-0.008 788 423 614 98 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.008 788 423 614 98(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
-0.008 788 423 614 98(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:

|-0.008 788 423 614 98| = 0.008 788 423 614 98


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: 0.008 788 423 614 98.

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) 0.008 788 423 614 98 × 2 = 0 + 0.017 576 847 229 96;
  • 2) 0.017 576 847 229 96 × 2 = 0 + 0.035 153 694 459 92;
  • 3) 0.035 153 694 459 92 × 2 = 0 + 0.070 307 388 919 84;
  • 4) 0.070 307 388 919 84 × 2 = 0 + 0.140 614 777 839 68;
  • 5) 0.140 614 777 839 68 × 2 = 0 + 0.281 229 555 679 36;
  • 6) 0.281 229 555 679 36 × 2 = 0 + 0.562 459 111 358 72;
  • 7) 0.562 459 111 358 72 × 2 = 1 + 0.124 918 222 717 44;
  • 8) 0.124 918 222 717 44 × 2 = 0 + 0.249 836 445 434 88;
  • 9) 0.249 836 445 434 88 × 2 = 0 + 0.499 672 890 869 76;
  • 10) 0.499 672 890 869 76 × 2 = 0 + 0.999 345 781 739 52;
  • 11) 0.999 345 781 739 52 × 2 = 1 + 0.998 691 563 479 04;
  • 12) 0.998 691 563 479 04 × 2 = 1 + 0.997 383 126 958 08;
  • 13) 0.997 383 126 958 08 × 2 = 1 + 0.994 766 253 916 16;
  • 14) 0.994 766 253 916 16 × 2 = 1 + 0.989 532 507 832 32;
  • 15) 0.989 532 507 832 32 × 2 = 1 + 0.979 065 015 664 64;
  • 16) 0.979 065 015 664 64 × 2 = 1 + 0.958 130 031 329 28;
  • 17) 0.958 130 031 329 28 × 2 = 1 + 0.916 260 062 658 56;
  • 18) 0.916 260 062 658 56 × 2 = 1 + 0.832 520 125 317 12;
  • 19) 0.832 520 125 317 12 × 2 = 1 + 0.665 040 250 634 24;
  • 20) 0.665 040 250 634 24 × 2 = 1 + 0.330 080 501 268 48;
  • 21) 0.330 080 501 268 48 × 2 = 0 + 0.660 161 002 536 96;
  • 22) 0.660 161 002 536 96 × 2 = 1 + 0.320 322 005 073 92;
  • 23) 0.320 322 005 073 92 × 2 = 0 + 0.640 644 010 147 84;
  • 24) 0.640 644 010 147 84 × 2 = 1 + 0.281 288 020 295 68;
  • 25) 0.281 288 020 295 68 × 2 = 0 + 0.562 576 040 591 36;
  • 26) 0.562 576 040 591 36 × 2 = 1 + 0.125 152 081 182 72;
  • 27) 0.125 152 081 182 72 × 2 = 0 + 0.250 304 162 365 44;
  • 28) 0.250 304 162 365 44 × 2 = 0 + 0.500 608 324 730 88;
  • 29) 0.500 608 324 730 88 × 2 = 1 + 0.001 216 649 461 76;
  • 30) 0.001 216 649 461 76 × 2 = 0 + 0.002 433 298 923 52;
  • 31) 0.002 433 298 923 52 × 2 = 0 + 0.004 866 597 847 04;
  • 32) 0.004 866 597 847 04 × 2 = 0 + 0.009 733 195 694 08;
  • 33) 0.009 733 195 694 08 × 2 = 0 + 0.019 466 391 388 16;
  • 34) 0.019 466 391 388 16 × 2 = 0 + 0.038 932 782 776 32;
  • 35) 0.038 932 782 776 32 × 2 = 0 + 0.077 865 565 552 64;
  • 36) 0.077 865 565 552 64 × 2 = 0 + 0.155 731 131 105 28;
  • 37) 0.155 731 131 105 28 × 2 = 0 + 0.311 462 262 210 56;
  • 38) 0.311 462 262 210 56 × 2 = 0 + 0.622 924 524 421 12;
  • 39) 0.622 924 524 421 12 × 2 = 1 + 0.245 849 048 842 24;
  • 40) 0.245 849 048 842 24 × 2 = 0 + 0.491 698 097 684 48;
  • 41) 0.491 698 097 684 48 × 2 = 0 + 0.983 396 195 368 96;
  • 42) 0.983 396 195 368 96 × 2 = 1 + 0.966 792 390 737 92;
  • 43) 0.966 792 390 737 92 × 2 = 1 + 0.933 584 781 475 84;
  • 44) 0.933 584 781 475 84 × 2 = 1 + 0.867 169 562 951 68;
  • 45) 0.867 169 562 951 68 × 2 = 1 + 0.734 339 125 903 36;
  • 46) 0.734 339 125 903 36 × 2 = 1 + 0.468 678 251 806 72;
  • 47) 0.468 678 251 806 72 × 2 = 0 + 0.937 356 503 613 44;
  • 48) 0.937 356 503 613 44 × 2 = 1 + 0.874 713 007 226 88;
  • 49) 0.874 713 007 226 88 × 2 = 1 + 0.749 426 014 453 76;
  • 50) 0.749 426 014 453 76 × 2 = 1 + 0.498 852 028 907 52;
  • 51) 0.498 852 028 907 52 × 2 = 0 + 0.997 704 057 815 04;
  • 52) 0.997 704 057 815 04 × 2 = 1 + 0.995 408 115 630 08;
  • 53) 0.995 408 115 630 08 × 2 = 1 + 0.990 816 231 260 16;
  • 54) 0.990 816 231 260 16 × 2 = 1 + 0.981 632 462 520 32;
  • 55) 0.981 632 462 520 32 × 2 = 1 + 0.963 264 925 040 64;
  • 56) 0.963 264 925 040 64 × 2 = 1 + 0.926 529 850 081 28;
  • 57) 0.926 529 850 081 28 × 2 = 1 + 0.853 059 700 162 56;
  • 58) 0.853 059 700 162 56 × 2 = 1 + 0.706 119 400 325 12;
  • 59) 0.706 119 400 325 12 × 2 = 1 + 0.412 238 800 650 24;

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:


0.008 788 423 614 98(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0010 0111 1101 1101 1111 111(2)

6. Positive number before normalization:

0.008 788 423 614 98(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0010 0111 1101 1101 1111 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:


0.008 788 423 614 98(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0010 0111 1101 1101 1111 111(2) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0010 0111 1101 1101 1111 111(2) × 20 =


1.0001 1111 1111 1010 1010 0100 0000 0001 0011 1110 1110 1111 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 0100 0000 0001 0011 1110 1110 1111 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 0100 0000 0001 0011 1110 1110 1111 1111 =


0001 1111 1111 1010 1010 0100 0000 0001 0011 1110 1110 1111 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 0100 0000 0001 0011 1110 1110 1111 1111


Decimal number -0.008 788 423 614 98 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1000 - 0001 1111 1111 1010 1010 0100 0000 0001 0011 1110 1110 1111 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