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This paper presents an optimized parallel algorithm for the next-generation video codec HEVC. The proposed method provides maximized parallel scalability by exploiting two levels of parallelism: frame-level and tasklevel. Frame-level parallelism is exploited by using a graph that efficiently provides a parallel coding order of the frames with complex reference dependencies. The proposed Reference Dependency Graph is generated at runtime by a novel construction algorithm that dynamically analyzes the configuration of the HEVC codec.Task-level parallelism is exploited to provide further scalability to frame-level parallelization. A pipelined execution is allowed for independent tasks, which are defined by dividing and categorizing a single coding process into multiple types of tasks. The proposed parallel encoder and decoder do not suffer from loss in coding efficiency because neither constraints nor modification in coding options are required. The proposed parallel methods result in an average encoding speedup of 1.75 and the aggressive method that exploits additional frame-level parallelism achieved 6.52 speedup using eight physical cores.Abstract-This paper presents an optimized parallel algorithm for the next-generation video codec HEVC. The proposed method provides maximized parallel scalability by exploiting two levels of parallelism: frame-level and task-level. Frame-level parallelism is exploited by using a graph that efficiently provides a parallel coding order of the frames with complex reference dependencies. The proposed Reference Dependency Graph is generated at runtime by a novel construction algorithm that dynamically analyzes the configuration of the HEVC codec. Tasklevel parallelism is exploited to provide further scalability to frame-level parallelization. A pipelined execution is allowed for independent tasks, which are defined by dividing and categorizing a single coding process into multiple types of tasks. The proposed parallel encoder and decoder do not suffer from loss in coding efficiency because neither constraints nor modification in coding options are required. The proposed parallel methods result in an average encoding speedup of 1.75 and the aggressive method that exploits additional frame-level parallelism achieved 6.52 speedup using eight physical cores.

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