Abstract
Cuckoo search algorithm (CSA) has been a candidate for numerous recent applications and showed great compatibility in solving optimization problems. It is a metaheuristic algorithm which is based on the odd breeding strategy of the Cuckoo bird spices. It is used to find an optimum or near optimum solution for a certain problem. In this research, we propose an FPGA hardware implementation for the CSA based on single precision IEEE floating point (FP). The FP format provides a wider range and higher precision when compared to fixed point format. To the best of our knowledge, this is the first study to consider implementing FP format-based CSA on FPGA. The proposed design is implemented using pipelined and parallel techniques to get a high throughput and speed. The design is controlled and coordinated using finite state machines (FSMs) modules and is configured on Cyclone IV E FPGA chip from Intel. Three common benchmark functions are used to evaluate the performance of the proposed design. The design has a maximum operating frequency of 99 MHz. It was found out the maximum power consumption for the most complex function is 610.28 mW, mainly due to the use of FP format. In addition, the proposed design is implementation and evaluated for multidimensional operation. Accordingly, the proposed design is suitable for path planning for unmanned aerial vehicles (UAVs), sensor deployments for wireless sensor networks (WSNs) in addition to medical diagnostic and DSP applications.
Highlights
Optimization algorithm (OA) is a procedure or set of instructions that is used to find an optimum solution for a given problem
The results have shown that the Cuckoo search algorithm (CSA) surpasses other optimization techniques such as perturb and observe (P&O) and particle swarm optimization (PSO)
Modern field programmable gate array (FPGA) are suitable for real time applications since they include digital signal processing (DSP) blocks, digital clock management (DCM) blocks, memory controller, error correcting code (ECC) blocks and one or more dedicated microprocessors
Summary
Optimization algorithm (OA) is a procedure or set of instructions that is used to find an optimum solution for a given problem. The nature inspired or bio metaheuristic optimization algorithms imitate the techniques found in nature to find the best solution. In data mining application, combining CSA with association rule mining (ARM) produces rules that are simple, easy to follow, and provide good coverage of the dataset as specified in [29] This combination consumed less time than other algorithms which is very critical when number of items or transactions becomes large [30]. Modern FPGAs are suitable for real time applications since they include digital signal processing (DSP) blocks, digital clock management (DCM) blocks, memory controller, error correcting code (ECC) blocks and one or more dedicated microprocessors They include protocol engines supporting common peripheral interfaces and a variety of high-speed I/O standard peripherals [36].
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