11 000 000 100 009 631 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 11 000 000 100 009 631(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
11 000 000 100 009 631(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. 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;
  • 11 000 000 100 009 631 ÷ 2 = 5 500 000 050 004 815 + 1;
  • 5 500 000 050 004 815 ÷ 2 = 2 750 000 025 002 407 + 1;
  • 2 750 000 025 002 407 ÷ 2 = 1 375 000 012 501 203 + 1;
  • 1 375 000 012 501 203 ÷ 2 = 687 500 006 250 601 + 1;
  • 687 500 006 250 601 ÷ 2 = 343 750 003 125 300 + 1;
  • 343 750 003 125 300 ÷ 2 = 171 875 001 562 650 + 0;
  • 171 875 001 562 650 ÷ 2 = 85 937 500 781 325 + 0;
  • 85 937 500 781 325 ÷ 2 = 42 968 750 390 662 + 1;
  • 42 968 750 390 662 ÷ 2 = 21 484 375 195 331 + 0;
  • 21 484 375 195 331 ÷ 2 = 10 742 187 597 665 + 1;
  • 10 742 187 597 665 ÷ 2 = 5 371 093 798 832 + 1;
  • 5 371 093 798 832 ÷ 2 = 2 685 546 899 416 + 0;
  • 2 685 546 899 416 ÷ 2 = 1 342 773 449 708 + 0;
  • 1 342 773 449 708 ÷ 2 = 671 386 724 854 + 0;
  • 671 386 724 854 ÷ 2 = 335 693 362 427 + 0;
  • 335 693 362 427 ÷ 2 = 167 846 681 213 + 1;
  • 167 846 681 213 ÷ 2 = 83 923 340 606 + 1;
  • 83 923 340 606 ÷ 2 = 41 961 670 303 + 0;
  • 41 961 670 303 ÷ 2 = 20 980 835 151 + 1;
  • 20 980 835 151 ÷ 2 = 10 490 417 575 + 1;
  • 10 490 417 575 ÷ 2 = 5 245 208 787 + 1;
  • 5 245 208 787 ÷ 2 = 2 622 604 393 + 1;
  • 2 622 604 393 ÷ 2 = 1 311 302 196 + 1;
  • 1 311 302 196 ÷ 2 = 655 651 098 + 0;
  • 655 651 098 ÷ 2 = 327 825 549 + 0;
  • 327 825 549 ÷ 2 = 163 912 774 + 1;
  • 163 912 774 ÷ 2 = 81 956 387 + 0;
  • 81 956 387 ÷ 2 = 40 978 193 + 1;
  • 40 978 193 ÷ 2 = 20 489 096 + 1;
  • 20 489 096 ÷ 2 = 10 244 548 + 0;
  • 10 244 548 ÷ 2 = 5 122 274 + 0;
  • 5 122 274 ÷ 2 = 2 561 137 + 0;
  • 2 561 137 ÷ 2 = 1 280 568 + 1;
  • 1 280 568 ÷ 2 = 640 284 + 0;
  • 640 284 ÷ 2 = 320 142 + 0;
  • 320 142 ÷ 2 = 160 071 + 0;
  • 160 071 ÷ 2 = 80 035 + 1;
  • 80 035 ÷ 2 = 40 017 + 1;
  • 40 017 ÷ 2 = 20 008 + 1;
  • 20 008 ÷ 2 = 10 004 + 0;
  • 10 004 ÷ 2 = 5 002 + 0;
  • 5 002 ÷ 2 = 2 501 + 0;
  • 2 501 ÷ 2 = 1 250 + 1;
  • 1 250 ÷ 2 = 625 + 0;
  • 625 ÷ 2 = 312 + 1;
  • 312 ÷ 2 = 156 + 0;
  • 156 ÷ 2 = 78 + 0;
  • 78 ÷ 2 = 39 + 0;
  • 39 ÷ 2 = 19 + 1;
  • 19 ÷ 2 = 9 + 1;
  • 9 ÷ 2 = 4 + 1;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the positive number.

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

11 000 000 100 009 631(10) =


10 0111 0001 0100 0111 0001 0001 1010 0111 1101 1000 0110 1001 1111(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 53 positions to the left, so that only one non zero digit remains to the left of it:


11 000 000 100 009 631(10) =


10 0111 0001 0100 0111 0001 0001 1010 0111 1101 1000 0110 1001 1111(2) =


10 0111 0001 0100 0111 0001 0001 1010 0111 1101 1000 0110 1001 1111(2) × 20 =


1.0011 1000 1010 0011 1000 1000 1101 0011 1110 1100 0011 0100 1111 1(2) × 253


4. 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): 53


Mantissa (not normalized):
1.0011 1000 1010 0011 1000 1000 1101 0011 1110 1100 0011 0100 1111 1


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


53 + 2(8-1) - 1 =


(53 + 127)(10) =


180(10)


6. 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;
  • 180 ÷ 2 = 90 + 0;
  • 90 ÷ 2 = 45 + 0;
  • 45 ÷ 2 = 22 + 1;
  • 22 ÷ 2 = 11 + 0;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


180(10) =


1011 0100(2)


8. 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. 001 1100 0101 0001 1100 0100 01 1010 0111 1101 1000 0110 1001 1111 =


001 1100 0101 0001 1100 0100


9. 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) =
1011 0100


Mantissa (23 bits) =
001 1100 0101 0001 1100 0100


Decimal number 11 000 000 100 009 631 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 0100 - 001 1100 0101 0001 1100 0100


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