A Self-Reconfigurable Platform for Scalable DCT Computation Using Compressed Partial Bitstreams and BlockRAM Prefetching

In this paper, we propose a self-reconfigurable platform which can reconfigure the architecture of DCT computations during run-time using dynamic partial reconfiguration. The scalable architecture of DCT computations can compute different number of DCT coefficients in the zigzag scan order to adapt to different requirements, such as power consumption, hardware resource, and performance. We propose a configuration manager which is implemented in the embedded processor in order to adaptively control the reconfiguration of scalable DCT architecture during run-time. In addition, we use LZSS algorithm for compression of the partial bitstreams and on-chip BlockRAM as a cache to reduce latency overhead for loading the partial bitstreams from the off-chip memory for run-time reconfiguration. A hardware module is designed for parallel reconfiguration of the partial bitstreams. The experimental results show that our approach can reduce the external memory accesses by 69% and can achieve 400 MBytes/s reconfiguration rate. Detailed trade-offs of power, throughput, and quality are investigated, and used as a criterion for self-reconfiguration.