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  2. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    Since the introduction of IEEE 754, the default method (round to nearest, ties to even, sometimes called Banker's Rounding) is more commonly used. This method rounds the ideal (infinitely precise) result of an arithmetic operation to the nearest representable value, and gives that representation as the result.

  3. Rounding - Wikipedia

    en.wikipedia.org/wiki/Rounding

    This variant of the round-to-nearest method is also called convergent rounding, statistician's rounding, Dutch rounding, Gaussian rounding, odd–even rounding, [6] or bankers' rounding. [ 7 ] This is the default rounding mode used in IEEE 754 operations for results in binary floating-point formats.

  4. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    Round-by-chop: The base-expansion of is truncated after the ()-th digit. This rounding rule is biased because it always moves the result toward zero. Round-to-nearest: () is set to the nearest floating-point number to . When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal ...

  5. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    The following is a list of well-known algorithms along with one-line descriptions ... Used in Python 2.3 and up, and Java SE 7. ... Newton's method; Rounding ...

  6. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    In the mainstream definition, machine epsilon is independent of rounding method, and is defined simply as the difference between 1 and the next larger floating point number. In the formal definition, machine epsilon is dependent on the type of rounding used and is also called unit roundoff, which has the symbol bold Roman u.

  7. Kahan summation algorithm - Wikipedia

    en.wikipedia.org/wiki/Kahan_summation_algorithm

    The exact result is 10005.85987, which rounds to 10005.9. With a plain summation, each incoming value would be aligned with sum, and many low-order digits would be lost (by truncation or rounding). The first result, after rounding, would be 10003.1. The second result would be 10005.81828 before rounding and 10005.8 after rounding. This is not ...

  8. Significant figures - Wikipedia

    en.wikipedia.org/wiki/Significant_figures

    If the n + 1 digit is 5 not followed by other digits or followed by only zeros, then rounding requires a tie-breaking rule. For example, to round 1.25 to 2 significant figures: Round half away from zero rounds up to 1.3. This is the default rounding method implied in many disciplines [citation needed] if the required rounding method is not ...

  9. Multiply–accumulate operation - Wikipedia

    en.wikipedia.org/wiki/Multiply–accumulate...

    That is, where an unfused multiply–add would compute the product b × c, round it to N significant bits, add the result to a, and round back to N significant bits, a fused multiply–add would compute the entire expression a + (b × c) to its full precision before rounding the final result down to N significant bits.