Scalable FPGA-based architecture for DCT computation using dynamic partial reconfiguration

Abstract

In this article, we propose field programmable gate array-based scalable architecture for discrete cosine transform (DCT) computation using dynamic partial reconfiguration. Our architecture can achieve quality scalability using dynamic partial reconfiguration. This is important for some critical applications that need continuous hardware servicing. Our scalable architecture has three features. First, the architecture can perform DCT computations for eight different zones, that is, from 1 × 1 DCT to 8× 8 DCT. Second, the architecture can change the configuration of processing elements to trade off the precisions of DCT coefficients with computational complexity. Third, unused PEs for DCT can be used for motion estimation computations. Using dynamic partial reconfiguration with 2.3MB bitstreams, 80 distinct hardware architectures can be implemented. We show the experimental results and comparisons between different configurations using both partial reconfiguration and nonpartial reconfiguration process. The detailed trade-offs among visual quality, power consumption, processing clock cycles, and reconfiguration overhead are analyzed in the article.