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Novel approach for implementing convolutions with small tables

机译:用小表实现卷积的新颖方法

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The author presents an algorithm, the one over eight squared algorithm, which can be useful in computing tasks with convolutional complexity, such as convolutions, correlations and complex multiplications. The algorithm reduces the address space requirement and hardware investment for table lookup implementations of such tasks from 2/sup 2n/ to 2/sup n/, where n is the width of the operands. Owing to considerable reduction in the required table size, convolutions and correlations with table lookups can be cost-effectively extended to wider operands.
机译:作者提出了一种算法,即八分之一平方算法,该算法可用于计算卷积复杂度的任务,例如卷积,相关性和复数乘法。该算法将此类任务的表查找实现的地址空间要求和硬件投资从2 / sup 2n /减少到2 / sup n /,其中n是操作数的宽度。由于所需表大小的显着减少,卷积和与表查找的相关性可以经济高效地扩展到更宽的操作数。

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