24.777 777 777 777 777 740 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 777 777 740 2(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
24.777 777 777 777 777 740 2(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: 0.777 777 777 777 777 740 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) 0.777 777 777 777 777 740 2 × 2 = 1 + 0.555 555 555 555 555 480 4;
  • 2) 0.555 555 555 555 555 480 4 × 2 = 1 + 0.111 111 111 111 110 960 8;
  • 3) 0.111 111 111 111 110 960 8 × 2 = 0 + 0.222 222 222 222 221 921 6;
  • 4) 0.222 222 222 222 221 921 6 × 2 = 0 + 0.444 444 444 444 443 843 2;
  • 5) 0.444 444 444 444 443 843 2 × 2 = 0 + 0.888 888 888 888 887 686 4;
  • 6) 0.888 888 888 888 887 686 4 × 2 = 1 + 0.777 777 777 777 775 372 8;
  • 7) 0.777 777 777 777 775 372 8 × 2 = 1 + 0.555 555 555 555 550 745 6;
  • 8) 0.555 555 555 555 550 745 6 × 2 = 1 + 0.111 111 111 111 101 491 2;
  • 9) 0.111 111 111 111 101 491 2 × 2 = 0 + 0.222 222 222 222 202 982 4;
  • 10) 0.222 222 222 222 202 982 4 × 2 = 0 + 0.444 444 444 444 405 964 8;
  • 11) 0.444 444 444 444 405 964 8 × 2 = 0 + 0.888 888 888 888 811 929 6;
  • 12) 0.888 888 888 888 811 929 6 × 2 = 1 + 0.777 777 777 777 623 859 2;
  • 13) 0.777 777 777 777 623 859 2 × 2 = 1 + 0.555 555 555 555 247 718 4;
  • 14) 0.555 555 555 555 247 718 4 × 2 = 1 + 0.111 111 111 110 495 436 8;
  • 15) 0.111 111 111 110 495 436 8 × 2 = 0 + 0.222 222 222 220 990 873 6;
  • 16) 0.222 222 222 220 990 873 6 × 2 = 0 + 0.444 444 444 441 981 747 2;
  • 17) 0.444 444 444 441 981 747 2 × 2 = 0 + 0.888 888 888 883 963 494 4;
  • 18) 0.888 888 888 883 963 494 4 × 2 = 1 + 0.777 777 777 767 926 988 8;
  • 19) 0.777 777 777 767 926 988 8 × 2 = 1 + 0.555 555 555 535 853 977 6;
  • 20) 0.555 555 555 535 853 977 6 × 2 = 1 + 0.111 111 111 071 707 955 2;
  • 21) 0.111 111 111 071 707 955 2 × 2 = 0 + 0.222 222 222 143 415 910 4;
  • 22) 0.222 222 222 143 415 910 4 × 2 = 0 + 0.444 444 444 286 831 820 8;
  • 23) 0.444 444 444 286 831 820 8 × 2 = 0 + 0.888 888 888 573 663 641 6;
  • 24) 0.888 888 888 573 663 641 6 × 2 = 1 + 0.777 777 777 147 327 283 2;
  • 25) 0.777 777 777 147 327 283 2 × 2 = 1 + 0.555 555 554 294 654 566 4;
  • 26) 0.555 555 554 294 654 566 4 × 2 = 1 + 0.111 111 108 589 309 132 8;
  • 27) 0.111 111 108 589 309 132 8 × 2 = 0 + 0.222 222 217 178 618 265 6;
  • 28) 0.222 222 217 178 618 265 6 × 2 = 0 + 0.444 444 434 357 236 531 2;
  • 29) 0.444 444 434 357 236 531 2 × 2 = 0 + 0.888 888 868 714 473 062 4;
  • 30) 0.888 888 868 714 473 062 4 × 2 = 1 + 0.777 777 737 428 946 124 8;
  • 31) 0.777 777 737 428 946 124 8 × 2 = 1 + 0.555 555 474 857 892 249 6;
  • 32) 0.555 555 474 857 892 249 6 × 2 = 1 + 0.111 110 949 715 784 499 2;
  • 33) 0.111 110 949 715 784 499 2 × 2 = 0 + 0.222 221 899 431 568 998 4;
  • 34) 0.222 221 899 431 568 998 4 × 2 = 0 + 0.444 443 798 863 137 996 8;
  • 35) 0.444 443 798 863 137 996 8 × 2 = 0 + 0.888 887 597 726 275 993 6;
  • 36) 0.888 887 597 726 275 993 6 × 2 = 1 + 0.777 775 195 452 551 987 2;
  • 37) 0.777 775 195 452 551 987 2 × 2 = 1 + 0.555 550 390 905 103 974 4;
  • 38) 0.555 550 390 905 103 974 4 × 2 = 1 + 0.111 100 781 810 207 948 8;
  • 39) 0.111 100 781 810 207 948 8 × 2 = 0 + 0.222 201 563 620 415 897 6;
  • 40) 0.222 201 563 620 415 897 6 × 2 = 0 + 0.444 403 127 240 831 795 2;
  • 41) 0.444 403 127 240 831 795 2 × 2 = 0 + 0.888 806 254 481 663 590 4;
  • 42) 0.888 806 254 481 663 590 4 × 2 = 1 + 0.777 612 508 963 327 180 8;
  • 43) 0.777 612 508 963 327 180 8 × 2 = 1 + 0.555 225 017 926 654 361 6;
  • 44) 0.555 225 017 926 654 361 6 × 2 = 1 + 0.110 450 035 853 308 723 2;
  • 45) 0.110 450 035 853 308 723 2 × 2 = 0 + 0.220 900 071 706 617 446 4;
  • 46) 0.220 900 071 706 617 446 4 × 2 = 0 + 0.441 800 143 413 234 892 8;
  • 47) 0.441 800 143 413 234 892 8 × 2 = 0 + 0.883 600 286 826 469 785 6;
  • 48) 0.883 600 286 826 469 785 6 × 2 = 1 + 0.767 200 573 652 939 571 2;
  • 49) 0.767 200 573 652 939 571 2 × 2 = 1 + 0.534 401 147 305 879 142 4;
  • 50) 0.534 401 147 305 879 142 4 × 2 = 1 + 0.068 802 294 611 758 284 8;
  • 51) 0.068 802 294 611 758 284 8 × 2 = 0 + 0.137 604 589 223 516 569 6;
  • 52) 0.137 604 589 223 516 569 6 × 2 = 0 + 0.275 209 178 447 033 139 2;
  • 53) 0.275 209 178 447 033 139 2 × 2 = 0 + 0.550 418 356 894 066 278 4;

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:


0.777 777 777 777 777 740 2(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0(2)

5. Positive number before normalization:

24.777 777 777 777 777 740 2(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 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:


24.777 777 777 777 777 740 2(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 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 0001 1100 0111 0001 1100 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 0001 1100 0111 0001 1 1000 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0001


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 0001 1100 0111 0001


Decimal number 24.777 777 777 777 777 740 2 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 0001 1100 0111 0001


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