Accelerating Vector Operations by Utilizing

To enhance performance of digital signal processing tasks while keeping the flexibility of programmable solutions is a clear motivation for coprocessors implemented as reconfigurable hardware blocks. This paper investigates the applicability of such coprocessors targeting digital signal processing multi-media applications, initially in the field of speech and audio. A tightly coupled coprocessor architecture with reconfigurable datapath and a local memory system is presented. The coprocessor inter- acts with the main processor through asynchronous FIFOs. Three computational models that provide support for functionality of different granularities to be accelerated are investigated. A speedup in the range of 2 to 46 compared to processor execution is achieved for vector operations and larger kernels such as autocorrelation, block filtering and Fast Fourier Transform. I. INTRODUCTION