# double-precision number

## double-precision number

[¦dəb·əl prə¦sizh·ən ′nəm·bər]
(computer science)
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.
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Atmosphere Temperature Anomaly (ATA) is the mean temperature in degrees ([degrees]C) averaged monthly per year relative to 1951-1980 base period and is represented as a double-precision number. Atmospheric Temperature (AirTemp) is the mean temperature in degrees ([degrees]C) averaged monthly via NCEP/NCAR reanalysis forecast system performing data assimilation using data from 1948 to present (8) and is represented as a double-precision number.
When you choose the date/time data type, Access stores a double-precision number that ranges from 657,434 for January 1, 100, to 2,958,465.99998843 for 11:59:59 p.m.
In contrast, IEEE-type quad-precision numbers might have 113 bits of mantissa; a double-precision number has 53 bits; and a double extended number has 64 bits of precision.
In this representation, a double-precision number is represented as the sum of two singles.
More specifically, we assume that a double-precision number has 53 mantissa bits in memory and 64 in the registers.
Note that we do not use the fact that the inputs are double-precision numbers. Promoting them: to quads sets the low-order bits to zero, a fact the hardware ignores.
One way to get the high and low parts of the product of two double-precision numbers on a machine that supports quad-precision variables.
One way to get the high and low parts of the product of two double-precision numbers on a machine that does a fused multiply-add but does not support a quad datatype.
One way to get all the digits of the product of two double-precision numbers stored in single-single format.
If we are using normalized, IEEE floating-point, double-precision numbers which have an implicit leading 1, mantissas lie in the interval [1,2).
Method Component Total Bytes U km double-precision numbers SVD V kn double-precision numbers 8k(m + n + 1) [Sigma] k double-precision numbers X km numbers from {-1, 0, 1} SDD Y kn numbers from {-1, 0, 1} 4k + 1/4k(m +n) D k single-precision numbers The SDD approximation is formed iteratively.
Numeric variables can be convened to string variables by using the MKS\$, MKI\$, or MKD\$ functions for single-precision numbers, integers, and double-precision numbers, respectively.

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