-0.008 788 423 611 89 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.008 788 423 611 89(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
-0.008 788 423 611 89(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:

|-0.008 788 423 611 89| = 0.008 788 423 611 89


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: 0.008 788 423 611 89.

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) 0.008 788 423 611 89 × 2 = 0 + 0.017 576 847 223 78;
  • 2) 0.017 576 847 223 78 × 2 = 0 + 0.035 153 694 447 56;
  • 3) 0.035 153 694 447 56 × 2 = 0 + 0.070 307 388 895 12;
  • 4) 0.070 307 388 895 12 × 2 = 0 + 0.140 614 777 790 24;
  • 5) 0.140 614 777 790 24 × 2 = 0 + 0.281 229 555 580 48;
  • 6) 0.281 229 555 580 48 × 2 = 0 + 0.562 459 111 160 96;
  • 7) 0.562 459 111 160 96 × 2 = 1 + 0.124 918 222 321 92;
  • 8) 0.124 918 222 321 92 × 2 = 0 + 0.249 836 444 643 84;
  • 9) 0.249 836 444 643 84 × 2 = 0 + 0.499 672 889 287 68;
  • 10) 0.499 672 889 287 68 × 2 = 0 + 0.999 345 778 575 36;
  • 11) 0.999 345 778 575 36 × 2 = 1 + 0.998 691 557 150 72;
  • 12) 0.998 691 557 150 72 × 2 = 1 + 0.997 383 114 301 44;
  • 13) 0.997 383 114 301 44 × 2 = 1 + 0.994 766 228 602 88;
  • 14) 0.994 766 228 602 88 × 2 = 1 + 0.989 532 457 205 76;
  • 15) 0.989 532 457 205 76 × 2 = 1 + 0.979 064 914 411 52;
  • 16) 0.979 064 914 411 52 × 2 = 1 + 0.958 129 828 823 04;
  • 17) 0.958 129 828 823 04 × 2 = 1 + 0.916 259 657 646 08;
  • 18) 0.916 259 657 646 08 × 2 = 1 + 0.832 519 315 292 16;
  • 19) 0.832 519 315 292 16 × 2 = 1 + 0.665 038 630 584 32;
  • 20) 0.665 038 630 584 32 × 2 = 1 + 0.330 077 261 168 64;
  • 21) 0.330 077 261 168 64 × 2 = 0 + 0.660 154 522 337 28;
  • 22) 0.660 154 522 337 28 × 2 = 1 + 0.320 309 044 674 56;
  • 23) 0.320 309 044 674 56 × 2 = 0 + 0.640 618 089 349 12;
  • 24) 0.640 618 089 349 12 × 2 = 1 + 0.281 236 178 698 24;
  • 25) 0.281 236 178 698 24 × 2 = 0 + 0.562 472 357 396 48;
  • 26) 0.562 472 357 396 48 × 2 = 1 + 0.124 944 714 792 96;
  • 27) 0.124 944 714 792 96 × 2 = 0 + 0.249 889 429 585 92;
  • 28) 0.249 889 429 585 92 × 2 = 0 + 0.499 778 859 171 84;
  • 29) 0.499 778 859 171 84 × 2 = 0 + 0.999 557 718 343 68;
  • 30) 0.999 557 718 343 68 × 2 = 1 + 0.999 115 436 687 36;
  • 31) 0.999 115 436 687 36 × 2 = 1 + 0.998 230 873 374 72;
  • 32) 0.998 230 873 374 72 × 2 = 1 + 0.996 461 746 749 44;
  • 33) 0.996 461 746 749 44 × 2 = 1 + 0.992 923 493 498 88;
  • 34) 0.992 923 493 498 88 × 2 = 1 + 0.985 846 986 997 76;
  • 35) 0.985 846 986 997 76 × 2 = 1 + 0.971 693 973 995 52;
  • 36) 0.971 693 973 995 52 × 2 = 1 + 0.943 387 947 991 04;
  • 37) 0.943 387 947 991 04 × 2 = 1 + 0.886 775 895 982 08;
  • 38) 0.886 775 895 982 08 × 2 = 1 + 0.773 551 791 964 16;
  • 39) 0.773 551 791 964 16 × 2 = 1 + 0.547 103 583 928 32;
  • 40) 0.547 103 583 928 32 × 2 = 1 + 0.094 207 167 856 64;
  • 41) 0.094 207 167 856 64 × 2 = 0 + 0.188 414 335 713 28;
  • 42) 0.188 414 335 713 28 × 2 = 0 + 0.376 828 671 426 56;
  • 43) 0.376 828 671 426 56 × 2 = 0 + 0.753 657 342 853 12;
  • 44) 0.753 657 342 853 12 × 2 = 1 + 0.507 314 685 706 24;
  • 45) 0.507 314 685 706 24 × 2 = 1 + 0.014 629 371 412 48;
  • 46) 0.014 629 371 412 48 × 2 = 0 + 0.029 258 742 824 96;
  • 47) 0.029 258 742 824 96 × 2 = 0 + 0.058 517 485 649 92;
  • 48) 0.058 517 485 649 92 × 2 = 0 + 0.117 034 971 299 84;
  • 49) 0.117 034 971 299 84 × 2 = 0 + 0.234 069 942 599 68;
  • 50) 0.234 069 942 599 68 × 2 = 0 + 0.468 139 885 199 36;
  • 51) 0.468 139 885 199 36 × 2 = 0 + 0.936 279 770 398 72;
  • 52) 0.936 279 770 398 72 × 2 = 1 + 0.872 559 540 797 44;
  • 53) 0.872 559 540 797 44 × 2 = 1 + 0.745 119 081 594 88;
  • 54) 0.745 119 081 594 88 × 2 = 1 + 0.490 238 163 189 76;
  • 55) 0.490 238 163 189 76 × 2 = 0 + 0.980 476 326 379 52;
  • 56) 0.980 476 326 379 52 × 2 = 1 + 0.960 952 652 759 04;
  • 57) 0.960 952 652 759 04 × 2 = 1 + 0.921 905 305 518 08;
  • 58) 0.921 905 305 518 08 × 2 = 1 + 0.843 810 611 036 16;
  • 59) 0.843 810 611 036 16 × 2 = 1 + 0.687 621 222 072 32;

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:


0.008 788 423 611 89(10) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 0001 1000 0001 1101 111(2)

6. Positive number before normalization:

0.008 788 423 611 89(10) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 0001 1000 0001 1101 111(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:


0.008 788 423 611 89(10) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 0001 1000 0001 1101 111(2) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 0001 1000 0001 1101 111(2) × 20 =


1.0001 1111 1111 1010 1010 0011 1111 1111 1000 1100 0000 1110 1111(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 1000 1100 0000 1110 1111


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 1000 1100 0000 1110 1111 =


0001 1111 1111 1010 1010 0011 1111 1111 1000 1100 0000 1110 1111


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 1000 1100 0000 1110 1111


Decimal number -0.008 788 423 611 89 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1000 - 0001 1111 1111 1010 1010 0011 1111 1111 1000 1100 0000 1110 1111


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