-24.901 899 999 999 997 685 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -24.901 899 999 999 997 685(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
-24.901 899 999 999 997 685(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. Start with the positive version of the number:

|-24.901 899 999 999 997 685| = 24.901 899 999 999 997 685


2. 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;

3. 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)


4. Convert to binary (base 2) the fractional part: 0.901 899 999 999 997 685.

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) 0.901 899 999 999 997 685 × 2 = 1 + 0.803 799 999 999 995 37;
  • 2) 0.803 799 999 999 995 37 × 2 = 1 + 0.607 599 999 999 990 74;
  • 3) 0.607 599 999 999 990 74 × 2 = 1 + 0.215 199 999 999 981 48;
  • 4) 0.215 199 999 999 981 48 × 2 = 0 + 0.430 399 999 999 962 96;
  • 5) 0.430 399 999 999 962 96 × 2 = 0 + 0.860 799 999 999 925 92;
  • 6) 0.860 799 999 999 925 92 × 2 = 1 + 0.721 599 999 999 851 84;
  • 7) 0.721 599 999 999 851 84 × 2 = 1 + 0.443 199 999 999 703 68;
  • 8) 0.443 199 999 999 703 68 × 2 = 0 + 0.886 399 999 999 407 36;
  • 9) 0.886 399 999 999 407 36 × 2 = 1 + 0.772 799 999 998 814 72;
  • 10) 0.772 799 999 998 814 72 × 2 = 1 + 0.545 599 999 997 629 44;
  • 11) 0.545 599 999 997 629 44 × 2 = 1 + 0.091 199 999 995 258 88;
  • 12) 0.091 199 999 995 258 88 × 2 = 0 + 0.182 399 999 990 517 76;
  • 13) 0.182 399 999 990 517 76 × 2 = 0 + 0.364 799 999 981 035 52;
  • 14) 0.364 799 999 981 035 52 × 2 = 0 + 0.729 599 999 962 071 04;
  • 15) 0.729 599 999 962 071 04 × 2 = 1 + 0.459 199 999 924 142 08;
  • 16) 0.459 199 999 924 142 08 × 2 = 0 + 0.918 399 999 848 284 16;
  • 17) 0.918 399 999 848 284 16 × 2 = 1 + 0.836 799 999 696 568 32;
  • 18) 0.836 799 999 696 568 32 × 2 = 1 + 0.673 599 999 393 136 64;
  • 19) 0.673 599 999 393 136 64 × 2 = 1 + 0.347 199 998 786 273 28;
  • 20) 0.347 199 998 786 273 28 × 2 = 0 + 0.694 399 997 572 546 56;
  • 21) 0.694 399 997 572 546 56 × 2 = 1 + 0.388 799 995 145 093 12;
  • 22) 0.388 799 995 145 093 12 × 2 = 0 + 0.777 599 990 290 186 24;
  • 23) 0.777 599 990 290 186 24 × 2 = 1 + 0.555 199 980 580 372 48;
  • 24) 0.555 199 980 580 372 48 × 2 = 1 + 0.110 399 961 160 744 96;
  • 25) 0.110 399 961 160 744 96 × 2 = 0 + 0.220 799 922 321 489 92;
  • 26) 0.220 799 922 321 489 92 × 2 = 0 + 0.441 599 844 642 979 84;
  • 27) 0.441 599 844 642 979 84 × 2 = 0 + 0.883 199 689 285 959 68;
  • 28) 0.883 199 689 285 959 68 × 2 = 1 + 0.766 399 378 571 919 36;
  • 29) 0.766 399 378 571 919 36 × 2 = 1 + 0.532 798 757 143 838 72;
  • 30) 0.532 798 757 143 838 72 × 2 = 1 + 0.065 597 514 287 677 44;
  • 31) 0.065 597 514 287 677 44 × 2 = 0 + 0.131 195 028 575 354 88;
  • 32) 0.131 195 028 575 354 88 × 2 = 0 + 0.262 390 057 150 709 76;
  • 33) 0.262 390 057 150 709 76 × 2 = 0 + 0.524 780 114 301 419 52;
  • 34) 0.524 780 114 301 419 52 × 2 = 1 + 0.049 560 228 602 839 04;
  • 35) 0.049 560 228 602 839 04 × 2 = 0 + 0.099 120 457 205 678 08;
  • 36) 0.099 120 457 205 678 08 × 2 = 0 + 0.198 240 914 411 356 16;
  • 37) 0.198 240 914 411 356 16 × 2 = 0 + 0.396 481 828 822 712 32;
  • 38) 0.396 481 828 822 712 32 × 2 = 0 + 0.792 963 657 645 424 64;
  • 39) 0.792 963 657 645 424 64 × 2 = 1 + 0.585 927 315 290 849 28;
  • 40) 0.585 927 315 290 849 28 × 2 = 1 + 0.171 854 630 581 698 56;
  • 41) 0.171 854 630 581 698 56 × 2 = 0 + 0.343 709 261 163 397 12;
  • 42) 0.343 709 261 163 397 12 × 2 = 0 + 0.687 418 522 326 794 24;
  • 43) 0.687 418 522 326 794 24 × 2 = 1 + 0.374 837 044 653 588 48;
  • 44) 0.374 837 044 653 588 48 × 2 = 0 + 0.749 674 089 307 176 96;
  • 45) 0.749 674 089 307 176 96 × 2 = 1 + 0.499 348 178 614 353 92;
  • 46) 0.499 348 178 614 353 92 × 2 = 0 + 0.998 696 357 228 707 84;
  • 47) 0.998 696 357 228 707 84 × 2 = 1 + 0.997 392 714 457 415 68;
  • 48) 0.997 392 714 457 415 68 × 2 = 1 + 0.994 785 428 914 831 36;
  • 49) 0.994 785 428 914 831 36 × 2 = 1 + 0.989 570 857 829 662 72;
  • 50) 0.989 570 857 829 662 72 × 2 = 1 + 0.979 141 715 659 325 44;
  • 51) 0.979 141 715 659 325 44 × 2 = 1 + 0.958 283 431 318 650 88;
  • 52) 0.958 283 431 318 650 88 × 2 = 1 + 0.916 566 862 637 301 76;
  • 53) 0.916 566 862 637 301 76 × 2 = 1 + 0.833 133 725 274 603 52;

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).


5. 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:


0.901 899 999 999 997 685(10) =


0.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011 1111 1(2)

6. Positive number before normalization:

24.901 899 999 999 997 685(10) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011 1111 1(2)

7. 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:


24.901 899 999 999 997 685(10) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011 1111 1(2) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011 1111 1(2) × 20 =


1.1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011 1111 1(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):
1.1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011 1111 1


9. 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)


10. 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;

11. 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)


12. 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 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011 1 1111 =


1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011


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

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


Exponent (11 bits) =
100 0000 0011


Mantissa (52 bits) =
1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011


Decimal number -24.901 899 999 999 997 685 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0011 - 1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1011


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