辅助多媒体加速器:二进制浮点数高效舍入的硬件设计

Mahendra Rathor, Vishesh Mishra, Urbi Chatterjee
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引用次数: 0

摘要

用于多媒体应用程序(如JPEG图像压缩和视频压缩)的硬件加速器非常受欢迎,因为它们能够增强整体性能和系统吞吐量。基本上所有有损压缩技术的核心都是量化过程。在量化过程中,进行舍入以获得压缩图像和视频帧的整数值。最近对照片取证研究的研究表明,浮点数的直接四舍五入(如向上或向下四舍五入)会导致一些压缩伪影,如“JPEG酒窝”。因此,在压缩过程中,执行舍入到最接近的整数值是很重要的,特别是对于高动态范围(HDR)摄影和录像。由于四舍五入到最接近的整数是一个数据密集型过程,因此将其实现为专用硬件对于提高整体性能至关重要。本文提出了一种新的高性能硬件结构,用于将二进制浮点数舍入到最接近的整数。此外,还提出了基本硬件设计的优化版本。与提出的基本架构相比,提出的优化版本的面积减少了6.7%,功耗降低了7.4%。此外,本文还讨论了所提出的浮点舍入硬件与压缩处理器计算内核设计流程的集成。所提出的舍入硬件架构和与压缩过程计算内核的集成设计已在Intel FPGA上实现。据报道,由于这种集成而产生的平均资源开销小于1%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Aiding to Multimedia Accelerators: A Hardware Design for Efficient Rounding of Binary Floating Point Numbers
Hardware accelerators for multimedia applications such as JPEG image compression and video compression are quite popular due to their capability of enhancing overall performance and system throughput. The core of essentially all lossy compression techniques is the quantization process. In the quantization process, rounding is performed to obtain integer values for the compressed images and video frames. The recent studies in the photo forensic research has revealed that the direct rounding e.g. round up or round down of floating point numbers results into some compression artifacts such as ‘JPEG dimples’. Therefore in the compression process, performing rounding to the nearest integer value is important especially for High Dynamic Range (HDR) photography and videography. Since rounding to the nearest integer is a data-intensive process, hence its realization as a dedicated hardware is imperative to enhance overall performance. This paper presents a novel high performance hardware architecture for performing rounding of binary floating point numbers to the nearest integer. Additionally, an optimized version of the basic hardware design is also proposed. The proposed optimized version provides 6.7% reduction in area and 7.4% reduction in power consumption in comparison to the proposed basic architecture. Furthermore, the integration of the proposed floating point rounding hardware with the design flow of the computing kernel of the compression processor is also discussed in the paper. The proposed rounding hardware architecture and the integrated design with the computing kernel of compression process have been implemented on an Intel FPGA. The average resource overhead due to this integration is reported to be less than 1%.
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