Fast inverse square root and William Kahan

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Fast inverse square root and William Kahan

Fast inverse square root vs. William Kahan

Fast inverse square root, sometimes referred to as Fast InvSqrt() or by the hexadecimal constant 0x5F3759DF, is an algorithm that estimates, the reciprocal (or multiplicative inverse) of the square root of a 32-bit floating-point number in IEEE 754 floating-point format. William "Velvel" Morton Kahan (born June 5, 1933) is a Canadian mathematician and computer scientist who received the Turing Award in 1989 for "his fundamental contributions to numerical analysis", was named an ACM Fellow in 1994, and inducted into the National Academy of Engineering in 2005.

Similarities between Fast inverse square root and William Kahan

Fast inverse square root and William Kahan have 2 things in common (in Unionpedia): Floating-point arithmetic, IEEE 754-1985.

Floating-point arithmetic

In computing, floating-point arithmetic is arithmetic using formulaic representation of real numbers as an approximation so as to support a trade-off between range and precision.

Fast inverse square root and Floating-point arithmetic · Floating-point arithmetic and William Kahan · See more »

IEEE 754-1985

IEEE 754-1985 was an industry standard for representing floating-point numbers in computers, officially adopted in 1985 and superseded in 2008 by IEEE 754-2008.

Fast inverse square root and IEEE 754-1985 · IEEE 754-1985 and William Kahan · See more »

The list above answers the following questions

What Fast inverse square root and William Kahan have in common
What are the similarities between Fast inverse square root and William Kahan

Fast inverse square root and William Kahan Comparison

Fast inverse square root has 65 relations, while William Kahan has 27. As they have in common 2, the Jaccard index is 2.17% = 2 / (65 + 27).

References

This article shows the relationship between Fast inverse square root and William Kahan. To access each article from which the information was extracted, please visit:

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