-0.008 788 423 612 71 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.008 788 423 612 71(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
-0.008 788 423 612 71(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:

|-0.008 788 423 612 71| = 0.008 788 423 612 71


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: 0.008 788 423 612 71.

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) 0.008 788 423 612 71 × 2 = 0 + 0.017 576 847 225 42;
  • 2) 0.017 576 847 225 42 × 2 = 0 + 0.035 153 694 450 84;
  • 3) 0.035 153 694 450 84 × 2 = 0 + 0.070 307 388 901 68;
  • 4) 0.070 307 388 901 68 × 2 = 0 + 0.140 614 777 803 36;
  • 5) 0.140 614 777 803 36 × 2 = 0 + 0.281 229 555 606 72;
  • 6) 0.281 229 555 606 72 × 2 = 0 + 0.562 459 111 213 44;
  • 7) 0.562 459 111 213 44 × 2 = 1 + 0.124 918 222 426 88;
  • 8) 0.124 918 222 426 88 × 2 = 0 + 0.249 836 444 853 76;
  • 9) 0.249 836 444 853 76 × 2 = 0 + 0.499 672 889 707 52;
  • 10) 0.499 672 889 707 52 × 2 = 0 + 0.999 345 779 415 04;
  • 11) 0.999 345 779 415 04 × 2 = 1 + 0.998 691 558 830 08;
  • 12) 0.998 691 558 830 08 × 2 = 1 + 0.997 383 117 660 16;
  • 13) 0.997 383 117 660 16 × 2 = 1 + 0.994 766 235 320 32;
  • 14) 0.994 766 235 320 32 × 2 = 1 + 0.989 532 470 640 64;
  • 15) 0.989 532 470 640 64 × 2 = 1 + 0.979 064 941 281 28;
  • 16) 0.979 064 941 281 28 × 2 = 1 + 0.958 129 882 562 56;
  • 17) 0.958 129 882 562 56 × 2 = 1 + 0.916 259 765 125 12;
  • 18) 0.916 259 765 125 12 × 2 = 1 + 0.832 519 530 250 24;
  • 19) 0.832 519 530 250 24 × 2 = 1 + 0.665 039 060 500 48;
  • 20) 0.665 039 060 500 48 × 2 = 1 + 0.330 078 121 000 96;
  • 21) 0.330 078 121 000 96 × 2 = 0 + 0.660 156 242 001 92;
  • 22) 0.660 156 242 001 92 × 2 = 1 + 0.320 312 484 003 84;
  • 23) 0.320 312 484 003 84 × 2 = 0 + 0.640 624 968 007 68;
  • 24) 0.640 624 968 007 68 × 2 = 1 + 0.281 249 936 015 36;
  • 25) 0.281 249 936 015 36 × 2 = 0 + 0.562 499 872 030 72;
  • 26) 0.562 499 872 030 72 × 2 = 1 + 0.124 999 744 061 44;
  • 27) 0.124 999 744 061 44 × 2 = 0 + 0.249 999 488 122 88;
  • 28) 0.249 999 488 122 88 × 2 = 0 + 0.499 998 976 245 76;
  • 29) 0.499 998 976 245 76 × 2 = 0 + 0.999 997 952 491 52;
  • 30) 0.999 997 952 491 52 × 2 = 1 + 0.999 995 904 983 04;
  • 31) 0.999 995 904 983 04 × 2 = 1 + 0.999 991 809 966 08;
  • 32) 0.999 991 809 966 08 × 2 = 1 + 0.999 983 619 932 16;
  • 33) 0.999 983 619 932 16 × 2 = 1 + 0.999 967 239 864 32;
  • 34) 0.999 967 239 864 32 × 2 = 1 + 0.999 934 479 728 64;
  • 35) 0.999 934 479 728 64 × 2 = 1 + 0.999 868 959 457 28;
  • 36) 0.999 868 959 457 28 × 2 = 1 + 0.999 737 918 914 56;
  • 37) 0.999 737 918 914 56 × 2 = 1 + 0.999 475 837 829 12;
  • 38) 0.999 475 837 829 12 × 2 = 1 + 0.998 951 675 658 24;
  • 39) 0.998 951 675 658 24 × 2 = 1 + 0.997 903 351 316 48;
  • 40) 0.997 903 351 316 48 × 2 = 1 + 0.995 806 702 632 96;
  • 41) 0.995 806 702 632 96 × 2 = 1 + 0.991 613 405 265 92;
  • 42) 0.991 613 405 265 92 × 2 = 1 + 0.983 226 810 531 84;
  • 43) 0.983 226 810 531 84 × 2 = 1 + 0.966 453 621 063 68;
  • 44) 0.966 453 621 063 68 × 2 = 1 + 0.932 907 242 127 36;
  • 45) 0.932 907 242 127 36 × 2 = 1 + 0.865 814 484 254 72;
  • 46) 0.865 814 484 254 72 × 2 = 1 + 0.731 628 968 509 44;
  • 47) 0.731 628 968 509 44 × 2 = 1 + 0.463 257 937 018 88;
  • 48) 0.463 257 937 018 88 × 2 = 0 + 0.926 515 874 037 76;
  • 49) 0.926 515 874 037 76 × 2 = 1 + 0.853 031 748 075 52;
  • 50) 0.853 031 748 075 52 × 2 = 1 + 0.706 063 496 151 04;
  • 51) 0.706 063 496 151 04 × 2 = 1 + 0.412 126 992 302 08;
  • 52) 0.412 126 992 302 08 × 2 = 0 + 0.824 253 984 604 16;
  • 53) 0.824 253 984 604 16 × 2 = 1 + 0.648 507 969 208 32;
  • 54) 0.648 507 969 208 32 × 2 = 1 + 0.297 015 938 416 64;
  • 55) 0.297 015 938 416 64 × 2 = 0 + 0.594 031 876 833 28;
  • 56) 0.594 031 876 833 28 × 2 = 1 + 0.188 063 753 666 56;
  • 57) 0.188 063 753 666 56 × 2 = 0 + 0.376 127 507 333 12;
  • 58) 0.376 127 507 333 12 × 2 = 0 + 0.752 255 014 666 24;
  • 59) 0.752 255 014 666 24 × 2 = 1 + 0.504 510 029 332 48;

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:


0.008 788 423 612 71(10) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 1111 1110 1110 1101 001(2)

6. Positive number before normalization:

0.008 788 423 612 71(10) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 1111 1110 1110 1101 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:


0.008 788 423 612 71(10) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 1111 1110 1110 1101 001(2) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 1111 1110 1110 1101 001(2) × 20 =


1.0001 1111 1111 1010 1010 0011 1111 1111 1111 1111 0111 0110 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 0011 1111 1111 1111 1111 0111 0110 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 0011 1111 1111 1111 1111 0111 0110 1001 =


0001 1111 1111 1010 1010 0011 1111 1111 1111 1111 0111 0110 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 0011 1111 1111 1111 1111 0111 0110 1001


Decimal number -0.008 788 423 612 71 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1000 - 0001 1111 1111 1010 1010 0011 1111 1111 1111 1111 0111 0110 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