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  2. 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 ...

  3. Floating-point error mitigation - Wikipedia

    en.wikipedia.org/wiki/Floating-point_error...

    Huberto M. Sierra noted in his 1956 patent "Floating Decimal Point Arithmetic Control Means for Calculator": [1] Thus under some conditions, the major portion of the significant data digits may lie beyond the capacity of the registers.

  4. GNU MPFR - Wikipedia

    en.wikipedia.org/wiki/GNU_MPFR

    The GNU Multiple Precision Floating-Point Reliable Library (GNU MPFR) is a GNU portable C library for arbitrary-precision binary floating-point computation with correct rounding, based on GNU Multi-Precision Library. [1] [2]

  5. 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.

  6. Fixed-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_arithmetic

    To convert a fixed-point number to floating-point, one may convert the integer to floating-point and then divide it by the scaling factor S. This conversion may entail rounding if the integer's absolute value is greater than 2 24 (for binary single-precision IEEE floating point) or of 2 53 (for double-precision).

  7. Decimal floating point - Wikipedia

    en.wikipedia.org/wiki/Decimal_floating_point

    Like the binary floating-point formats, the number is divided into a sign, an exponent, and a significand. Unlike binary floating-point, numbers are not necessarily normalized; values with few significant digits have multiple possible representations: 1×10 2 =0.1×10 3 =0.01×10 4, etc. When the significand is zero, the exponent can be any ...

  8. List of arbitrary-precision arithmetic software - Wikipedia

    en.wikipedia.org/wiki/List_of_arbitrary...

    JavaScript: as of ES2020, BigInt is supported in most browsers; [2] the gwt-math library provides an interface to java.math.BigDecimal, and libraries such as DecimalJS, BigInt and Crunch support arbitrary-precision integers. Julia: the built-in BigFloat and BigInt types provide arbitrary-precision floating point and integer arithmetic respectively.

  9. Kahan summation algorithm - Wikipedia

    en.wikipedia.org/wiki/Kahan_summation_algorithm

    = 2.80000 - 2.75987 As expected, the low-order parts can be retained in c with no or minor round-off effects. = 0.0401300 In this iteration, t was a bit too high, the excess will be subtracted off in next iteration. sum = 10005.9 Exact result is 10005.85987, sum is correct, rounded to 6 digits.