A new profiling and pipelining approach for HEVC decoder on ZedBoard platform

Abstract

New multimedia applications such as mobile video, high-quality Internet video or digital television requires high-performance encoding of video signals to meet technical constraints such as runtime, bandwidth or latency. Video coding standard h.265 HEVC (High Efficiency Video Coding) was developed by JCT-VC to replace the MPEG-2, MPEG-4 and h.264 codecs and to respond to these new functional constraints. Currently, there are several implementations of this standard. Some implementations are based on software acceleration techniques; Others, on techniques of purely hardware acceleration and some others combine the two techniques. In software implementations, several techniques are used in order to decrease the video coding and decoding time. We quote data parallelism, tasks parallelism and combined solutions. In the other hand, In order to fulfill the computational demands of the new standard, HEVC includes several coding tools that allow dividing each picture into several partitions that can be processed in parallel, without degrading neither the quality nor the bitrate. In this paper, we adapt one of these approaches, the Tile coding tool to propose a pipeline execution approach of the HEVC / h265 decoder application in its version HM Test model. This approach is based on a fine profiling by using code injection techniques supported by standard profiling tools such as Gprof and Valgrind. Profiling allowed us to divide functions into four groups according to three criteria: the first criterion is based on the minimization of communication between the different functions groups in order to have minimal intergroup communication and maximum intragroup communication. The second criterion is the load balancing between processors. The third criterion is the parallelism between functions. Experiments carried out in this paper are based on the Zedboard platform, which integrates a chip Zynq xilinx with a dual core ARM A9. We start with a purely sequential version to reach a version that use the pipeline techniques applied to the functional blocks that can run in parallel on the two processors of the experimental Platform. Results show that a gain of 30% is achieved compared to the sequential implementation.