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The Bfloat16 format requires the same amount of memory (16 bits) as the IEEE 754 half-precision format, but allocates 8 bits to the exponent instead of 5, thus providing the same range as a IEEE 754 single-precision number. The tradeoff is a reduced precision, as the trailing significand field is reduced from 10 to 7 bits.
Bfloat16 is designed to maintain the number range from the 32-bit IEEE 754 single-precision floating-point format (binary32), while reducing the precision from 24 bits to 8 bits. This means that the precision is between two and three decimal digits, and bfloat16 can represent finite values up to about 3.4 × 10 38 .
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.
Variable-length arithmetic operations are considerably slower than fixed-length format floating-point instructions. When high performance is not a requirement, but high precision is, variable length arithmetic can prove useful, though the actual accuracy of the result may not be known.
var x1 = 0; // A global variable, because it is not in any function let x2 = 0; // Also global, this time because it is not in any block function f {var z = 'foxes', r = 'birds'; // 2 local variables m = 'fish'; // global, because it wasn't declared anywhere before function child {var r = 'monkeys'; // This variable is local and does not affect the "birds" r of the parent function. z ...
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.
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Negative numbers (s is 1) are encoded as 2's complements. The two encodings in which all non-sign bits are 0 have special interpretations: If the sign bit is 1, the posit value is NaR ("not a real") If the sign bit is 0, the posit value is 0 (which is unsigned and the only value for which the sign function returns 0)