-0.008 788 423 613 44 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.008 788 423 613 44(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
-0.008 788 423 613 44(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:

|-0.008 788 423 613 44| = 0.008 788 423 613 44


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

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.

0(10) =


0(2)


4. Convert to binary (base 2) the fractional part: 0.008 788 423 613 44.

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) 0.008 788 423 613 44 × 2 = 0 + 0.017 576 847 226 88;
  • 2) 0.017 576 847 226 88 × 2 = 0 + 0.035 153 694 453 76;
  • 3) 0.035 153 694 453 76 × 2 = 0 + 0.070 307 388 907 52;
  • 4) 0.070 307 388 907 52 × 2 = 0 + 0.140 614 777 815 04;
  • 5) 0.140 614 777 815 04 × 2 = 0 + 0.281 229 555 630 08;
  • 6) 0.281 229 555 630 08 × 2 = 0 + 0.562 459 111 260 16;
  • 7) 0.562 459 111 260 16 × 2 = 1 + 0.124 918 222 520 32;
  • 8) 0.124 918 222 520 32 × 2 = 0 + 0.249 836 445 040 64;
  • 9) 0.249 836 445 040 64 × 2 = 0 + 0.499 672 890 081 28;
  • 10) 0.499 672 890 081 28 × 2 = 0 + 0.999 345 780 162 56;
  • 11) 0.999 345 780 162 56 × 2 = 1 + 0.998 691 560 325 12;
  • 12) 0.998 691 560 325 12 × 2 = 1 + 0.997 383 120 650 24;
  • 13) 0.997 383 120 650 24 × 2 = 1 + 0.994 766 241 300 48;
  • 14) 0.994 766 241 300 48 × 2 = 1 + 0.989 532 482 600 96;
  • 15) 0.989 532 482 600 96 × 2 = 1 + 0.979 064 965 201 92;
  • 16) 0.979 064 965 201 92 × 2 = 1 + 0.958 129 930 403 84;
  • 17) 0.958 129 930 403 84 × 2 = 1 + 0.916 259 860 807 68;
  • 18) 0.916 259 860 807 68 × 2 = 1 + 0.832 519 721 615 36;
  • 19) 0.832 519 721 615 36 × 2 = 1 + 0.665 039 443 230 72;
  • 20) 0.665 039 443 230 72 × 2 = 1 + 0.330 078 886 461 44;
  • 21) 0.330 078 886 461 44 × 2 = 0 + 0.660 157 772 922 88;
  • 22) 0.660 157 772 922 88 × 2 = 1 + 0.320 315 545 845 76;
  • 23) 0.320 315 545 845 76 × 2 = 0 + 0.640 631 091 691 52;
  • 24) 0.640 631 091 691 52 × 2 = 1 + 0.281 262 183 383 04;
  • 25) 0.281 262 183 383 04 × 2 = 0 + 0.562 524 366 766 08;
  • 26) 0.562 524 366 766 08 × 2 = 1 + 0.125 048 733 532 16;
  • 27) 0.125 048 733 532 16 × 2 = 0 + 0.250 097 467 064 32;
  • 28) 0.250 097 467 064 32 × 2 = 0 + 0.500 194 934 128 64;
  • 29) 0.500 194 934 128 64 × 2 = 1 + 0.000 389 868 257 28;
  • 30) 0.000 389 868 257 28 × 2 = 0 + 0.000 779 736 514 56;
  • 31) 0.000 779 736 514 56 × 2 = 0 + 0.001 559 473 029 12;
  • 32) 0.001 559 473 029 12 × 2 = 0 + 0.003 118 946 058 24;
  • 33) 0.003 118 946 058 24 × 2 = 0 + 0.006 237 892 116 48;
  • 34) 0.006 237 892 116 48 × 2 = 0 + 0.012 475 784 232 96;
  • 35) 0.012 475 784 232 96 × 2 = 0 + 0.024 951 568 465 92;
  • 36) 0.024 951 568 465 92 × 2 = 0 + 0.049 903 136 931 84;
  • 37) 0.049 903 136 931 84 × 2 = 0 + 0.099 806 273 863 68;
  • 38) 0.099 806 273 863 68 × 2 = 0 + 0.199 612 547 727 36;
  • 39) 0.199 612 547 727 36 × 2 = 0 + 0.399 225 095 454 72;
  • 40) 0.399 225 095 454 72 × 2 = 0 + 0.798 450 190 909 44;
  • 41) 0.798 450 190 909 44 × 2 = 1 + 0.596 900 381 818 88;
  • 42) 0.596 900 381 818 88 × 2 = 1 + 0.193 800 763 637 76;
  • 43) 0.193 800 763 637 76 × 2 = 0 + 0.387 601 527 275 52;
  • 44) 0.387 601 527 275 52 × 2 = 0 + 0.775 203 054 551 04;
  • 45) 0.775 203 054 551 04 × 2 = 1 + 0.550 406 109 102 08;
  • 46) 0.550 406 109 102 08 × 2 = 1 + 0.100 812 218 204 16;
  • 47) 0.100 812 218 204 16 × 2 = 0 + 0.201 624 436 408 32;
  • 48) 0.201 624 436 408 32 × 2 = 0 + 0.403 248 872 816 64;
  • 49) 0.403 248 872 816 64 × 2 = 0 + 0.806 497 745 633 28;
  • 50) 0.806 497 745 633 28 × 2 = 1 + 0.612 995 491 266 56;
  • 51) 0.612 995 491 266 56 × 2 = 1 + 0.225 990 982 533 12;
  • 52) 0.225 990 982 533 12 × 2 = 0 + 0.451 981 965 066 24;
  • 53) 0.451 981 965 066 24 × 2 = 0 + 0.903 963 930 132 48;
  • 54) 0.903 963 930 132 48 × 2 = 1 + 0.807 927 860 264 96;
  • 55) 0.807 927 860 264 96 × 2 = 1 + 0.615 855 720 529 92;
  • 56) 0.615 855 720 529 92 × 2 = 1 + 0.231 711 441 059 84;
  • 57) 0.231 711 441 059 84 × 2 = 0 + 0.463 422 882 119 68;
  • 58) 0.463 422 882 119 68 × 2 = 0 + 0.926 845 764 239 36;
  • 59) 0.926 845 764 239 36 × 2 = 1 + 0.853 691 528 478 72;

