Transform coding on programmable stream processors

Abstract

Stream processors can achieve high performance in stream applications that share stream characteristics of large parallelism, intensive computation and little data reuse. Transform coding, as a core component in video compression, is widely used in video storage and video transmission. This paper summarizes stream execution mechanism and explores design approaches of programmable stream processors including the Imagine stream processor and graphics processing unit (GPU). Based on the stream processing model, stream algorithms for block-based and frame-based (nonblock-based) transform coding are presented and mapped onto stream processors. Especially, an Interleaved Streaming Transform (IST) algorithm on Imagine and a Row-wise Zonal Transform (RZT) algorithm on GPU for 4×4 integer transform in H.264 are proposed to exploit great potential of stream processing for block-based transform. Our experiments of transform coding suite on Imagine and GPU show that the coding efficiency of stream processors is far beyond the real-time requirements of current video applications, dealing with a variety of different video resolutions ranging from QCIF to high definition (HD). The performance evaluation of stream implementations discusses the architectural supports for transform coding, and presents the significant improvements over other programmable platforms. Transform coding may take advantage of the flexibility of programmable stream processors with high performance to play an important role in the future.