1.400 000 000 000 000 000 000 000 000 000 71 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.400 000 000 000 000 000 000 000 000 000 71(10) to 32 bit single precision IEEE 754 binary floating point representation standard (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

What are the steps to convert decimal number
1.400 000 000 000 000 000 000 000 000 000 71(10) to 32 bit single precision IEEE 754 binary floating point representation (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

1. First, convert to binary (in base 2) the integer part: 1.
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 ÷ 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(10) =


1(2)


3. Convert to binary (base 2) the fractional part: 0.400 000 000 000 000 000 000 000 000 000 71.

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) 0.400 000 000 000 000 000 000 000 000 000 71 × 2 = 0 + 0.800 000 000 000 000 000 000 000 000 001 42;
  • 2) 0.800 000 000 000 000 000 000 000 000 001 42 × 2 = 1 + 0.600 000 000 000 000 000 000 000 000 002 84;
  • 3) 0.600 000 000 000 000 000 000 000 000 002 84 × 2 = 1 + 0.200 000 000 000 000 000 000 000 000 005 68;
  • 4) 0.200 000 000 000 000 000 000 000 000 005 68 × 2 = 0 + 0.400 000 000 000 000 000 000 000 000 011 36;
  • 5) 0.400 000 000 000 000 000 000 000 000 011 36 × 2 = 0 + 0.800 000 000 000 000 000 000 000 000 022 72;
  • 6) 0.800 000 000 000 000 000 000 000 000 022 72 × 2 = 1 + 0.600 000 000 000 000 000 000 000 000 045 44;
  • 7) 0.600 000 000 000 000 000 000 000 000 045 44 × 2 = 1 + 0.200 000 000 000 000 000 000 000 000 090 88;
  • 8) 0.200 000 000 000 000 000 000 000 000 090 88 × 2 = 0 + 0.400 000 000 000 000 000 000 000 000 181 76;
  • 9) 0.400 000 000 000 000 000 000 000 000 181 76 × 2 = 0 + 0.800 000 000 000 000 000 000 000 000 363 52;
  • 10) 0.800 000 000 000 000 000 000 000 000 363 52 × 2 = 1 + 0.600 000 000 000 000 000 000 000 000 727 04;
  • 11) 0.600 000 000 000 000 000 000 000 000 727 04 × 2 = 1 + 0.200 000 000 000 000 000 000 000 001 454 08;
  • 12) 0.200 000 000 000 000 000 000 000 001 454 08 × 2 = 0 + 0.400 000 000 000 000 000 000 000 002 908 16;
  • 13) 0.400 000 000 000 000 000 000 000 002 908 16 × 2 = 0 + 0.800 000 000 000 000 000 000 000 005 816 32;
  • 14) 0.800 000 000 000 000 000 000 000 005 816 32 × 2 = 1 + 0.600 000 000 000 000 000 000 000 011 632 64;
  • 15) 0.600 000 000 000 000 000 000 000 011 632 64 × 2 = 1 + 0.200 000 000 000 000 000 000 000 023 265 28;
  • 16) 0.200 000 000 000 000 000 000 000 023 265 28 × 2 = 0 + 0.400 000 000 000 000 000 000 000 046 530 56;
  • 17) 0.400 000 000 000 000 000 000 000 046 530 56 × 2 = 0 + 0.800 000 000 000 000 000 000 000 093 061 12;
  • 18) 0.800 000 000 000 000 000 000 000 093 061 12 × 2 = 1 + 0.600 000 000 000 000 000 000 000 186 122 24;
  • 19) 0.600 000 000 000 000 000 000 000 186 122 24 × 2 = 1 + 0.200 000 000 000 000 000 000 000 372 244 48;
  • 20) 0.200 000 000 000 000 000 000 000 372 244 48 × 2 = 0 + 0.400 000 000 000 000 000 000 000 744 488 96;
  • 21) 0.400 000 000 000 000 000 000 000 744 488 96 × 2 = 0 + 0.800 000 000 000 000 000 000 001 488 977 92;
  • 22) 0.800 000 000 000 000 000 000 001 488 977 92 × 2 = 1 + 0.600 000 000 000 000 000 000 002 977 955 84;
  • 23) 0.600 000 000 000 000 000 000 002 977 955 84 × 2 = 1 + 0.200 000 000 000 000 000 000 005 955 911 68;
  • 24) 0.200 000 000 000 000 000 000 005 955 911 68 × 2 = 0 + 0.400 000 000 000 000 000 000 011 911 823 36;

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 - the converted number we get in the end will be just a very good approximation of the initial one).


