A parallel implementation of JPEG2000 encoder on multi-GPU system

Bumho Kim, Jeong-Woo Lee, K. Yoon
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引用次数: 3

Abstract

There has been an increase in the demand for a high-quality video codec that supports 4K (3,840 × 2,160) or more. JPEG2000 is an important technique for data compression, which has been successfully used in digital cinema and medical application. To process the high workload of JPEG2000 coding for large-scale video data, hybrid CPU/GPU platform is used to obtain high computing power. In this paper, we develop and implementation of the JPEG2000 compression standard in hybrid CPU/GPU platforms. Specifically, we develop multi-GPU implementations of the JPEG2000 encode to obtain high computing power and balance the load between cores and GPUs in the hybrid architecture. In out experiments with multi-GPU, we couple the JPEG2000 codec optimized for multicores and multi-GPUs and achieve high performance of the JPEG2000 compression.
JPEG2000编码器在多gpu系统上的并行实现
对支持4K (3840 × 2160)或更高分辨率的高质量视频编解码器的需求有所增加。JPEG2000是一种重要的数据压缩技术,已成功应用于数字电影和医疗领域。为了处理JPEG2000编码对大规模视频数据的高工作量,采用CPU/GPU混合平台来获得高计算能力。本文在CPU/GPU混合平台上开发并实现了JPEG2000压缩标准。具体而言,我们开发了JPEG2000编码的多gpu实现,以获得高计算能力,并在混合架构中平衡内核和gpu之间的负载。在我们的多gpu实验中,我们将针对多核和多gpu优化的JPEG2000编解码器耦合在一起,实现了JPEG2000的高性能压缩。
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