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In computer science, type conversion, [1] [2] type casting, [1] [3] type coercion, [3] and type juggling [4] [5] are different ways of changing an expression from one data type to another. An example would be the conversion of an integer value into a floating point value or its textual representation as a string, and vice versa.
Integer addition, for example, can be performed as a single machine instruction, and some offer specific instructions to process sequences of characters with a single instruction. [7] But the choice of primitive data type may affect performance, for example it is faster using SIMD operations and data types to operate on an array of floats.
Information about the actual properties, such as size, of the basic arithmetic types, is provided via macro constants in two headers: <limits.h> header (climits header in C++) defines macros for integer types and <float.h> header (cfloat header in C++) defines macros for floating-point types. The actual values depend on the implementation.
Computers typically use binary arithmetic, but to make the example easier to read, it will be given in decimal. Suppose we are using six-digit decimal floating-point arithmetic, sum has attained the value 10000.0, and the next two values of input[i] are 3.14159 and 2.71828. The exact result is 10005.85987, which rounds to 10005.9.
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.
The type-generic macros that correspond to a function that is defined for only real numbers encapsulates a total of 3 different functions: float, double and long double variants of the function. The C++ language includes native support for function overloading and thus does not provide the <tgmath.h> header even as a compatibility feature.
The above describes an example 8-bit float with 1 sign bit, 4 exponent bits, and 3 significand bits, which is a nice balance. However, any bit allocation is possible. A format could choose to give more of the bits to the exponent if they need more dynamic range with less precision, or give more of the bits to the significand if they need more ...
The most common use case is the conversion between IEEE 754 binary32 and bfloat16. The following section describes the conversion process and its rounding scheme in the conversion. Note that there are other possible scenarios of format conversions to or from bfloat16. For example, int16 and bfloat16. From binary32 to bfloat16.