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Numerical Reproducibility and Parallel Computations: Issues for Interval Algorithms

机译:数值可再现性和并行计算:间隔算法的问题

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What is called numerical reproducibility is the problem of getting the same result when the scientific computation is run several times, either on the same machine or on different machines, with different types and numbers of processing units, execution environments, computational loads, etc. This problem is especially stringent for HPC numerical simulations. In what follows, we identify the problems encountered when implementing interval routines in floating-point arithmetic. Some are well-known and common in numerical computations, some are specific to interval computations. We propose here a classification of floating-point issues by distinguishing their severity with respect to correctness and tightness of the computed interval result. In fact, interval computation can accommodate the lack of numerical reproducibility as long as it does not affect the inclusion property, which is the main property of interval arithmetic. Several ways to preserve the inclusion property are presented, on the example of the product of matrices with interval coefficients.
机译:所谓的数值可重复性是当科学计算在同一台机器上或在不同机器上,具有不同类型和数量的处理单元,执行环境的计算机上多次运行时,获得相同结果的问题。 ,计算负荷等。对于HPC数值模拟,此问题尤为严格。接下来,我们确定在浮点算术中实现间隔例程时遇到的问题。有些在数值计算中是众所周知的和常见的,有些则专门用于区间计算。我们在这里提出浮点问题的分类,方法是根据计算间隔结果的正确性和紧密性来区分其严重性。实际上,区间计算只要不影响作为区间算术的主要特性的包含特性,就可以弥补数值再现性的不足。在具有间隔系数的矩阵乘积的示例中,提出了几种保留包含特性的方法。

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