Parallel Genetic Algorithm for Optimizing Run-time Reconfigurable Circuits
نویسندگان
چکیده
In this paper a methodology for finding the maximal common subgraph of two directed graphs with parallel genetic algorithm is discussed. The method is directly applicable to the optimization of configurations of FPGA (Field Programmable Gate Array) circuits in Run-Time Reconfigurable systems. The problem of finding the maximal common subgraph is known to be NP-complete. The advantage of our approach is that we find optimal or near-optimal solutions in polynomial time using a genetic algorithm. Since the cost function of the optimization task is multimodal, an implementation of parallel genetic algorithm assures significant improvments of the results.
منابع مشابه
Optimization of Agricultural BMPs Using a Parallel Computing Based Multi-Objective Optimization Algorithm
Beneficial Management Practices (BMPs) are important measures for reducing agricultural non-point source (NPS) pollution. However, selection of BMPs for placement in a watershed requires optimizing available resources to maximize possible water quality benefits. Due to its iterative nature, the optimization typically takes a long time to achieve the BMP trade-off results which is not desirable ...
متن کاملA hardware Memetic accelerator for VLSI circuit partitioning
During the last decade, the complexity and size of circuits have been rapidly increasing, placing a stressing demand on industry for faster and more efficient CAD tools for VLSI circuit layout. One major problem is the computational requirements for optimizing the place and route operations of a VLSI circuit. Thus, this paper investigates the feasibility of using reconfigurable computing platfo...
متن کاملA New Approach to Solve N-Queen Problem with Parallel Genetic Algorithm
Over the past few decades great efforts were made to solve uncertain hybrid optimization problems. The n-Queen problem is one of such problems that many solutions have been proposed for. The traditional methods to solve this problem are exponential in terms of runtime and are not acceptable in terms of space and memory complexity. In this study, parallel genetic algorithms are proposed to solve...
متن کاملOptimization of Quantum Cellular Automata Circuits by Genetic Algorithm
Quantum cellular automata (QCA) enables performing arithmetic and logic operations at the molecular scale. This nanotechnology promises high device density, low power consumption and high computational power. Unlike the CMOS technology where the ON and OFF states of the transistors represent binary information, in QCA, data is represented by the charge configuration. The primary and basic devic...
متن کاملSimulation and Genetic Algorithms for Optimizing Comminution Circuit at Gol-e-Gohar Iron Plant (RESEARCH NOTE)
simulation optimization is a scientific tool that is widely used to design and optimize comminution circuits in mineral processing plants. In this research, first of all, in order to determine the suitable d80 for cicuit hydrocyclone underflow, the requiremed parameters of simulator (residence time distribution, breakage function, selection function and Plitt’s model calibration) were determin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002