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:


0.008 788 423 613 44(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0000 1100 1100 0110 0111 001(2)

6. Positive number before normalization:

0.008 788 423 613 44(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0000 1100 1100 0110 0111 001(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 7 positions to the right, so that only one non zero digit remains to the left of it:


0.008 788 423 613 44(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0000 1100 1100 0110 0111 001(2) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0000 1100 1100 0110 0111 001(2) × 20 =


1.0001 1111 1111 1010 1010 0100 0000 0000 0110 0110 0011 0011 1001(2) × 2-7


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): -7


Mantissa (not normalized):
1.0001 1111 1111 1010 1010 0100 0000 0000 0110 0110 0011 0011 1001


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-7 + 2(11-1) - 1 =


(-7 + 1 023)(10) =


1 016(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;
  • 1 016 ÷ 2 = 508 + 0;
  • 508 ÷ 2 = 254 + 0;
  • 254 ÷ 2 = 127 + 0;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1016(10) =


011 1111 1000(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 0001 1111 1111 1010 1010 0100 0000 0000 0110 0110 0011 0011 1001 =


0001 1111 1111 1010 1010 0100 0000 0000 0110 0110 0011 0011 1001


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) =
011 1111 1000


Mantissa (52 bits) =
0001 1111 1111 1010 1010 0100 0000 0000 0110 0110 0011 0011 1001


Decimal number -0.008 788 423 613 44 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1000 - 0001 1111 1111 1010 1010 0100 0000 0000 0110 0110 0011 0011 1001


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