8 800.883 411 943 535 971 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 8 800.883 411 943 535 971 3(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
8 800.883 411 943 535 971 3(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. First, convert to binary (in base 2) the integer part: 8 800.
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;
  • 8 800 ÷ 2 = 4 400 + 0;
  • 4 400 ÷ 2 = 2 200 + 0;
  • 2 200 ÷ 2 = 1 100 + 0;
  • 1 100 ÷ 2 = 550 + 0;
  • 550 ÷ 2 = 275 + 0;
  • 275 ÷ 2 = 137 + 1;
  • 137 ÷ 2 = 68 + 1;
  • 68 ÷ 2 = 34 + 0;
  • 34 ÷ 2 = 17 + 0;
  • 17 ÷ 2 = 8 + 1;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

2. 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.

8 800(10) =


10 0010 0110 0000(2)


3. Convert to binary (base 2) the fractional part: 0.883 411 943 535 971 3.

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) 0.883 411 943 535 971 3 × 2 = 1 + 0.766 823 887 071 942 6;
  • 2) 0.766 823 887 071 942 6 × 2 = 1 + 0.533 647 774 143 885 2;
  • 3) 0.533 647 774 143 885 2 × 2 = 1 + 0.067 295 548 287 770 4;
  • 4) 0.067 295 548 287 770 4 × 2 = 0 + 0.134 591 096 575 540 8;
  • 5) 0.134 591 096 575 540 8 × 2 = 0 + 0.269 182 193 151 081 6;
  • 6) 0.269 182 193 151 081 6 × 2 = 0 + 0.538 364 386 302 163 2;
  • 7) 0.538 364 386 302 163 2 × 2 = 1 + 0.076 728 772 604 326 4;
  • 8) 0.076 728 772 604 326 4 × 2 = 0 + 0.153 457 545 208 652 8;
  • 9) 0.153 457 545 208 652 8 × 2 = 0 + 0.306 915 090 417 305 6;
  • 10) 0.306 915 090 417 305 6 × 2 = 0 + 0.613 830 180 834 611 2;
  • 11) 0.613 830 180 834 611 2 × 2 = 1 + 0.227 660 361 669 222 4;
  • 12) 0.227 660 361 669 222 4 × 2 = 0 + 0.455 320 723 338 444 8;
  • 13) 0.455 320 723 338 444 8 × 2 = 0 + 0.910 641 446 676 889 6;
  • 14) 0.910 641 446 676 889 6 × 2 = 1 + 0.821 282 893 353 779 2;
  • 15) 0.821 282 893 353 779 2 × 2 = 1 + 0.642 565 786 707 558 4;
  • 16) 0.642 565 786 707 558 4 × 2 = 1 + 0.285 131 573 415 116 8;
  • 17) 0.285 131 573 415 116 8 × 2 = 0 + 0.570 263 146 830 233 6;
  • 18) 0.570 263 146 830 233 6 × 2 = 1 + 0.140 526 293 660 467 2;
  • 19) 0.140 526 293 660 467 2 × 2 = 0 + 0.281 052 587 320 934 4;
  • 20) 0.281 052 587 320 934 4 × 2 = 0 + 0.562 105 174 641 868 8;
  • 21) 0.562 105 174 641 868 8 × 2 = 1 + 0.124 210 349 283 737 6;
  • 22) 0.124 210 349 283 737 6 × 2 = 0 + 0.248 420 698 567 475 2;
  • 23) 0.248 420 698 567 475 2 × 2 = 0 + 0.496 841 397 134 950 4;
  • 24) 0.496 841 397 134 950 4 × 2 = 0 + 0.993 682 794 269 900 8;
  • 25) 0.993 682 794 269 900 8 × 2 = 1 + 0.987 365 588 539 801 6;
  • 26) 0.987 365 588 539 801 6 × 2 = 1 + 0.974 731 177 079 603 2;
  • 27) 0.974 731 177 079 603 2 × 2 = 1 + 0.949 462 354 159 206 4;
  • 28) 0.949 462 354 159 206 4 × 2 = 1 + 0.898 924 708 318 412 8;
  • 29) 0.898 924 708 318 412 8 × 2 = 1 + 0.797 849 416 636 825 6;
  • 30) 0.797 849 416 636 825 6 × 2 = 1 + 0.595 698 833 273 651 2;
  • 31) 0.595 698 833 273 651 2 × 2 = 1 + 0.191 397 666 547 302 4;
  • 32) 0.191 397 666 547 302 4 × 2 = 0 + 0.382 795 333 094 604 8;
  • 33) 0.382 795 333 094 604 8 × 2 = 0 + 0.765 590 666 189 209 6;
  • 34) 0.765 590 666 189 209 6 × 2 = 1 + 0.531 181 332 378 419 2;
  • 35) 0.531 181 332 378 419 2 × 2 = 1 + 0.062 362 664 756 838 4;
  • 36) 0.062 362 664 756 838 4 × 2 = 0 + 0.124 725 329 513 676 8;
  • 37) 0.124 725 329 513 676 8 × 2 = 0 + 0.249 450 659 027 353 6;
  • 38) 0.249 450 659 027 353 6 × 2 = 0 + 0.498 901 318 054 707 2;
  • 39) 0.498 901 318 054 707 2 × 2 = 0 + 0.997 802 636 109 414 4;
  • 40) 0.997 802 636 109 414 4 × 2 = 1 + 0.995 605 272 218 828 8;
  • 41) 0.995 605 272 218 828 8 × 2 = 1 + 0.991 210 544 437 657 6;
  • 42) 0.991 210 544 437 657 6 × 2 = 1 + 0.982 421 088 875 315 2;
  • 43) 0.982 421 088 875 315 2 × 2 = 1 + 0.964 842 177 750 630 4;
  • 44) 0.964 842 177 750 630 4 × 2 = 1 + 0.929 684 355 501 260 8;
  • 45) 0.929 684 355 501 260 8 × 2 = 1 + 0.859 368 711 002 521 6;
  • 46) 0.859 368 711 002 521 6 × 2 = 1 + 0.718 737 422 005 043 2;
  • 47) 0.718 737 422 005 043 2 × 2 = 1 + 0.437 474 844 010 086 4;
  • 48) 0.437 474 844 010 086 4 × 2 = 0 + 0.874 949 688 020 172 8;
  • 49) 0.874 949 688 020 172 8 × 2 = 1 + 0.749 899 376 040 345 6;
  • 50) 0.749 899 376 040 345 6 × 2 = 1 + 0.499 798 752 080 691 2;
  • 51) 0.499 798 752 080 691 2 × 2 = 0 + 0.999 597 504 161 382 4;
  • 52) 0.999 597 504 161 382 4 × 2 = 1 + 0.999 195 008 322 764 8;
  • 53) 0.999 195 008 322 764 8 × 2 = 1 + 0.998 390 016 645 529 6;

