Multi-FFT Vectorization for the Cell Multicore Processor

Abstract

The emergence of streaming multicore processors with multi-SIMD architectures and ultra-low power operation combined with real-time compute and I/O reconfigurability opens unprecedented opportunities for executing sophisticated signal processing algorithms faster and within a much lower energy budget. Here, we present an unconventional FFT implementation scheme for the IBM Cell, named transverse vectorization. It is shown to outperform (both in terms of timing or GFLOP throughput) the fastest FFT results reported to date in the open literature.

Implementation of the SIMT based Image Signal Processor for the Image Processing

“…Radix-2 FFT의 수행 시간 비교를 위해 1024 point에 대한 FFT 수행 시간을 표 1과 같이 cell multicore processor [6] , 임베디드 플랫폼의 CPU와 비교하였다. 1024 Point에 대한 FFT 수행 시간 비교 결과는 그림 5와 같다.…”