FFT Implementation on a Streaming Architecture

Fast Fourier Transform (FFT) is a useful tool for applications requiring signal analysis and processing. However, its high computational cost requires efficient implementations, specially if real time applications are used, where response time is a decisive factor. Thus, the computational cost and wide application range that requires FFT transforms has motivated the research of efficient implementations. Recently, GPU computing is becoming more and more relevant because of their high computational power and low cost, but due to its novelty there is some lack of tools and libraries. In this paper we propose an efficient implementation of the FFT with AMD's Brook+ language. We describe several features and optimization strategies, analyzing the scalability and performance compared to other well-known existing solutions.