10 000.555 555 555 555 592 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 10 000.555 555 555 555 592(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
10 000.555 555 555 555 592(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: 10 000.
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;
  • 10 000 ÷ 2 = 5 000 + 0;
  • 5 000 ÷ 2 = 2 500 + 0;
  • 2 500 ÷ 2 = 1 250 + 0;
  • 1 250 ÷ 2 = 625 + 0;
  • 625 ÷ 2 = 312 + 1;
  • 312 ÷ 2 = 156 + 0;
  • 156 ÷ 2 = 78 + 0;
  • 78 ÷ 2 = 39 + 0;
  • 39 ÷ 2 = 19 + 1;
  • 19 ÷ 2 = 9 + 1;
  • 9 ÷ 2 = 4 + 1;
  • 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.

10 000(10) =


10 0111 0001 0000(2)


3. Convert to binary (base 2) the fractional part: 0.555 555 555 555 592.

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) 0.555 555 555 555 592 × 2 = 1 + 0.111 111 111 111 184;
  • 2) 0.111 111 111 111 184 × 2 = 0 + 0.222 222 222 222 368;
  • 3) 0.222 222 222 222 368 × 2 = 0 + 0.444 444 444 444 736;
  • 4) 0.444 444 444 444 736 × 2 = 0 + 0.888 888 888 889 472;
  • 5) 0.888 888 888 889 472 × 2 = 1 + 0.777 777 777 778 944;
  • 6) 0.777 777 777 778 944 × 2 = 1 + 0.555 555 555 557 888;
  • 7) 0.555 555 555 557 888 × 2 = 1 + 0.111 111 111 115 776;
  • 8) 0.111 111 111 115 776 × 2 = 0 + 0.222 222 222 231 552;
  • 9) 0.222 222 222 231 552 × 2 = 0 + 0.444 444 444 463 104;
  • 10) 0.444 444 444 463 104 × 2 = 0 + 0.888 888 888 926 208;
  • 11) 0.888 888 888 926 208 × 2 = 1 + 0.777 777 777 852 416;
  • 12) 0.777 777 777 852 416 × 2 = 1 + 0.555 555 555 704 832;
  • 13) 0.555 555 555 704 832 × 2 = 1 + 0.111 111 111 409 664;
  • 14) 0.111 111 111 409 664 × 2 = 0 + 0.222 222 222 819 328;
  • 15) 0.222 222 222 819 328 × 2 = 0 + 0.444 444 445 638 656;
  • 16) 0.444 444 445 638 656 × 2 = 0 + 0.888 888 891 277 312;
  • 17) 0.888 888 891 277 312 × 2 = 1 + 0.777 777 782 554 624;
  • 18) 0.777 777 782 554 624 × 2 = 1 + 0.555 555 565 109 248;
  • 19) 0.555 555 565 109 248 × 2 = 1 + 0.111 111 130 218 496;
  • 20) 0.111 111 130 218 496 × 2 = 0 + 0.222 222 260 436 992;
  • 21) 0.222 222 260 436 992 × 2 = 0 + 0.444 444 520 873 984;
  • 22) 0.444 444 520 873 984 × 2 = 0 + 0.888 889 041 747 968;
  • 23) 0.888 889 041 747 968 × 2 = 1 + 0.777 778 083 495 936;
  • 24) 0.777 778 083 495 936 × 2 = 1 + 0.555 556 166 991 872;
  • 25) 0.555 556 166 991 872 × 2 = 1 + 0.111 112 333 983 744;
  • 26) 0.111 112 333 983 744 × 2 = 0 + 0.222 224 667 967 488;
  • 27) 0.222 224 667 967 488 × 2 = 0 + 0.444 449 335 934 976;
  • 28) 0.444 449 335 934 976 × 2 = 0 + 0.888 898 671 869 952;
  • 29) 0.888 898 671 869 952 × 2 = 1 + 0.777 797 343 739 904;
  • 30) 0.777 797 343 739 904 × 2 = 1 + 0.555 594 687 479 808;
  • 31) 0.555 594 687 479 808 × 2 = 1 + 0.111 189 374 959 616;
  • 32) 0.111 189 374 959 616 × 2 = 0 + 0.222 378 749 919 232;
  • 33) 0.222 378 749 919 232 × 2 = 0 + 0.444 757 499 838 464;
  • 34) 0.444 757 499 838 464 × 2 = 0 + 0.889 514 999 676 928;
  • 35) 0.889 514 999 676 928 × 2 = 1 + 0.779 029 999 353 856;
  • 36) 0.779 029 999 353 856 × 2 = 1 + 0.558 059 998 707 712;
  • 37) 0.558 059 998 707 712 × 2 = 1 + 0.116 119 997 415 424;
  • 38) 0.116 119 997 415 424 × 2 = 0 + 0.232 239 994 830 848;
  • 39) 0.232 239 994 830 848 × 2 = 0 + 0.464 479 989 661 696;
  • 40) 0.464 479 989 661 696 × 2 = 0 + 0.928 959 979 323 392;
  • 41) 0.928 959 979 323 392 × 2 = 1 + 0.857 919 958 646 784;
  • 42) 0.857 919 958 646 784 × 2 = 1 + 0.715 839 917 293 568;
  • 43) 0.715 839 917 293 568 × 2 = 1 + 0.431 679 834 587 136;
  • 44) 0.431 679 834 587 136 × 2 = 0 + 0.863 359 669 174 272;
  • 45) 0.863 359 669 174 272 × 2 = 1 + 0.726 719 338 348 544;
  • 46) 0.726 719 338 348 544 × 2 = 1 + 0.453 438 676 697 088;
  • 47) 0.453 438 676 697 088 × 2 = 0 + 0.906 877 353 394 176;
  • 48) 0.906 877 353 394 176 × 2 = 1 + 0.813 754 706 788 352;
  • 49) 0.813 754 706 788 352 × 2 = 1 + 0.627 509 413 576 704;
  • 50) 0.627 509 413 576 704 × 2 = 1 + 0.255 018 827 153 408;
  • 51) 0.255 018 827 153 408 × 2 = 0 + 0.510 037 654 306 816;
  • 52) 0.510 037 654 306 816 × 2 = 1 + 0.020 075 308 613 632;
  • 53) 0.020 075 308 613 632 × 2 = 0 + 0.040 150 617 227 264;

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:


0.555 555 555 555 592(10) =


0.1000 1110 0011 1000 1110 0011 1000 1110 0011 1000 1110 1101 1101 0(2)

5. Positive number before normalization:

10 000.555 555 555 555 592(10) =


10 0111 0001 0000.1000 1110 0011 1000 1110 0011 1000 1110 0011 1000 1110 1101 1101 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:


10 000.555 555 555 555 592(10) =


10 0111 0001 0000.1000 1110 0011 1000 1110 0011 1000 1110 0011 1000 1110 1101 1101 0(2) =


10 0111 0001 0000.1000 1110 0011 1000 1110 0011 1000 1110 0011 1000 1110 1101 1101 0(2) × 20 =


1.0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0110 1110 10(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):
1.0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100 0111 0110 1110 10


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. 0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100 01 1101 1011 1010 =


0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100


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) =
0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100


Decimal number 10 000.555 555 555 555 592 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1100 - 0011 1000 1000 0100 0111 0001 1100 0111 0001 1100 0111 0001 1100


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