24.777 777 777 784 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 784 9(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
24.777 777 777 784 9(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. First, convert to binary (in base 2) the integer part: 24.
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;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 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.

24(10) =


1 1000(2)


3. Convert to binary (base 2) the fractional part: 0.777 777 777 784 9.

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) 0.777 777 777 784 9 × 2 = 1 + 0.555 555 555 569 8;
  • 2) 0.555 555 555 569 8 × 2 = 1 + 0.111 111 111 139 6;
  • 3) 0.111 111 111 139 6 × 2 = 0 + 0.222 222 222 279 2;
  • 4) 0.222 222 222 279 2 × 2 = 0 + 0.444 444 444 558 4;
  • 5) 0.444 444 444 558 4 × 2 = 0 + 0.888 888 889 116 8;
  • 6) 0.888 888 889 116 8 × 2 = 1 + 0.777 777 778 233 6;
  • 7) 0.777 777 778 233 6 × 2 = 1 + 0.555 555 556 467 2;
  • 8) 0.555 555 556 467 2 × 2 = 1 + 0.111 111 112 934 4;
  • 9) 0.111 111 112 934 4 × 2 = 0 + 0.222 222 225 868 8;
  • 10) 0.222 222 225 868 8 × 2 = 0 + 0.444 444 451 737 6;
  • 11) 0.444 444 451 737 6 × 2 = 0 + 0.888 888 903 475 2;
  • 12) 0.888 888 903 475 2 × 2 = 1 + 0.777 777 806 950 4;
  • 13) 0.777 777 806 950 4 × 2 = 1 + 0.555 555 613 900 8;
  • 14) 0.555 555 613 900 8 × 2 = 1 + 0.111 111 227 801 6;
  • 15) 0.111 111 227 801 6 × 2 = 0 + 0.222 222 455 603 2;
  • 16) 0.222 222 455 603 2 × 2 = 0 + 0.444 444 911 206 4;
  • 17) 0.444 444 911 206 4 × 2 = 0 + 0.888 889 822 412 8;
  • 18) 0.888 889 822 412 8 × 2 = 1 + 0.777 779 644 825 6;
  • 19) 0.777 779 644 825 6 × 2 = 1 + 0.555 559 289 651 2;
  • 20) 0.555 559 289 651 2 × 2 = 1 + 0.111 118 579 302 4;
  • 21) 0.111 118 579 302 4 × 2 = 0 + 0.222 237 158 604 8;
  • 22) 0.222 237 158 604 8 × 2 = 0 + 0.444 474 317 209 6;
  • 23) 0.444 474 317 209 6 × 2 = 0 + 0.888 948 634 419 2;
  • 24) 0.888 948 634 419 2 × 2 = 1 + 0.777 897 268 838 4;
  • 25) 0.777 897 268 838 4 × 2 = 1 + 0.555 794 537 676 8;
  • 26) 0.555 794 537 676 8 × 2 = 1 + 0.111 589 075 353 6;
  • 27) 0.111 589 075 353 6 × 2 = 0 + 0.223 178 150 707 2;
  • 28) 0.223 178 150 707 2 × 2 = 0 + 0.446 356 301 414 4;
  • 29) 0.446 356 301 414 4 × 2 = 0 + 0.892 712 602 828 8;
  • 30) 0.892 712 602 828 8 × 2 = 1 + 0.785 425 205 657 6;
  • 31) 0.785 425 205 657 6 × 2 = 1 + 0.570 850 411 315 2;
  • 32) 0.570 850 411 315 2 × 2 = 1 + 0.141 700 822 630 4;
  • 33) 0.141 700 822 630 4 × 2 = 0 + 0.283 401 645 260 8;
  • 34) 0.283 401 645 260 8 × 2 = 0 + 0.566 803 290 521 6;
  • 35) 0.566 803 290 521 6 × 2 = 1 + 0.133 606 581 043 2;
  • 36) 0.133 606 581 043 2 × 2 = 0 + 0.267 213 162 086 4;
  • 37) 0.267 213 162 086 4 × 2 = 0 + 0.534 426 324 172 8;
  • 38) 0.534 426 324 172 8 × 2 = 1 + 0.068 852 648 345 6;
  • 39) 0.068 852 648 345 6 × 2 = 0 + 0.137 705 296 691 2;
  • 40) 0.137 705 296 691 2 × 2 = 0 + 0.275 410 593 382 4;
  • 41) 0.275 410 593 382 4 × 2 = 0 + 0.550 821 186 764 8;
  • 42) 0.550 821 186 764 8 × 2 = 1 + 0.101 642 373 529 6;
  • 43) 0.101 642 373 529 6 × 2 = 0 + 0.203 284 747 059 2;
  • 44) 0.203 284 747 059 2 × 2 = 0 + 0.406 569 494 118 4;
  • 45) 0.406 569 494 118 4 × 2 = 0 + 0.813 138 988 236 8;
  • 46) 0.813 138 988 236 8 × 2 = 1 + 0.626 277 976 473 6;
  • 47) 0.626 277 976 473 6 × 2 = 1 + 0.252 555 952 947 2;
  • 48) 0.252 555 952 947 2 × 2 = 0 + 0.505 111 905 894 4;
  • 49) 0.505 111 905 894 4 × 2 = 1 + 0.010 223 811 788 8;
  • 50) 0.010 223 811 788 8 × 2 = 0 + 0.020 447 623 577 6;
  • 51) 0.020 447 623 577 6 × 2 = 0 + 0.040 895 247 155 2;
  • 52) 0.040 895 247 155 2 × 2 = 0 + 0.081 790 494 310 4;
  • 53) 0.081 790 494 310 4 × 2 = 0 + 0.163 580 988 620 8;

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:


0.777 777 777 784 9(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110 1000 0(2)

5. Positive number before normalization:

24.777 777 777 784 9(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110 1000 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the left, so that only one non zero digit remains to the left of it:


24.777 777 777 784 9(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110 1000 0(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110 1000 0(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110 1000 0(2) × 24


7. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): 4


Mantissa (not normalized):
1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110 1000 0


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


4 + 2(11-1) - 1 =


(4 + 1 023)(10) =


1 027(10)


9. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 027 ÷ 2 = 513 + 1;
  • 513 ÷ 2 = 256 + 1;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 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) =


1027(10) =


100 0000 0011(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 52 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. 1000 1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110 1 0000 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

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


Exponent (11 bits) =
100 0000 0011


Mantissa (52 bits) =
1000 1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110


Decimal number 24.777 777 777 784 9 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0011 - 1000 1100 0111 0001 1100 0111 0001 1100 0111 0010 0100 0100 0110


How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double 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 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 from the previous 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 multiplying operations, starting from the top of the list constructed 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, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' 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 -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

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

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 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:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. 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) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) 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:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

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

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

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

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100