24.777 777 777 777 777 777 477 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 777 777 777 477(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
24.777 777 777 777 777 777 477(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: 0.777 777 777 777 777 777 477.

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) 0.777 777 777 777 777 777 477 × 2 = 1 + 0.555 555 555 555 555 554 954;
  • 2) 0.555 555 555 555 555 554 954 × 2 = 1 + 0.111 111 111 111 111 109 908;
  • 3) 0.111 111 111 111 111 109 908 × 2 = 0 + 0.222 222 222 222 222 219 816;
  • 4) 0.222 222 222 222 222 219 816 × 2 = 0 + 0.444 444 444 444 444 439 632;
  • 5) 0.444 444 444 444 444 439 632 × 2 = 0 + 0.888 888 888 888 888 879 264;
  • 6) 0.888 888 888 888 888 879 264 × 2 = 1 + 0.777 777 777 777 777 758 528;
  • 7) 0.777 777 777 777 777 758 528 × 2 = 1 + 0.555 555 555 555 555 517 056;
  • 8) 0.555 555 555 555 555 517 056 × 2 = 1 + 0.111 111 111 111 111 034 112;
  • 9) 0.111 111 111 111 111 034 112 × 2 = 0 + 0.222 222 222 222 222 068 224;
  • 10) 0.222 222 222 222 222 068 224 × 2 = 0 + 0.444 444 444 444 444 136 448;
  • 11) 0.444 444 444 444 444 136 448 × 2 = 0 + 0.888 888 888 888 888 272 896;
  • 12) 0.888 888 888 888 888 272 896 × 2 = 1 + 0.777 777 777 777 776 545 792;
  • 13) 0.777 777 777 777 776 545 792 × 2 = 1 + 0.555 555 555 555 553 091 584;
  • 14) 0.555 555 555 555 553 091 584 × 2 = 1 + 0.111 111 111 111 106 183 168;
  • 15) 0.111 111 111 111 106 183 168 × 2 = 0 + 0.222 222 222 222 212 366 336;
  • 16) 0.222 222 222 222 212 366 336 × 2 = 0 + 0.444 444 444 444 424 732 672;
  • 17) 0.444 444 444 444 424 732 672 × 2 = 0 + 0.888 888 888 888 849 465 344;
  • 18) 0.888 888 888 888 849 465 344 × 2 = 1 + 0.777 777 777 777 698 930 688;
  • 19) 0.777 777 777 777 698 930 688 × 2 = 1 + 0.555 555 555 555 397 861 376;
  • 20) 0.555 555 555 555 397 861 376 × 2 = 1 + 0.111 111 111 110 795 722 752;
  • 21) 0.111 111 111 110 795 722 752 × 2 = 0 + 0.222 222 222 221 591 445 504;
  • 22) 0.222 222 222 221 591 445 504 × 2 = 0 + 0.444 444 444 443 182 891 008;
  • 23) 0.444 444 444 443 182 891 008 × 2 = 0 + 0.888 888 888 886 365 782 016;
  • 24) 0.888 888 888 886 365 782 016 × 2 = 1 + 0.777 777 777 772 731 564 032;
  • 25) 0.777 777 777 772 731 564 032 × 2 = 1 + 0.555 555 555 545 463 128 064;
  • 26) 0.555 555 555 545 463 128 064 × 2 = 1 + 0.111 111 111 090 926 256 128;
  • 27) 0.111 111 111 090 926 256 128 × 2 = 0 + 0.222 222 222 181 852 512 256;
  • 28) 0.222 222 222 181 852 512 256 × 2 = 0 + 0.444 444 444 363 705 024 512;
  • 29) 0.444 444 444 363 705 024 512 × 2 = 0 + 0.888 888 888 727 410 049 024;
  • 30) 0.888 888 888 727 410 049 024 × 2 = 1 + 0.777 777 777 454 820 098 048;
  • 31) 0.777 777 777 454 820 098 048 × 2 = 1 + 0.555 555 554 909 640 196 096;
  • 32) 0.555 555 554 909 640 196 096 × 2 = 1 + 0.111 111 109 819 280 392 192;
  • 33) 0.111 111 109 819 280 392 192 × 2 = 0 + 0.222 222 219 638 560 784 384;
  • 34) 0.222 222 219 638 560 784 384 × 2 = 0 + 0.444 444 439 277 121 568 768;
  • 35) 0.444 444 439 277 121 568 768 × 2 = 0 + 0.888 888 878 554 243 137 536;
  • 36) 0.888 888 878 554 243 137 536 × 2 = 1 + 0.777 777 757 108 486 275 072;
  • 37) 0.777 777 757 108 486 275 072 × 2 = 1 + 0.555 555 514 216 972 550 144;
  • 38) 0.555 555 514 216 972 550 144 × 2 = 1 + 0.111 111 028 433 945 100 288;
  • 39) 0.111 111 028 433 945 100 288 × 2 = 0 + 0.222 222 056 867 890 200 576;
  • 40) 0.222 222 056 867 890 200 576 × 2 = 0 + 0.444 444 113 735 780 401 152;
  • 41) 0.444 444 113 735 780 401 152 × 2 = 0 + 0.888 888 227 471 560 802 304;
  • 42) 0.888 888 227 471 560 802 304 × 2 = 1 + 0.777 776 454 943 121 604 608;
  • 43) 0.777 776 454 943 121 604 608 × 2 = 1 + 0.555 552 909 886 243 209 216;
  • 44) 0.555 552 909 886 243 209 216 × 2 = 1 + 0.111 105 819 772 486 418 432;
  • 45) 0.111 105 819 772 486 418 432 × 2 = 0 + 0.222 211 639 544 972 836 864;
  • 46) 0.222 211 639 544 972 836 864 × 2 = 0 + 0.444 423 279 089 945 673 728;
  • 47) 0.444 423 279 089 945 673 728 × 2 = 0 + 0.888 846 558 179 891 347 456;
  • 48) 0.888 846 558 179 891 347 456 × 2 = 1 + 0.777 693 116 359 782 694 912;
  • 49) 0.777 693 116 359 782 694 912 × 2 = 1 + 0.555 386 232 719 565 389 824;
  • 50) 0.555 386 232 719 565 389 824 × 2 = 1 + 0.110 772 465 439 130 779 648;
  • 51) 0.110 772 465 439 130 779 648 × 2 = 0 + 0.221 544 930 878 261 559 296;
  • 52) 0.221 544 930 878 261 559 296 × 2 = 0 + 0.443 089 861 756 523 118 592;
  • 53) 0.443 089 861 756 523 118 592 × 2 = 0 + 0.886 179 723 513 046 237 184;

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:


0.777 777 777 777 777 777 477(10) =


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

5. Positive number before normalization:

24.777 777 777 777 777 777 477(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:


24.777 777 777 777 777 777 477(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 24.777 777 777 777 777 777 477 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