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Double-precision floating-point format (sometimes called FP64 or float64) is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point. Double precision may be chosen when the range or precision of single precision would be insufficient.
This gives from 33 to 36 significant decimal digits precision. If a decimal string with at most 33 significant digits is converted to the IEEE 754 quadruple-precision format, giving a normal number, and then converted back to a decimal string with the same number of digits, the final result should match the original string.
Go has a number of built-in types, including numeric ones (byte, int64, float32, etc.), Booleans, and byte strings (string). Strings are immutable; built-in operators and keywords (rather than functions) provide concatenation, comparison, and UTF-8 encoding/decoding. [59] Record types can be defined with the struct keyword. [60]
If a decimal string with at most 6 significant digits is converted to the IEEE 754 single-precision format, giving a normal number, and then converted back to a decimal string with the same number of digits, the final result should match the original string. If an IEEE 754 single-precision number is converted to a decimal string with at least 9 ...
interchange formats: encodings (bit strings) that may be used to exchange floating-point data in an efficient and compact form; rounding rules: properties to be satisfied when rounding numbers during arithmetic and conversions; operations: arithmetic and other operations (such as trigonometric functions) on arithmetic formats
In computing, half precision (sometimes called FP16 or float16) is a binary floating-point computer number format that occupies 16 bits (two bytes in modern computers) in computer memory.
Extended precision refers to floating-point number formats that provide greater precision than the basic floating-point formats. [1] Extended-precision formats support a basic format by minimizing roundoff and overflow errors in intermediate values of expressions on the base format.
Decimal64 supports 'normal' values that can have 16 digit precision from ±1.000 000 000 000 000 × 10 ^ −383 to ±9.999 999 999 999 999 × 10 ^ 384, plus 'denormal' values with ramp-down relative precision down to ±1.×10 −398, signed zeros, signed infinities and NaN (Not a Number).