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Before the widespread adoption of IEEE 754-1985, the representation and properties of floating-point data types depended on the computer manufacturer and computer model, and upon decisions made by programming-language designers. E.g., GW-BASIC's single-precision data type was the 32-bit MBF floating-point format.
Real floating-point type, usually referred to as a double-precision floating-point type. Actual properties unspecified (except minimum limits); however, on most systems, this is the IEEE 754 double-precision binary floating-point format (64 bits). This format is required by the optional Annex F "IEC 60559 floating-point arithmetic".
Concise Binary Object Representation (CBOR) is a binary data serialization format loosely based on JSON authored by Carsten Bormann and Paul Hoffman. [ a ] Like JSON it allows the transmission of data objects that contain name–value pairs , but in a more concise manner.
The Intel C++ compiler on Microsoft Windows supports extended precision, but requires the /Qlong‑double switch for long double to correspond to the hardware's extended precision format. [3] Compilers may also use long double for the IEEE 754 quadruple-precision binary floating-point format (binary128).
^ The current default format is binary. ^ The "classic" format is plain text, and an XML format is also supported. ^ Theoretically possible due to abstraction, but no implementation is included. ^ The primary format is binary, but text and JSON formats are available. [8] [9]
Double-precision binary floating-point is a commonly used format on PCs, due to its wider range over single-precision floating point, in spite of its performance and bandwidth cost. It is commonly known simply as double. The IEEE 754 standard specifies a binary64 as having: Sign bit: 1 bit; Exponent: 11 bits
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. It is intended for storage of floating-point values in applications where higher precision is not essential, in particular image processing and neural networks.
The bfloat16 (brain floating point) [1] [2] floating-point format is a computer number format occupying 16 bits in computer memory; it represents a wide dynamic range of numeric values by using a floating radix point. This format is a shortened (16-bit) version of the 32-bit IEEE 754 single-precision floating-point format (binary32) with the ...