IEEE 754 Floating point is the most common representation used to store real numbers in a computer.
Index
1. What are floating point numbers
2. How to represent a floating point number.
a. Single and Double precisions
3.Data ranges
What are floating point number:
The term ‘floating point’ refers to the decimal point (or) binary point in a real number.
The decimal point placed in between group of digits is called floating point numbers.
Ex: 28.36, 0.00124
Floating point number representation IEEE 754 standard:
Floating point number contains three components
1. Sign bit - Represents the sign of floating point number.
2. Exponent - Represents the magnitude of the exponent (explained at later part) (Ex: 1.086 * 10^6)
3. Mantissa - Represents the precision bits of the number. (Ex: 1.086 * 10^6)
Single precision floating point representation (32-bit):
Fig 1: SP floating point representation
S = 1bit; E = 8 bit - Min = 126, Max = 127, Bias = 127; M = 23bits.
31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0
S ------ E-8bit------ -----------------------------M-23bit-------------------
Double precision floating point representation (64-bit):
Fig 2: DP floating point representation
S = 1bit; E = 12 bit - Min = 1022, Max = 1023, Bias = 1023; M = 23bits.Normalized floating point representation:
Components of a floating point representation
In general to maximize the representable numbers, FP numbers are typically stored in ‘normalized’ form. This puts a radix point after a non-zero digit. Fig 1 & 2 are normalized representation of floating point (FP) numbers.
In order to represent in more optimized way number is represented with base 2, since only non-zero value possible is 1, this is implicitly stored.
Demoralized floating point representation:
Ranges of floating point numbers:
Introduction to fp representation - part II
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