论文标题

迭代算法的快速近似倒数近似

Fast approximate reciprocal approximations for iterative algorithms

论文作者

Lunglmayr, Michael, Ploder, Oliver

论文摘要

相互函数1/x对于许多实时算法很重要。它用于从迭代估计到机器学习的领域的各种算法中使用。这些算法中有许多本质上是迭代性的,需要对倒数的在线计算。这种迭代结构通常阻止有效使用管道来实施倒数。因此,仅需要低量的时钟周期的相互算法。许多实时算法通常具有近似性质,可以忍受仅使用倒数的近似解决方案。 因此,我们提出了相互函数的低复杂性非涉及近似值。可以仅使用组合逻辑来计算此近似值。我们提出综合结果表明,在高时钟频率下,可以在面积较低的情况下实现所提出的方法。我们分析地描述了近似值的误差,并表明,通过优化近似中使用的常数,可以获得具有不同误差行为的不同变体。此外,我们目前的应用示例的绩效结果在使用我们的建议方法时,与使用确切的相互函数相比,仅显示可忽略不计的性能降解,这证明了我们提出的方法的多功能性。

The reciprocal function, 1/x, is important for many real-time algorithms. It is used in a large variety of algorithms from areas ranging from iterative estimation to machine learning. Many of these algorithms are iterative in nature and require the online computation of the reciprocal. Such an iterative structure often prevents effective use of pipelining for implementation of the reciprocal. For this reason, a reciprocal algorithm requiring only a low amount of clock cycles is desired. Many real-time algorithms, often being of approximate nature, can tolerate the use of only an approximate solution of the reciprocal. For this reason, we present a low complexity non-iterative approximation of the reciprocal function. This approximation can be calculated using only combinatorial logic. We present synthesis results showing that the proposed approach can be implemented with low area requirements at high clock frequencies. We analytically describe the error of the approximation and show that by optimizing a constant value used in the approximation, different variants with different error behaviors can be obtained. We furthermore present performance results of application examples that, when using our proposed method, show only negligible performance degradation compared to when using the exact reciprocal function, demonstrating the versatility of our proposed approach.

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