Convert the Number 1 000 000 000 000.2 to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard, From a Base 10 Decimal System Number. Detailed Explanations

Number 1 000 000 000 000.2(10) converted and written in 32 bit single precision IEEE 754 binary floating point representation (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

The first steps we'll go through to make the conversion:

Convert to binary (to base 2) the integer part of the number.

Convert to binary the fractional part of the number.


1. First, convert to binary (in base 2) the integer part: 1 000 000 000 000.
Divide the number repeatedly by 2.

Keep track of each remainder.

We stop when we get a quotient that is equal to zero.


  • division = quotient + remainder;
  • 1 000 000 000 000 ÷ 2 = 500 000 000 000 + 0;
  • 500 000 000 000 ÷ 2 = 250 000 000 000 + 0;
  • 250 000 000 000 ÷ 2 = 125 000 000 000 + 0;
  • 125 000 000 000 ÷ 2 = 62 500 000 000 + 0;
  • 62 500 000 000 ÷ 2 = 31 250 000 000 + 0;
  • 31 250 000 000 ÷ 2 = 15 625 000 000 + 0;
  • 15 625 000 000 ÷ 2 = 7 812 500 000 + 0;
  • 7 812 500 000 ÷ 2 = 3 906 250 000 + 0;
  • 3 906 250 000 ÷ 2 = 1 953 125 000 + 0;
  • 1 953 125 000 ÷ 2 = 976 562 500 + 0;
  • 976 562 500 ÷ 2 = 488 281 250 + 0;
  • 488 281 250 ÷ 2 = 244 140 625 + 0;
  • 244 140 625 ÷ 2 = 122 070 312 + 1;
  • 122 070 312 ÷ 2 = 61 035 156 + 0;
  • 61 035 156 ÷ 2 = 30 517 578 + 0;
  • 30 517 578 ÷ 2 = 15 258 789 + 0;
  • 15 258 789 ÷ 2 = 7 629 394 + 1;
  • 7 629 394 ÷ 2 = 3 814 697 + 0;
  • 3 814 697 ÷ 2 = 1 907 348 + 1;
  • 1 907 348 ÷ 2 = 953 674 + 0;
  • 953 674 ÷ 2 = 476 837 + 0;
  • 476 837 ÷ 2 = 238 418 + 1;
  • 238 418 ÷ 2 = 119 209 + 0;
  • 119 209 ÷ 2 = 59 604 + 1;
  • 59 604 ÷ 2 = 29 802 + 0;
  • 29 802 ÷ 2 = 14 901 + 0;
  • 14 901 ÷ 2 = 7 450 + 1;
  • 7 450 ÷ 2 = 3 725 + 0;
  • 3 725 ÷ 2 = 1 862 + 1;
  • 1 862 ÷ 2 = 931 + 0;
  • 931 ÷ 2 = 465 + 1;
  • 465 ÷ 2 = 232 + 1;
  • 232 ÷ 2 = 116 + 0;
  • 116 ÷ 2 = 58 + 0;
  • 58 ÷ 2 = 29 + 0;
  • 29 ÷ 2 = 14 + 1;
  • 14 ÷ 2 = 7 + 0;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the integer part of the number.

Take all the remainders starting from the bottom of the list constructed above.


1 000 000 000 000(10) =


1110 1000 1101 0100 1010 0101 0001 0000 0000 0000(2)


