8 800.883 411 943 535 974 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 8 800.883 411 943 535 974(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
8 800.883 411 943 535 974(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: 0.883 411 943 535 974.

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) 0.883 411 943 535 974 × 2 = 1 + 0.766 823 887 071 948;
  • 2) 0.766 823 887 071 948 × 2 = 1 + 0.533 647 774 143 896;
  • 3) 0.533 647 774 143 896 × 2 = 1 + 0.067 295 548 287 792;
  • 4) 0.067 295 548 287 792 × 2 = 0 + 0.134 591 096 575 584;
  • 5) 0.134 591 096 575 584 × 2 = 0 + 0.269 182 193 151 168;
  • 6) 0.269 182 193 151 168 × 2 = 0 + 0.538 364 386 302 336;
  • 7) 0.538 364 386 302 336 × 2 = 1 + 0.076 728 772 604 672;
  • 8) 0.076 728 772 604 672 × 2 = 0 + 0.153 457 545 209 344;
  • 9) 0.153 457 545 209 344 × 2 = 0 + 0.306 915 090 418 688;
  • 10) 0.306 915 090 418 688 × 2 = 0 + 0.613 830 180 837 376;
  • 11) 0.613 830 180 837 376 × 2 = 1 + 0.227 660 361 674 752;
  • 12) 0.227 660 361 674 752 × 2 = 0 + 0.455 320 723 349 504;
  • 13) 0.455 320 723 349 504 × 2 = 0 + 0.910 641 446 699 008;
  • 14) 0.910 641 446 699 008 × 2 = 1 + 0.821 282 893 398 016;
  • 15) 0.821 282 893 398 016 × 2 = 1 + 0.642 565 786 796 032;
  • 16) 0.642 565 786 796 032 × 2 = 1 + 0.285 131 573 592 064;
  • 17) 0.285 131 573 592 064 × 2 = 0 + 0.570 263 147 184 128;
  • 18) 0.570 263 147 184 128 × 2 = 1 + 0.140 526 294 368 256;
  • 19) 0.140 526 294 368 256 × 2 = 0 + 0.281 052 588 736 512;
  • 20) 0.281 052 588 736 512 × 2 = 0 + 0.562 105 177 473 024;
  • 21) 0.562 105 177 473 024 × 2 = 1 + 0.124 210 354 946 048;
  • 22) 0.124 210 354 946 048 × 2 = 0 + 0.248 420 709 892 096;
  • 23) 0.248 420 709 892 096 × 2 = 0 + 0.496 841 419 784 192;
  • 24) 0.496 841 419 784 192 × 2 = 0 + 0.993 682 839 568 384;
  • 25) 0.993 682 839 568 384 × 2 = 1 + 0.987 365 679 136 768;
  • 26) 0.987 365 679 136 768 × 2 = 1 + 0.974 731 358 273 536;
  • 27) 0.974 731 358 273 536 × 2 = 1 + 0.949 462 716 547 072;
  • 28) 0.949 462 716 547 072 × 2 = 1 + 0.898 925 433 094 144;
  • 29) 0.898 925 433 094 144 × 2 = 1 + 0.797 850 866 188 288;
  • 30) 0.797 850 866 188 288 × 2 = 1 + 0.595 701 732 376 576;
  • 31) 0.595 701 732 376 576 × 2 = 1 + 0.191 403 464 753 152;
  • 32) 0.191 403 464 753 152 × 2 = 0 + 0.382 806 929 506 304;
  • 33) 0.382 806 929 506 304 × 2 = 0 + 0.765 613 859 012 608;
  • 34) 0.765 613 859 012 608 × 2 = 1 + 0.531 227 718 025 216;
  • 35) 0.531 227 718 025 216 × 2 = 1 + 0.062 455 436 050 432;
  • 36) 0.062 455 436 050 432 × 2 = 0 + 0.124 910 872 100 864;
  • 37) 0.124 910 872 100 864 × 2 = 0 + 0.249 821 744 201 728;
  • 38) 0.249 821 744 201 728 × 2 = 0 + 0.499 643 488 403 456;
  • 39) 0.499 643 488 403 456 × 2 = 0 + 0.999 286 976 806 912;
  • 40) 0.999 286 976 806 912 × 2 = 1 + 0.998 573 953 613 824;
  • 41) 0.998 573 953 613 824 × 2 = 1 + 0.997 147 907 227 648;
  • 42) 0.997 147 907 227 648 × 2 = 1 + 0.994 295 814 455 296;
  • 43) 0.994 295 814 455 296 × 2 = 1 + 0.988 591 628 910 592;
  • 44) 0.988 591 628 910 592 × 2 = 1 + 0.977 183 257 821 184;
  • 45) 0.977 183 257 821 184 × 2 = 1 + 0.954 366 515 642 368;
  • 46) 0.954 366 515 642 368 × 2 = 1 + 0.908 733 031 284 736;
  • 47) 0.908 733 031 284 736 × 2 = 1 + 0.817 466 062 569 472;
  • 48) 0.817 466 062 569 472 × 2 = 1 + 0.634 932 125 138 944;
  • 49) 0.634 932 125 138 944 × 2 = 1 + 0.269 864 250 277 888;
  • 50) 0.269 864 250 277 888 × 2 = 0 + 0.539 728 500 555 776;
  • 51) 0.539 728 500 555 776 × 2 = 1 + 0.079 457 001 111 552;
  • 52) 0.079 457 001 111 552 × 2 = 0 + 0.158 914 002 223 104;
  • 53) 0.158 914 002 223 104 × 2 = 0 + 0.317 828 004 446 208;

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:


0.883 411 943 535 974(10) =


0.1110 0010 0010 0111 0100 1000 1111 1110 0110 0001 1111 1111 1010 0(2)

5. Positive number before normalization:

8 800.883 411 943 535 974(10) =


10 0010 0110 0000.1110 0010 0010 0111 0100 1000 1111 1110 0110 0001 1111 1111 1010 0(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:


8 800.883 411 943 535 974(10) =


10 0010 0110 0000.1110 0010 0010 0111 0100 1000 1111 1110 0110 0001 1111 1111 1010 0(2) =


10 0010 0110 0000.1110 0010 0010 0111 0100 1000 1111 1110 0110 0001 1111 1111 1010 0(2) × 20 =


1.0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0000 1111 1111 1101 00(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 1101 00


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 1111 0100 =


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 8 800.883 411 943 535 974 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