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:


0.400 000 000 000 000 000 000 000 000 000 71(10) =


0.0110 0110 0110 0110 0110 0110(2)

5. Positive number before normalization:

1.400 000 000 000 000 000 000 000 000 000 71(10) =


1.0110 0110 0110 0110 0110 0110(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 0 positions to the left, so that only one non zero digit remains to the left of it:


1.400 000 000 000 000 000 000 000 000 000 71(10) =


1.0110 0110 0110 0110 0110 0110(2) =


1.0110 0110 0110 0110 0110 0110(2) × 20


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): 0


Mantissa (not normalized):
1.0110 0110 0110 0110 0110 0110


8. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


0 + 2(8-1) - 1 =


(0 + 127)(10) =


127(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;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


127(10) =


0111 1111(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. 011 0011 0011 0011 0011 0011 0 =


011 0011 0011 0011 0011 0011


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) =
0111 1111


Mantissa (23 bits) =
011 0011 0011 0011 0011 0011


Decimal number 1.400 000 000 000 000 000 000 000 000 000 71 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 0111 1111 - 011 0011 0011 0011 0011 0011


How to convert decimal numbers from base ten to 32 bit single precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 32 bit single precision IEEE 754 binary floating point:

  • 1. If the number to be converted is negative, start with its the positive version.
  • 2. First convert the integer part. Divide repeatedly by 2 the base ten positive representation of the integer number that is to be converted to binary, until we get a quotient that is equal to zero, keeping track of each remainder.
  • 3. Construct the base 2 representation of the positive integer part of the number, by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above. Thus, the last remainder of the divisions becomes the first symbol (the leftmost) of the base two number, while the first remainder becomes the last symbol (the rightmost).
  • 4. Then convert the fractional part. Multiply the number repeatedly by 2, until we get a fractional part that is equal to zero, keeping track of each integer part of the results.
  • 5. Construct the base 2 representation of the fractional part of the number by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above (they should appear in the binary representation, from left to right, in the order they have been calculated).
  • 6. Normalize the binary representation of the number, by shifting the decimal point (or if you prefer, the decimal mark) "n" positions either to the left or to the right, so that only one non zero digit remains to the left of the decimal point.
  • 7. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign if the case) and adjust its length to 23 bits, either by removing the excess bits from the right (losing precision...) or by adding extra '0' bits to the right.
  • 9. Sign (it takes 1 bit) is either 1 for a negative or 0 for a positive number.

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

  • 1. Start with the positive version of the number:

    |-25.347| = 25.347

  • 2. First convert the integer part, 25. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 25 ÷ 2 = 12 + 1;
    • 12 ÷ 2 = 6 + 0;
    • 6 ÷ 2 = 3 + 0;
    • 3 ÷ 2 = 1 + 1;
    • 1 ÷ 2 = 0 + 1;
    • We have encountered a quotient that is ZERO => FULL STOP
  • 3. Construct the base 2 representation of the integer part of the number by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above:

    25(10) = 1 1001(2)

  • 4. Then convert the fractional part, 0.347. Multiply repeatedly by 2, keeping track of each integer part of the results, until we get a fractional part that is equal to zero:
    • #) multiplying = integer + fractional part;
    • 1) 0.347 × 2 = 0 + 0.694;
    • 2) 0.694 × 2 = 1 + 0.388;
    • 3) 0.388 × 2 = 0 + 0.776;
    • 4) 0.776 × 2 = 1 + 0.552;
    • 5) 0.552 × 2 = 1 + 0.104;
    • 6) 0.104 × 2 = 0 + 0.208;
    • 7) 0.208 × 2 = 0 + 0.416;
    • 8) 0.416 × 2 = 0 + 0.832;
    • 9) 0.832 × 2 = 1 + 0.664;
    • 10) 0.664 × 2 = 1 + 0.328;
    • 11) 0.328 × 2 = 0 + 0.656;
    • 12) 0.656 × 2 = 1 + 0.312;
    • 13) 0.312 × 2 = 0 + 0.624;
    • 14) 0.624 × 2 = 1 + 0.248;
    • 15) 0.248 × 2 = 0 + 0.496;
    • 16) 0.496 × 2 = 0 + 0.992;
    • 17) 0.992 × 2 = 1 + 0.984;
    • 18) 0.984 × 2 = 1 + 0.968;
    • 19) 0.968 × 2 = 1 + 0.936;
    • 20) 0.936 × 2 = 1 + 0.872;
    • 21) 0.872 × 2 = 1 + 0.744;
    • 22) 0.744 × 2 = 1 + 0.488;
    • 23) 0.488 × 2 = 0 + 0.976;
    • 24) 0.976 × 2 = 1 + 0.952;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 23) and at least one integer part that was different from zero => FULL STOP (losing precision...).
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above:

    0.347(10) = 0.0101 1000 1101 0100 1111 1101(2)

  • 6. Summarizing - the positive number before normalization:

    25.347(10) = 1 1001.0101 1000 1101 0100 1111 1101(2)

  • 7. Normalize the binary representation of the number, shifting the decimal point 4 positions to the left so that only one non-zero digit stays to the left of the decimal point:

    25.347(10) =
    1 1001.0101 1000 1101 0100 1111 1101(2) =
    1 1001.0101 1000 1101 0100 1111 1101(2) × 20 =
    1.1001 0101 1000 1101 0100 1111 1101(2) × 24

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

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

  • 9. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as already demonstrated above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1 = (4 + 127)(10) = 131(10) =
    1000 0011(2)

  • 10. Normalize the mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal point) and adjust its length to 23 bits, by removing the excess bits from the right (losing precision...):

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

    Mantissa (normalized): 100 1010 1100 0110 1010 0111

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 1000 0011

    Mantissa (23 bits) = 100 1010 1100 0110 1010 0111

  • Number -25.347, converted from the decimal system (base 10) to 32 bit single precision IEEE 754 binary floating point =
    1 - 1000 0011 - 100 1010 1100 0110 1010 0111