Proceedings Article10.1145/944645.944693
A multiobjective optimization model for exploring multiprocessor mappings of process networks
Cagkan Erbas,Selin C. Erbas,Andy D. Pimentel +2 more
- 01 Oct 2003
- pp 182-187
TL;DR: A optimization software tool, implementing an evolutionary algorithm from the literature, has been developed to achieve a set of best alternative mapping decisions under multiple criteria, some of which were further evaluated by the Sesame simulation framework.
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Abstract: In the Sesame framework, we develop a modeling and simulation environment for the efficient design space exploration of heterogeneous embedded systems. Since Sesame recognizes separate application and architecture models within a single system simulation, it needs an explicit mapping step to relate these models for co-simulation. So far in Sesame, the mapping decision has been assumed to be made by an experienced designer, intuitively. However, this assumption is increasingly becoming inappropriate for the following reasons: already the realistic systems are far too complex for making intuitive decisions at an early design stage where the design space is very large. Likely, these systems will even get more complex in the near future. Besides, there exist multiple criteria to consider, like processing times, power consumption and cost of the architecture, which make the decision problem even harder.In this paper, the mapping decision problem is formulated as a multiobjective combinatorial optimization problem. For a solution approach, an optimization software tool, implementing an evolutionary algorithm from the literature, has been developed to achieve a set of best alternative mapping decisions under multiple criteria. In a case study, we have used our optimization tool to obtain a set of mapping decisions, some of which were further evaluated by the Sesame simulation framework.
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Citations
A systematic approach to exploring embedded system architectures at multiple abstraction levels
TL;DR: The Sesame framework as mentioned in this paper provides high-level modeling and simulation methods and tools for system-level performance evaluation and exploration of heterogeneous embedded systems, and it takes a designer systematically along the path from selecting candidate architectures, using analytical modeling and multi-objective optimization, to simulating these candidate architectures with our system level simulation environment.
Quo Vadis, SLD? Reasoning About the Trends and Challenges of System Level Design Recognizing common requirements for co-design of hardware and software in diverse systems may lead to productivity gains, lower costs and first-pass design success.
Alberto Sangiovanni-Vincentelli
- 01 Jan 2007
TL;DR: In this paper, the authors present the challenges faced by industry in system level design and propose a design methodology, platform-based design (PBD), that has the potential of addres- sing these challenges in a unified way.
343
Quo Vadis, SLD? Reasoning About the Trends and Challenges of System Level Design
Alberto Sangiovanni-Vincentelli
- 30 Apr 2007
TL;DR: A design methodology, platform-based design (PBD), is proposed that has the potential of addressing system level design challenges in a unified way and a tool environment is presented, Metropolis, that supports PBD and can be used to integrate available tools and methods.
300
Multiobjective optimization and evolutionary algorithms for the application mapping problem in multiprocessor system-on-chip design
TL;DR: This paper aims at investigating the performance of multiobjective evolutionary algorithms (MOEAs) on solving large instances of the mapping problem and shows that MOEAs provide the designer with a highly accurate set of solutions in a reasonable amount of time.
A framework for system-level modeling and simulation of embedded systems architectures
TL;DR: An overview of the system-level modeling and simulation environment, Sesame, which aims at efficient design space exploration of embedded multimedia system architectures, discusses many important key concepts in early systems evaluation, such as Y-chart-based systems modeling, design space pruning and exploration, trace-driven cosimulation, and model calibration.
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