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Correctness proofs outline for Newton-Raphson based floating-point divide and square root algorithms

机译:基于牛顿-拉夫逊浮点除法和平方根算法的正确性证明大纲

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This paper describes a study of a class of algorithms for the floating-point divide and square root operations, based on the Newton-Raphson iterative method. The two main goals were. (1) Proving the IEEE correctness of these iterative floating-point algorithms, i.e. compliance with the IEEE-754 standard for binary floating-point operations. The focus was on software driven iterative algorithms, instead of the hardware based implementations that dominated until now. (2) Identifying the special cases of operands that require results. Assistance due to possible overflow, or loss of precision of intermediate This study was initiated in an attempt to prove the IEEE for a class of divide and square root based on the Newton-Rapshson iterative methods. As more insight into the inner workings of these algorithms was gained, it became obvious that a formal study and proof were necessary in order to achieve the desired objectives. The result is a complete and rigorous proof of IEEE correctness for floating-point divide and square root algorithms based on the Newton-Raphson iterative method. Even more, the method used in proving the IEEE correctness of the square root algorithm is applicable in principle to any iterative algorithm, not only based on the Newton-Raphson method. Conditions requiring Software Assistance (SWA) were also determined, and were used to identify cases when alternate algorithms are needed to generate correct results. Overall, this is one important step toward flawless implementation of these floating-point operations based on software implementations.
机译:本文介绍了一种基于牛顿-拉夫森迭代法的浮点除法和平方根运算算法的研究。两个主要目标是。 (1)证明这些迭代浮点算法的IEEE正确性,即符合IEEE-754标准的二进制浮点运算。重点是软件驱动的迭代算法,而不是目前为止占主导地位的基于硬件的实现。 (2)确定需要结果的操作数的特殊情况。由于可能的溢出或中间精度的损失而提供的帮助。这项研究旨在尝试基于Newton-Rapshson迭代方法证明IEEE用于一类除法和平方根。随着对这些算法的内部工作方式的深入了解,很明显,为了实现所需的目标,必须进行正式的研究和证明。结果是基于Newton-Raphson迭代方法的浮点除法和平方根算法的IEEE正确性的完整而严格的证明。甚至,证明平方根算法的IEEE正确性的方法原则上可应用于任何迭代算法,而不仅是基于Newton-Raphson方法。还确定了需要软件协助(SWA)的条件,并将其用于识别需要替代算法以生成正确结果的情况。总体而言,这是迈向基于软件实现的这些浮点运算的完美实现的重要一步。

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