Three-dimensional Fourier convolution with an array processor
Three-dimensional Fourier convolution with an array processor
复制标题
使用阵列处理器的三维傅立叶卷积
DOI：
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发表时间：
1990
期刊：
影响因子：
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通讯作者：
A. Boyer
中科院分区：
文献类型：
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作者：
N. H. Wells;C. Burrus;G. Desobry;A. Boyer
本文介绍了减少对真实的数据执行三维卷积所需的CPU时间、内存和I/O时间的技术，以及阵列处理器的使用。这些技术利用数学上真实的输入数据的傅立叶变换的厄米特性质，利用在三维中具有镜像对称性的卷积核，并且消除平凡变换。结果是在包含250 K真实的元素的三维64×64×64数组上进行卷积，仅需28 s即可执行。中型阵列处理器的内存空间足够大，可以同时在整个真实的单精度阵列上执行程序，而无需在阵列处理器和磁盘存储器之间传输数据。
This paper describes techniques for reducing CPU time, memory, and I/O time required to perform a three‐dimensional convolution on real data, and the use of an array processor. These techniques capitalize on the Hermitian nature of the Fourier transform of mathematically real input data, take advantage of convolution kernels having mirror symmetry in three dimensions, and eliminate trivial transformations. The result is convolution over a three‐dimensional 64×64×64 array containing 250 K real elements that requires only 28 s to execute. Memory space of a medium‐sized array processor is sufficiently large for the procedures to be carried out on entire real, single‐precision arrays at one time without transferring data between the array processor and disk storage.