-0.008 788 423 612 66 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.008 788 423 612 66(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 66(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 66| = 0.008 788 423 612 66


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 66.

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 66 × 2 = 0 + 0.017 576 847 225 32;
  • 2) 0.017 576 847 225 32 × 2 = 0 + 0.035 153 694 450 64;
  • 3) 0.035 153 694 450 64 × 2 = 0 + 0.070 307 388 901 28;
  • 4) 0.070 307 388 901 28 × 2 = 0 + 0.140 614 777 802 56;
  • 5) 0.140 614 777 802 56 × 2 = 0 + 0.281 229 555 605 12;
  • 6) 0.281 229 555 605 12 × 2 = 0 + 0.562 459 111 210 24;
  • 7) 0.562 459 111 210 24 × 2 = 1 + 0.124 918 222 420 48;
  • 8) 0.124 918 222 420 48 × 2 = 0 + 0.249 836 444 840 96;
  • 9) 0.249 836 444 840 96 × 2 = 0 + 0.499 672 889 681 92;
  • 10) 0.499 672 889 681 92 × 2 = 0 + 0.999 345 779 363 84;
  • 11) 0.999 345 779 363 84 × 2 = 1 + 0.998 691 558 727 68;
  • 12) 0.998 691 558 727 68 × 2 = 1 + 0.997 383 117 455 36;
  • 13) 0.997 383 117 455 36 × 2 = 1 + 0.994 766 234 910 72;
  • 14) 0.994 766 234 910 72 × 2 = 1 + 0.989 532 469 821 44;
  • 15) 0.989 532 469 821 44 × 2 = 1 + 0.979 064 939 642 88;
  • 16) 0.979 064 939 642 88 × 2 = 1 + 0.958 129 879 285 76;
  • 17) 0.958 129 879 285 76 × 2 = 1 + 0.916 259 758 571 52;
  • 18) 0.916 259 758 571 52 × 2 = 1 + 0.832 519 517 143 04;
  • 19) 0.832 519 517 143 04 × 2 = 1 + 0.665 039 034 286 08;
  • 20) 0.665 039 034 286 08 × 2 = 1 + 0.330 078 068 572 16;
  • 21) 0.330 078 068 572 16 × 2 = 0 + 0.660 156 137 144 32;
  • 22) 0.660 156 137 144 32 × 2 = 1 + 0.320 312 274 288 64;
  • 23) 0.320 312 274 288 64 × 2 = 0 + 0.640 624 548 577 28;
  • 24) 0.640 624 548 577 28 × 2 = 1 + 0.281 249 097 154 56;
  • 25) 0.281 249 097 154 56 × 2 = 0 + 0.562 498 194 309 12;
  • 26) 0.562 498 194 309 12 × 2 = 1 + 0.124 996 388 618 24;
  • 27) 0.124 996 388 618 24 × 2 = 0 + 0.249 992 777 236 48;
  • 28) 0.249 992 777 236 48 × 2 = 0 + 0.499 985 554 472 96;
  • 29) 0.499 985 554 472 96 × 2 = 0 + 0.999 971 108 945 92;
  • 30) 0.999 971 108 945 92 × 2 = 1 + 0.999 942 217 891 84;
  • 31) 0.999 942 217 891 84 × 2 = 1 + 0.999 884 435 783 68;
  • 32) 0.999 884 435 783 68 × 2 = 1 + 0.999 768 871 567 36;
  • 33) 0.999 768 871 567 36 × 2 = 1 + 0.999 537 743 134 72;
  • 34) 0.999 537 743 134 72 × 2 = 1 + 0.999 075 486 269 44;
  • 35) 0.999 075 486 269 44 × 2 = 1 + 0.998 150 972 538 88;
  • 36) 0.998 150 972 538 88 × 2 = 1 + 0.996 301 945 077 76;
  • 37) 0.996 301 945 077 76 × 2 = 1 + 0.992 603 890 155 52;
  • 38) 0.992 603 890 155 52 × 2 = 1 + 0.985 207 780 311 04;
  • 39) 0.985 207 780 311 04 × 2 = 1 + 0.970 415 560 622 08;
  • 40) 0.970 415 560 622 08 × 2 = 1 + 0.940 831 121 244 16;
  • 41) 0.940 831 121 244 16 × 2 = 1 + 0.881 662 242 488 32;
  • 42) 0.881 662 242 488 32 × 2 = 1 + 0.763 324 484 976 64;
  • 43) 0.763 324 484 976 64 × 2 = 1 + 0.526 648 969 953 28;
  • 44) 0.526 648 969 953 28 × 2 = 1 + 0.053 297 939 906 56;
  • 45) 0.053 297 939 906 56 × 2 = 0 + 0.106 595 879 813 12;
  • 46) 0.106 595 879 813 12 × 2 = 0 + 0.213 191 759 626 24;
  • 47) 0.213 191 759 626 24 × 2 = 0 + 0.426 383 519 252 48;
  • 48) 0.426 383 519 252 48 × 2 = 0 + 0.852 767 038 504 96;
  • 49) 0.852 767 038 504 96 × 2 = 1 + 0.705 534 077 009 92;
  • 50) 0.705 534 077 009 92 × 2 = 1 + 0.411 068 154 019 84;
  • 51) 0.411 068 154 019 84 × 2 = 0 + 0.822 136 308 039 68;
  • 52) 0.822 136 308 039 68 × 2 = 1 + 0.644 272 616 079 36;
  • 53) 0.644 272 616 079 36 × 2 = 1 + 0.288 545 232 158 72;
  • 54) 0.288 545 232 158 72 × 2 = 0 + 0.577 090 464 317 44;
  • 55) 0.577 090 464 317 44 × 2 = 1 + 0.154 180 928 634 88;
  • 56) 0.154 180 928 634 88 × 2 = 0 + 0.308 361 857 269 76;
  • 57) 0.308 361 857 269 76 × 2 = 0 + 0.616 723 714 539 52;
  • 58) 0.616 723 714 539 52 × 2 = 1 + 0.233 447 429 079 04;
  • 59) 0.233 447 429 079 04 × 2 = 0 + 0.466 894 858 158 08;

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 66(10) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 1111 0000 1101 1010 010(2)

6. Positive number before normalization:

0.008 788 423 612 66(10) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 1111 0000 1101 1010 010(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 66(10) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 1111 0000 1101 1010 010(2) =


0.0000 0010 0011 1111 1111 0101 0100 0111 1111 1111 1111 0000 1101 1010 010(2) × 20 =


1.0001 1111 1111 1010 1010 0011 1111 1111 1111 1000 0110 1101 0010(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 1000 0110 1101 0010


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 1000 0110 1101 0010 =


0001 1111 1111 1010 1010 0011 1111 1111 1111 1000 0110 1101 0010


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 1000 0110 1101 0010


Decimal number -0.008 788 423 612 66 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 1000 0110 1101 0010


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