3. Convert to binary (base 2) the fractional part: 0.2.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.2 × 2 = 0 + 0.4;
  • 2) 0.4 × 2 = 0 + 0.8;
  • 3) 0.8 × 2 = 1 + 0.6;
  • 4) 0.6 × 2 = 1 + 0.2;
  • 5) 0.2 × 2 = 0 + 0.4;
  • 6) 0.4 × 2 = 0 + 0.8;
  • 7) 0.8 × 2 = 1 + 0.6;
  • 8) 0.6 × 2 = 1 + 0.2;
  • 9) 0.2 × 2 = 0 + 0.4;
  • 10) 0.4 × 2 = 0 + 0.8;
  • 11) 0.8 × 2 = 1 + 0.6;
  • 12) 0.6 × 2 = 1 + 0.2;
  • 13) 0.2 × 2 = 0 + 0.4;
  • 14) 0.4 × 2 = 0 + 0.8;
  • 15) 0.8 × 2 = 1 + 0.6;
  • 16) 0.6 × 2 = 1 + 0.2;
  • 17) 0.2 × 2 = 0 + 0.4;
  • 18) 0.4 × 2 = 0 + 0.8;
  • 19) 0.8 × 2 = 1 + 0.6;
  • 20) 0.6 × 2 = 1 + 0.2;
  • 21) 0.2 × 2 = 0 + 0.4;
  • 22) 0.4 × 2 = 0 + 0.8;
  • 23) 0.8 × 2 = 1 + 0.6;
  • 24) 0.6 × 2 = 1 + 0.2;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (losing precision...)


4. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.2(10) =


0.0011 0011 0011 0011 0011 0011(2)


5. Positive number before normalization:

1 000 000 000 000.2(10) =


1110 1000 1101 0100 1010 0101 0001 0000 0000 0000.0011 0011 0011 0011 0011 0011(2)


The last steps we'll go through to make the conversion:

Normalize the binary representation of the number.

Adjust the exponent.

Convert the adjusted exponent from the decimal (base 10) to 8 bit binary.

Normalize the mantissa.


6. Normalize the binary representation of the number.

Shift the decimal mark 39 positions to the left, so that only one non zero digit remains to the left of it:


1 000 000 000 000.2(10) =


1110 1000 1101 0100 1010 0101 0001 0000 0000 0000.0011 0011 0011 0011 0011 0011(2) =


1110 1000 1101 0100 1010 0101 0001 0000 0000 0000.0011 0011 0011 0011 0011 0011(2) × 20 =


1.1101 0001 1010 1001 0100 1010 0010 0000 0000 0000 0110 0110 0110 0110 0110 011(2) × 239


7. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): 39


Mantissa (not normalized):
1.1101 0001 1010 1001 0100 1010 0010 0000 0000 0000 0110 0110 0110 0110 0110 011


8. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(8-1) - 1 =


39 + 2(8-1) - 1 =


(39 + 127)(10) =


166(10)


9. Convert the adjusted exponent from the decimal (base 10) to 8 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 166 ÷ 2 = 83 + 0;
  • 83 ÷ 2 = 41 + 1;
  • 41 ÷ 2 = 20 + 1;
  • 20 ÷ 2 = 10 + 0;
  • 10 ÷ 2 = 5 + 0;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

10. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


166(10) =


1010 0110(2)


11. Normalize the mantissa.

a) Remove the leading (the leftmost) bit, since it's allways 1, and the decimal point, if the case.


b) Adjust its length to 23 bits, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 110 1000 1101 0100 1010 0101 0001 0000 0000 0000 0011 0011 0011 0011 0011 0011 =


110 1000 1101 0100 1010 0101


12. The three elements that make up the number's 32 bit single precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (8 bits) =
1010 0110


Mantissa (23 bits) =
110 1000 1101 0100 1010 0101


The base ten decimal number 1 000 000 000 000.2 converted and written in 32 bit single precision IEEE 754 binary floating point representation:
0 - 1010 0110 - 110 1000 1101 0100 1010 0101

(32 bits IEEE 754)

Number 1 000 000 000 000.1 converted from decimal system (base 10) to 32 bit single precision IEEE 754 binary floating point representation = ?

Number 1 000 000 000 000.3 converted from decimal system (base 10) to 32 bit single precision IEEE 754 binary floating point representation = ?

Convert to 32 bit single precision IEEE 754 binary floating point representation standard

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Example: convert the negative number -25.347 from decimal system (base ten) to 32 bit single precision IEEE 754 binary floating point:

Available Base Conversions Between Decimal and Binary Systems

Conversions Between Decimal System Numbers (Written in Base Ten) and Binary System Numbers (Base Two and Computer Representation):


1. Integer -> Binary

2. Decimal -> Binary

3. Binary -> Integer

4. Binary -> Decimal