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2008
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Discrete Particle Swarm Optimization for Multi-objective Design Space Exploration

8 years 4 months ago
Discrete Particle Swarm Optimization for Multi-objective Design Space Exploration
Platform-based design represents the most widely used approach to design System-On-Chip (SOC) applications. In this context, the Design Space Exploration (DSE) phase consists of optimally configure a parameterized SOC platform in terms of system-level requirements depending on the target application. In this paper, we introduce the Discrete Particle Swarm Optimization methodology (DPSO) for supporting the DSE of an hardware platform. The proposed technique aims at efficiently profiling the target application and deriving an approximated Pareto set of system configurations with respect to the selected figures of merit. Once the approximated Pareto set has been built, the designer can quickly select the best system configuration satisfying the constraints. Experimental results show that the proposed DPSO technique can speed up the design space exploration time up to 5X with an accuracy of up to 70% with respect to a full search exploration for the selected benchmarks1 .
Gianluca Palermo, Cristina Silvano, Vittorio Zacca
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where DSD
Authors Gianluca Palermo, Cristina Silvano, Vittorio Zaccaria
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