-0.008 788 423 614 66 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

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

|-0.008 788 423 614 66| = 0.008 788 423 614 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: 0.008 788 423 614 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) 0.008 788 423 614 66 × 2 = 0 + 0.017 576 847 229 32;
  • 2) 0.017 576 847 229 32 × 2 = 0 + 0.035 153 694 458 64;
  • 3) 0.035 153 694 458 64 × 2 = 0 + 0.070 307 388 917 28;
  • 4) 0.070 307 388 917 28 × 2 = 0 + 0.140 614 777 834 56;
  • 5) 0.140 614 777 834 56 × 2 = 0 + 0.281 229 555 669 12;
  • 6) 0.281 229 555 669 12 × 2 = 0 + 0.562 459 111 338 24;
  • 7) 0.562 459 111 338 24 × 2 = 1 + 0.124 918 222 676 48;
  • 8) 0.124 918 222 676 48 × 2 = 0 + 0.249 836 445 352 96;
  • 9) 0.249 836 445 352 96 × 2 = 0 + 0.499 672 890 705 92;
  • 10) 0.499 672 890 705 92 × 2 = 0 + 0.999 345 781 411 84;
  • 11) 0.999 345 781 411 84 × 2 = 1 + 0.998 691 562 823 68;
  • 12) 0.998 691 562 823 68 × 2 = 1 + 0.997 383 125 647 36;
  • 13) 0.997 383 125 647 36 × 2 = 1 + 0.994 766 251 294 72;
  • 14) 0.994 766 251 294 72 × 2 = 1 + 0.989 532 502 589 44;
  • 15) 0.989 532 502 589 44 × 2 = 1 + 0.979 065 005 178 88;
  • 16) 0.979 065 005 178 88 × 2 = 1 + 0.958 130 010 357 76;
  • 17) 0.958 130 010 357 76 × 2 = 1 + 0.916 260 020 715 52;
  • 18) 0.916 260 020 715 52 × 2 = 1 + 0.832 520 041 431 04;
  • 19) 0.832 520 041 431 04 × 2 = 1 + 0.665 040 082 862 08;
  • 20) 0.665 040 082 862 08 × 2 = 1 + 0.330 080 165 724 16;
  • 21) 0.330 080 165 724 16 × 2 = 0 + 0.660 160 331 448 32;
  • 22) 0.660 160 331 448 32 × 2 = 1 + 0.320 320 662 896 64;
  • 23) 0.320 320 662 896 64 × 2 = 0 + 0.640 641 325 793 28;
  • 24) 0.640 641 325 793 28 × 2 = 1 + 0.281 282 651 586 56;
  • 25) 0.281 282 651 586 56 × 2 = 0 + 0.562 565 303 173 12;
  • 26) 0.562 565 303 173 12 × 2 = 1 + 0.125 130 606 346 24;
  • 27) 0.125 130 606 346 24 × 2 = 0 + 0.250 261 212 692 48;
  • 28) 0.250 261 212 692 48 × 2 = 0 + 0.500 522 425 384 96;
  • 29) 0.500 522 425 384 96 × 2 = 1 + 0.001 044 850 769 92;
  • 30) 0.001 044 850 769 92 × 2 = 0 + 0.002 089 701 539 84;
  • 31) 0.002 089 701 539 84 × 2 = 0 + 0.004 179 403 079 68;
  • 32) 0.004 179 403 079 68 × 2 = 0 + 0.008 358 806 159 36;
  • 33) 0.008 358 806 159 36 × 2 = 0 + 0.016 717 612 318 72;
  • 34) 0.016 717 612 318 72 × 2 = 0 + 0.033 435 224 637 44;
  • 35) 0.033 435 224 637 44 × 2 = 0 + 0.066 870 449 274 88;
  • 36) 0.066 870 449 274 88 × 2 = 0 + 0.133 740 898 549 76;
  • 37) 0.133 740 898 549 76 × 2 = 0 + 0.267 481 797 099 52;
  • 38) 0.267 481 797 099 52 × 2 = 0 + 0.534 963 594 199 04;
  • 39) 0.534 963 594 199 04 × 2 = 1 + 0.069 927 188 398 08;
  • 40) 0.069 927 188 398 08 × 2 = 0 + 0.139 854 376 796 16;
  • 41) 0.139 854 376 796 16 × 2 = 0 + 0.279 708 753 592 32;
  • 42) 0.279 708 753 592 32 × 2 = 0 + 0.559 417 507 184 64;
  • 43) 0.559 417 507 184 64 × 2 = 1 + 0.118 835 014 369 28;
  • 44) 0.118 835 014 369 28 × 2 = 0 + 0.237 670 028 738 56;
  • 45) 0.237 670 028 738 56 × 2 = 0 + 0.475 340 057 477 12;
  • 46) 0.475 340 057 477 12 × 2 = 0 + 0.950 680 114 954 24;
  • 47) 0.950 680 114 954 24 × 2 = 1 + 0.901 360 229 908 48;
  • 48) 0.901 360 229 908 48 × 2 = 1 + 0.802 720 459 816 96;
  • 49) 0.802 720 459 816 96 × 2 = 1 + 0.605 440 919 633 92;
  • 50) 0.605 440 919 633 92 × 2 = 1 + 0.210 881 839 267 84;
  • 51) 0.210 881 839 267 84 × 2 = 0 + 0.421 763 678 535 68;
  • 52) 0.421 763 678 535 68 × 2 = 0 + 0.843 527 357 071 36;
  • 53) 0.843 527 357 071 36 × 2 = 1 + 0.687 054 714 142 72;
  • 54) 0.687 054 714 142 72 × 2 = 1 + 0.374 109 428 285 44;
  • 55) 0.374 109 428 285 44 × 2 = 0 + 0.748 218 856 570 88;
  • 56) 0.748 218 856 570 88 × 2 = 1 + 0.496 437 713 141 76;
  • 57) 0.496 437 713 141 76 × 2 = 0 + 0.992 875 426 283 52;
  • 58) 0.992 875 426 283 52 × 2 = 1 + 0.985 750 852 567 04;
  • 59) 0.985 750 852 567 04 × 2 = 1 + 0.971 501 705 134 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:


0.008 788 423 614 66(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0010 0010 0011 1100 1101 011(2)

6. Positive number before normalization:

0.008 788 423 614 66(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0010 0010 0011 1100 1101 011(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 66(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0010 0010 0011 1100 1101 011(2) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0010 0010 0011 1100 1101 011(2) × 20 =


1.0001 1111 1111 1010 1010 0100 0000 0001 0001 0001 1110 0110 1011(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 0001 0001 1110 0110 1011


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 0001 0001 1110 0110 1011 =


0001 1111 1111 1010 1010 0100 0000 0001 0001 0001 1110 0110 1011


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 0001 0001 1110 0110 1011


Decimal number -0.008 788 423 614 66 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1000 - 0001 1111 1111 1010 1010 0100 0000 0001 0001 0001 1110 0110 1011


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