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首页> 外文会议>Conference on Real-Time Image Processing; 20080128-29; San Jose,CA(US) >Optimization Model for Memory Bandwidth Usage in X-ray Image Enhancement
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Optimization Model for Memory Bandwidth Usage in X-ray Image Enhancement

机译：X射线图像增强中内存带宽使用的优化模型

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摘要

In Cardiovascular minimal invasive interventions, physicians require low-latency X-ray imaging applications, as their actions must be directly visible on the screen. The image-processing system should enable the simultaneous execution of a plurality of functions. Because dedicated hardware lacks flexibility, there is a growing interest in using off-the-shelf computer technology. Because memory bandwidth is a scarce parameter, we will focus on optimization methods for bandwidth reduction within multiprocessor systems at the chip level. We create a practical realistic model of required compute and memory bandwidth for a given set of image-processing functions. Similar modeling is applied for the available system resources. We concentrate in particular on X-ray image processing based on multi-resolution decomposition, noise reduction and image-enhancement techniques. We derive formulas for which we can optimize the mapping of the application onto processors, cache and memory for different configurations. The data-block granularity is matched to the memory hierarchy, so that caching will be optimized for low latency. More specifically, we exploit the locality of the signal-processing functions to streamline the memory communication. A substantial performance improvement is realized by a new memory-communication model that incorporates the data dependencies of the image-processing functions. Results show a memory-bandwidth reduction in the order of 60% and a latency reduction in the order of 30-60% compared to straightforward implementations.
机译：在心血管微创介入治疗中，医生要求低延迟X射线成像应用，因为他们的动作必须在屏幕上直接可见。该图像处理系统应该能够同时执行多个功能。由于专用硬件缺乏灵活性，因此人们对使用现成的计算机技术越来越感兴趣。由于内存带宽是一个稀缺的参数，因此我们将专注于在芯片级别降低多处理器系统中带宽的优化方法。我们为一组给定的图像处理功能创建了一个实用的现实模型，其中需要计算和内存带宽。将类似的建模应用于可用的系统资源。我们特别专注于基于多分辨率分解，降噪和图像增强技术的X射线图像处理。我们得出公式，可以针对不同的配置优化应用程序到处理器，高速缓存和内存的映射。数据块的粒度与内存层次结构匹配，因此可以优化缓存以降低延迟。更具体地说，我们利用信号处理功能的局部性来简化存储器通信。通过合并了图像处理功能的数据依赖关系的新的内存通信模型，可以实现性能的显着提高。结果显示，与简单的实现相比，内存带宽减少了60％左右，延迟减少了30-60％左右。

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