploration (DSE) for optimal micro-architecture synthesis is an extremely complex yet crucial stage in embedded systems development. Often it is very time complex to find the best suitable configuration to map the inherently contradictory performance parameters into systems silicon real estate. Owing to its exponentially exploding design space and multi way combinatorial mapping, DSE has proven to be notoriously hard and intractable for VLSI CAD tools. The presented work introduces a highly scalable and generalized analytical approach to identify the best configuration of systems architecture while maintaining prime accuracy resolution. This PSE approach coupled with Stability in Competition principles has been applied to a number of well known benchmark High Level Synthesis (HLS) applications, with an impressive 71.80% aggregate speedup and results being more pronounced for larger design space HLS applications.


2021 ◽  
Author(s):  
Summit Sehgal

Multi Parametric Design Space Exploration (DSE) for optimal micro-architecture synthesis is an extremely complex yet crucial stage in embedded systems development. Often it is very time complex to find the best suitable configuration to map the inherently contradictory performance parameters into systems silicon real estate. Owing to its exponentially exploding design space and multi way combinatorial mapping, DSE has proven to be notoriously hard and intractable for VLSI CAD tools. The presented work introduces a highly scalable and generalized analytical approach to identify the best configuration of systems architecture while maintaining prime accuracy resolution. This PSE approach coupled with Stability in Competition principles has been applied to a number of well known benchmark High Level Synthesis (HLS) applications, with an impressive 71.80% aggregate speedup and results being more pronounced for larger design space HLS applications.


Author(s):  
Julia Reisinger ◽  
Maximilian Knoll ◽  
Iva Kovacic

AbstractIndustrial buildings play a major role in sustainable development, producing and expending a significant amount of resources, energy and waste. Due to product individualization and accelerating technological advances in manufacturing, industrial buildings strive for highly flexible building structures to accommodate constantly evolving production processes. However, common sustainability assessment tools do not respect flexibility metrics and manufacturing and building design processes run sequentially, neglecting discipline-specific interaction, leading to inflexible solutions. In integrated industrial building design (IIBD), incorporating manufacturing and building disciplines simultaneously, design teams are faced with the choice of multiple conflicting criteria and complex design decisions, opening up a huge design space. To address these issues, this paper presents a parametric design process for efficient design space exploration in IIBD. A state-of-the-art survey and multiple case study are conducted to define four novel flexibility metrics and to develop a unified design space, respecting both building and manufacturing requirements. Based on these results, a parametric design process for automated structural optimization and quantitative flexibility assessment is developed, guiding the decision-making process towards increased sustainability. The proposed framework is tested on a pilot-project of a food and hygiene production, evaluating the design space representation and validating the flexibility metrics. Results confirmed the efficiency of the process that an evolutionary multi-objective optimization algorithm can be implemented in future research to enable multidisciplinary design optimization for flexible industrial building solutions.


2017 ◽  
Vol 62 ◽  
pp. 373-383 ◽  
Author(s):  
Andrea Patanè ◽  
Andrea Santoro ◽  
Piero Conca ◽  
Giovanni Carapezza ◽  
Antonino La Magna ◽  
...  

2021 ◽  
Author(s):  
Aakriti Tarun Sharma

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.


Author(s):  
Eduardo Castro e Costa ◽  
Joaquim Jorge ◽  
Aaron D. Knochel ◽  
José Pinto Duarte

AbstractIn mass customization, software configurators enable novice end-users to design customized products and services according to their needs and preferences. However, traditional configurators hardly provide an engaging experience while avoiding the burden of choice. We propose a Design Participation Model to facilitate navigating the design space, based on two modules. Modeler enables designers to create customizable designs as parametric models, and Navigator subsequently permits novice end-users to explore these designs. While most parametric designs support direct manipulation of low-level features, we propose interpolation features to give customers more flexibility. In this paper, we focus on the implementation of such interpolation features into Navigator and its user interface. To assess our approach, we designed and performed user experiments to test and compare Modeler and Navigator, thus providing insights for further developments of our approach. Our results suggest that barycentric interpolation between qualitative parameters provides a more easily understandable interface that empowers novice customers to explore the design space expeditiously.


2020 ◽  
Vol 10 (3) ◽  
pp. 22
Author(s):  
Andy D. Pimentel

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.


2021 ◽  
Author(s):  
Aakriti Tarun Sharma

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.


Author(s):  
Fakhre Ali ◽  
Konstantinos Tzanidakis ◽  
Ioannis Goulos ◽  
Vassilios Pachidis ◽  
Roberto d'Ippolito

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.


Sign in / Sign up

Export Citation Format

Share Document