对称流多处理器上的动态流水线分割视频解码

Ming-Ju Wu, Yan-Ting Chen, Chun-Jen Tsai
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摘要

在本文中,我们为对称流多处理器(SSMP)架构实现了一个动态管道分割视频解码器。SSMP体系结构扩展了传统的对称多处理器(SMP)体系结构,具有专用的每核刮刮板存储器和处理器间通信(IPC)控制器,可在处理器内核之间有效地传递数据。SSMP体系结构允许处理器内核以细粒度的软件管道方式有效地协作。传统的软件流水线视频解码器具有固定的流水线级分区。AVC / H。本文研究的264视频解码器将视频宏块(MB)解码任务的不同阶段动态分配给不同的处理器内核,以保持处理器内核之间的负载平衡。管道分区策略基于阶段间缓冲区的队列级别。实验结果表明,与基于波前的并行视频解码器相比,所提出的动态管道分割视频解码器的平均速度快34%。
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Dynamic pipeline-partitioned video decoding on symmetric stream multiprocessors
In this paper, we have implemented a dynamic pipeline-partitioning video decoder for the symmetric stream multiprocessor (SSMP) architecture. The SSMP architecture extends the traditional symmetric multiprocessor (SMP) architecture with dedicated per-core scratchpad memories and inter-processor communication (IPC) controllers for efficient data passing between the processor cores. The SSMP architecture allows the processor cores to cooperate efficiently in a fine-grained software pipeline fashion. A traditional software pipelined video decoder has fixed pipeline-stage partitions. The AVC/H.264 video decoder investigated in this paper dynamically assigns different stages of the video macroblock (MB) decoding tasks to different processor cores in order to maintain load balance among the processor cores. The pipeline partitioning policy is based on the queue levels of the inter-stage buffers. Experimental results show that, on average, the proposed dynamic pipeline-partitioning video decoder is 34% faster compared to a wavefront-based parallel video decoder.
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