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In this study, a scalable coprocessor for accelerating the Differential Evolution (DE) algorithm is presented. The coprocessor is interfaced with PowerPC embedded processor of Xilinx Virtex-5 FX70T Field Programmable Gate Array. In the proposed design, the DE algorithm module is tightly coupled with fitness function module to reduce communication and control overhead. The fixed point DE algorithm is implemented in the coprocessor whereas both fixed and floating point DE are implemented in the embedded processor. Performance of the coprocessor is evaluated by optimising benchmark functions of different complexities. The implementation results show that the coprocessor is 73.14-160.2× and 2.19-27.63× faster compared to the software execution time of the floating and fixed point algorithm respectively. As a case study, spectrum allocation problem of cognitive radio network is evaluated with the coprocessor. Results show an acceleration of 76.79-105× and 5.19-6.91× with respect to floating and fixed point DE in embedded processor. It is also observed that the application occupies 56% of BRAM, 54% of DSP48E, 16% of slice LUTs and maximum frequency of operation as 63.55 MHz in a Virtex-5 FPGA. This type of coprocessor is suitable for embedded applications where the fitness function remains unchanged.