Domain Specific Description in Halide for Randomized Image Convolution
Domain Specific Description in Halide for Randomized Image Convolution
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发表时间：
2021-12
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通讯作者：
Hiroyasu Takagi;Norishige Fukushima
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作者：
Hiroyasu Takagi;Norishige Fukushima
我们建议使用随机算法提出一种针对有限脉冲响应（FIR）过滤器的特定领域语言。高斯和双侧过滤器等FIR过滤器是信号处理和图像处理的基本工具。随着卷积内核大小变得更加广泛，这些卷积的计算时间会增加，因为计算时间取决于内核大小。通过随机子采样近似内核是减少计算时间的方法之一。这种近似值的优点很容易控制其近似准确性和计算时间之间的平衡。但是，优化此近似值以适合最近CPU中提供的多核和SIMD指令非常棘手。卤化物是一种用于图像处理的特定领域语言，可以通过简洁的描述强大地加速图像处理。卤化物的显着点之一是，它可以描述为对算法的单独描述，即图像处理和调度的本质，可优化处理等处理，例如并行化和矢量化。使用卤化物，我们通过随机算法优化了FIR滤波器的近似值。另外，我们设计了一种新的特定领域的语言，该语言在简洁的描述中输出优化的卤化物代码。
We propose a domain-specific language for finite impulse response (FIR) filters using a randomized algorithm. FIR filters such as Gaussian and bilateral filters are fundamental tools for signal processing and image processing. The computational time of these convolutions increases as the convolution kernel size becomes more extensive because the computational time depends on the kernel size. Approximating the kernel by random sub-sampling is one of the methods to reduce the computational time. The advantage of this approximation is easily controllable for the balance between its approximation accuracy and computational time. However, it is tricky to optimize this approximation to suit the multi-core and SIMD instructions provided in recent CPUs. Halide is a domain-specific language for image processing and can powerfully accelerate image processing with a concise description. One of the remarkable points of Halide is that it can be described as a separate description of the algorithm, which is the essence of image processing, and scheduling, which optimizes the processing such as parallelization and vectorization. Using Halide, we optimize the approximation of the FIR filter by the randomized algorithm. Also, we design a new domain-specific language that outputs the optimized Halide code in a concise description.