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).


4. 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:


0.883 411 943 535 971 3(10) =


0.1110 0010 0010 0111 0100 1000 1111 1110 0110 0001 1111 1110 1101 1(2)

5. Positive number before normalization:

8 800.883 411 943 535 971 3(10) =


10 0010 0110 0000.1110 0010 0010 0111 0100 1000 1111 1110 0110 0001 1111 1110 1101 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 13 positions to the left, so that only one non zero digit remains to the left of it:


8 800.883 411 943 535 971 3(10) =


10 0010 0110 0000.1110 0010 0010 0111 0100 1000 1111 1110 0110 0001 1111 1110 1101 1(2) =


10 0010 0110 0000.1110 0010 0010 0111 0100 1000 1111 1110 0110 0001 1111 1110 1101 1(2) × 20 =


1.0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0000 1111 1111 0110 11(2) × 213


7. 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 0 (a positive number)


Exponent (unadjusted): 13


Mantissa (not normalized):
1.0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0000 1111 1111 0110 11


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


13 + 2(11-1) - 1 =


(13 + 1 023)(10) =


1 036(10)


9. 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;
  • 1 036 ÷ 2 = 518 + 0;
  • 518 ÷ 2 = 259 + 0;
  • 259 ÷ 2 = 129 + 1;
  • 129 ÷ 2 = 64 + 1;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

10. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1036(10) =


100 0000 1100(2)


11. 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, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0000 11 1111 1101 1011 =


0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0000


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
100 0000 1100


Mantissa (52 bits) =
0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0000


Decimal number 8 800.883 411 943 535 971 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1100 - 0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0000


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