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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 .
In computer architecture, 16-bit integers, memory addresses, or other data units are those that are 16 bits (2 octets) wide.Also, 16-bit central processing unit (CPU) and arithmetic logic unit (ALU) architectures are those that are based on registers, address buses, or data buses of that size. 16-bit microcomputers are microcomputers that use 16-bit microprocessors.
0 11111110 11111111111111111111111 2 = 7f7f ffff 16 = 2 127 × (2 − 2 −23) ≈ 3.4028234664 × 10 38 (largest normal number) 0 01111110 11111111111111111111111 2 = 3f7f ffff 16 = 1 − 2 −24 ≈ 0.999999940395355225 (largest number less than one) 0 01111111 00000000000000000000000 2 = 3f80 0000 16 = 1 (one)
For example, if there is no representable number lying between the representable numbers 1.45a70c22 hex and 1.45a70c24 hex, the ULP is 2×16 −8, or 2 −31. For numbers with a base-2 exponent part of 0, i.e. numbers with an absolute value higher than or equal to 1 but lower than 2, an ULP is exactly 2 −23 or about 10 −7 in single ...
For example, while a fixed-point representation that allocates 8 decimal digits and 2 decimal places can represent the numbers 123456.78, 8765.43, 123.00, and so on, a floating-point representation with 8 decimal digits could also represent 1.2345678, 1234567.8, 0.000012345678, 12345678000000000, and so on.
That is, the value of an octal "10" is the same as a decimal "8", an octal "20" is a decimal "16", and so on. In a hexadecimal system, there are 16 digits, 0 through 9 followed, by convention, with A through F. That is, a hexadecimal "10" is the same as a decimal "16" and a hexadecimal "20" is the same as a decimal "32".
A fixed-point representation of a fractional number is essentially an integer that is to be implicitly multiplied by a fixed scaling factor. For example, the value 1.23 can be stored in a variable as the integer value 1230 with implicit scaling factor of 1/1000 (meaning that the last 3 decimal digits are implicitly assumed to be a decimal fraction), and the value 1 230 000 can be represented ...
Both alternatives provide exactly the same set of representable numbers: 16 digits of significand and 3 × 2 8 = 768 possible decimal exponent values. (All the possible decimal exponent values storable in a binary64 number are representable in decimal64, and most bits of the significand of a binary64 are stored keeping roughly the same number ...