-0.008 788 423 614 47 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.008 788 423 614 47(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 47(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 47| = 0.008 788 423 614 47


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 47.

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 47 × 2 = 0 + 0.017 576 847 228 94;
  • 2) 0.017 576 847 228 94 × 2 = 0 + 0.035 153 694 457 88;
  • 3) 0.035 153 694 457 88 × 2 = 0 + 0.070 307 388 915 76;
  • 4) 0.070 307 388 915 76 × 2 = 0 + 0.140 614 777 831 52;
  • 5) 0.140 614 777 831 52 × 2 = 0 + 0.281 229 555 663 04;
  • 6) 0.281 229 555 663 04 × 2 = 0 + 0.562 459 111 326 08;
  • 7) 0.562 459 111 326 08 × 2 = 1 + 0.124 918 222 652 16;
  • 8) 0.124 918 222 652 16 × 2 = 0 + 0.249 836 445 304 32;
  • 9) 0.249 836 445 304 32 × 2 = 0 + 0.499 672 890 608 64;
  • 10) 0.499 672 890 608 64 × 2 = 0 + 0.999 345 781 217 28;
  • 11) 0.999 345 781 217 28 × 2 = 1 + 0.998 691 562 434 56;
  • 12) 0.998 691 562 434 56 × 2 = 1 + 0.997 383 124 869 12;
  • 13) 0.997 383 124 869 12 × 2 = 1 + 0.994 766 249 738 24;
  • 14) 0.994 766 249 738 24 × 2 = 1 + 0.989 532 499 476 48;
  • 15) 0.989 532 499 476 48 × 2 = 1 + 0.979 064 998 952 96;
  • 16) 0.979 064 998 952 96 × 2 = 1 + 0.958 129 997 905 92;
  • 17) 0.958 129 997 905 92 × 2 = 1 + 0.916 259 995 811 84;
  • 18) 0.916 259 995 811 84 × 2 = 1 + 0.832 519 991 623 68;
  • 19) 0.832 519 991 623 68 × 2 = 1 + 0.665 039 983 247 36;
  • 20) 0.665 039 983 247 36 × 2 = 1 + 0.330 079 966 494 72;
  • 21) 0.330 079 966 494 72 × 2 = 0 + 0.660 159 932 989 44;
  • 22) 0.660 159 932 989 44 × 2 = 1 + 0.320 319 865 978 88;
  • 23) 0.320 319 865 978 88 × 2 = 0 + 0.640 639 731 957 76;
  • 24) 0.640 639 731 957 76 × 2 = 1 + 0.281 279 463 915 52;
  • 25) 0.281 279 463 915 52 × 2 = 0 + 0.562 558 927 831 04;
  • 26) 0.562 558 927 831 04 × 2 = 1 + 0.125 117 855 662 08;
  • 27) 0.125 117 855 662 08 × 2 = 0 + 0.250 235 711 324 16;
  • 28) 0.250 235 711 324 16 × 2 = 0 + 0.500 471 422 648 32;
  • 29) 0.500 471 422 648 32 × 2 = 1 + 0.000 942 845 296 64;
  • 30) 0.000 942 845 296 64 × 2 = 0 + 0.001 885 690 593 28;
  • 31) 0.001 885 690 593 28 × 2 = 0 + 0.003 771 381 186 56;
  • 32) 0.003 771 381 186 56 × 2 = 0 + 0.007 542 762 373 12;
  • 33) 0.007 542 762 373 12 × 2 = 0 + 0.015 085 524 746 24;
  • 34) 0.015 085 524 746 24 × 2 = 0 + 0.030 171 049 492 48;
  • 35) 0.030 171 049 492 48 × 2 = 0 + 0.060 342 098 984 96;
  • 36) 0.060 342 098 984 96 × 2 = 0 + 0.120 684 197 969 92;
  • 37) 0.120 684 197 969 92 × 2 = 0 + 0.241 368 395 939 84;
  • 38) 0.241 368 395 939 84 × 2 = 0 + 0.482 736 791 879 68;
  • 39) 0.482 736 791 879 68 × 2 = 0 + 0.965 473 583 759 36;
  • 40) 0.965 473 583 759 36 × 2 = 1 + 0.930 947 167 518 72;
  • 41) 0.930 947 167 518 72 × 2 = 1 + 0.861 894 335 037 44;
  • 42) 0.861 894 335 037 44 × 2 = 1 + 0.723 788 670 074 88;
  • 43) 0.723 788 670 074 88 × 2 = 1 + 0.447 577 340 149 76;
  • 44) 0.447 577 340 149 76 × 2 = 0 + 0.895 154 680 299 52;
  • 45) 0.895 154 680 299 52 × 2 = 1 + 0.790 309 360 599 04;
  • 46) 0.790 309 360 599 04 × 2 = 1 + 0.580 618 721 198 08;
  • 47) 0.580 618 721 198 08 × 2 = 1 + 0.161 237 442 396 16;
  • 48) 0.161 237 442 396 16 × 2 = 0 + 0.322 474 884 792 32;
  • 49) 0.322 474 884 792 32 × 2 = 0 + 0.644 949 769 584 64;
  • 50) 0.644 949 769 584 64 × 2 = 1 + 0.289 899 539 169 28;
  • 51) 0.289 899 539 169 28 × 2 = 0 + 0.579 799 078 338 56;
  • 52) 0.579 799 078 338 56 × 2 = 1 + 0.159 598 156 677 12;
  • 53) 0.159 598 156 677 12 × 2 = 0 + 0.319 196 313 354 24;
  • 54) 0.319 196 313 354 24 × 2 = 0 + 0.638 392 626 708 48;
  • 55) 0.638 392 626 708 48 × 2 = 1 + 0.276 785 253 416 96;
  • 56) 0.276 785 253 416 96 × 2 = 0 + 0.553 570 506 833 92;
  • 57) 0.553 570 506 833 92 × 2 = 1 + 0.107 141 013 667 84;
  • 58) 0.107 141 013 667 84 × 2 = 0 + 0.214 282 027 335 68;
  • 59) 0.214 282 027 335 68 × 2 = 0 + 0.428 564 054 671 36;

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 47(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0001 1110 1110 0101 0010 100(2)

6. Positive number before normalization:

0.008 788 423 614 47(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0001 1110 1110 0101 0010 100(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 47(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0001 1110 1110 0101 0010 100(2) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0001 1110 1110 0101 0010 100(2) × 20 =


1.0001 1111 1111 1010 1010 0100 0000 0000 1111 0111 0010 1001 0100(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 1111 0111 0010 1001 0100


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 1111 0111 0010 1001 0100 =


0001 1111 1111 1010 1010 0100 0000 0000 1111 0111 0010 1001 0100


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 1111 0111 0010 1001 0100


Decimal number -0.008 788 423 614 47 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1000 - 0001 1111 1111 1010 1010 0100 0000 0000 1111 0111 0010 1001 0100


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