Decimal to 64 Bit IEEE 754 Binary: Convert Number 490 892 359 490 122 710 to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From Base Ten Decimal System

Number 490 892 359 490 122 710(10) converted and written in 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. 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;
  • 490 892 359 490 122 710 ÷ 2 = 245 446 179 745 061 355 + 0;
  • 245 446 179 745 061 355 ÷ 2 = 122 723 089 872 530 677 + 1;
  • 122 723 089 872 530 677 ÷ 2 = 61 361 544 936 265 338 + 1;
  • 61 361 544 936 265 338 ÷ 2 = 30 680 772 468 132 669 + 0;
  • 30 680 772 468 132 669 ÷ 2 = 15 340 386 234 066 334 + 1;
  • 15 340 386 234 066 334 ÷ 2 = 7 670 193 117 033 167 + 0;
  • 7 670 193 117 033 167 ÷ 2 = 3 835 096 558 516 583 + 1;
  • 3 835 096 558 516 583 ÷ 2 = 1 917 548 279 258 291 + 1;
  • 1 917 548 279 258 291 ÷ 2 = 958 774 139 629 145 + 1;
  • 958 774 139 629 145 ÷ 2 = 479 387 069 814 572 + 1;
  • 479 387 069 814 572 ÷ 2 = 239 693 534 907 286 + 0;
  • 239 693 534 907 286 ÷ 2 = 119 846 767 453 643 + 0;
  • 119 846 767 453 643 ÷ 2 = 59 923 383 726 821 + 1;
  • 59 923 383 726 821 ÷ 2 = 29 961 691 863 410 + 1;
  • 29 961 691 863 410 ÷ 2 = 14 980 845 931 705 + 0;
  • 14 980 845 931 705 ÷ 2 = 7 490 422 965 852 + 1;
  • 7 490 422 965 852 ÷ 2 = 3 745 211 482 926 + 0;
  • 3 745 211 482 926 ÷ 2 = 1 872 605 741 463 + 0;
  • 1 872 605 741 463 ÷ 2 = 936 302 870 731 + 1;
  • 936 302 870 731 ÷ 2 = 468 151 435 365 + 1;
  • 468 151 435 365 ÷ 2 = 234 075 717 682 + 1;
  • 234 075 717 682 ÷ 2 = 117 037 858 841 + 0;
  • 117 037 858 841 ÷ 2 = 58 518 929 420 + 1;
  • 58 518 929 420 ÷ 2 = 29 259 464 710 + 0;
  • 29 259 464 710 ÷ 2 = 14 629 732 355 + 0;
  • 14 629 732 355 ÷ 2 = 7 314 866 177 + 1;
  • 7 314 866 177 ÷ 2 = 3 657 433 088 + 1;
  • 3 657 433 088 ÷ 2 = 1 828 716 544 + 0;
  • 1 828 716 544 ÷ 2 = 914 358 272 + 0;
  • 914 358 272 ÷ 2 = 457 179 136 + 0;
  • 457 179 136 ÷ 2 = 228 589 568 + 0;
  • 228 589 568 ÷ 2 = 114 294 784 + 0;
  • 114 294 784 ÷ 2 = 57 147 392 + 0;
  • 57 147 392 ÷ 2 = 28 573 696 + 0;
  • 28 573 696 ÷ 2 = 14 286 848 + 0;
  • 14 286 848 ÷ 2 = 7 143 424 + 0;
  • 7 143 424 ÷ 2 = 3 571 712 + 0;
  • 3 571 712 ÷ 2 = 1 785 856 + 0;
  • 1 785 856 ÷ 2 = 892 928 + 0;
  • 892 928 ÷ 2 = 446 464 + 0;
  • 446 464 ÷ 2 = 223 232 + 0;
  • 223 232 ÷ 2 = 111 616 + 0;
  • 111 616 ÷ 2 = 55 808 + 0;
  • 55 808 ÷ 2 = 27 904 + 0;
  • 27 904 ÷ 2 = 13 952 + 0;
  • 13 952 ÷ 2 = 6 976 + 0;
  • 6 976 ÷ 2 = 3 488 + 0;
  • 3 488 ÷ 2 = 1 744 + 0;
  • 1 744 ÷ 2 = 872 + 0;
  • 872 ÷ 2 = 436 + 0;
  • 436 ÷ 2 = 218 + 0;
  • 218 ÷ 2 = 109 + 0;
  • 109 ÷ 2 = 54 + 1;
  • 54 ÷ 2 = 27 + 0;
  • 27 ÷ 2 = 13 + 1;
  • 13 ÷ 2 = 6 + 1;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the positive number.

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

490 892 359 490 122 710(10) =


110 1101 0000 0000 0000 0000 0000 0000 0110 0101 1100 1011 0011 1101 0110(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 58 positions to the left, so that only one non zero digit remains to the left of it:


490 892 359 490 122 710(10) =


110 1101 0000 0000 0000 0000 0000 0000 0110 0101 1100 1011 0011 1101 0110(2) =


110 1101 0000 0000 0000 0000 0000 0000 0110 0101 1100 1011 0011 1101 0110(2) × 20 =


1.1011 0100 0000 0000 0000 0000 0000 0001 1001 0111 0010 1100 1111 0101 10(2) × 258


4. 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): 58


Mantissa (not normalized):
1.1011 0100 0000 0000 0000 0000 0000 0001 1001 0111 0010 1100 1111 0101 10


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


58 + 2(11-1) - 1 =


(58 + 1 023)(10) =


1 081(10)


6. 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;
  • 1 081 ÷ 2 = 540 + 1;
  • 540 ÷ 2 = 270 + 0;
  • 270 ÷ 2 = 135 + 0;
  • 135 ÷ 2 = 67 + 1;
  • 67 ÷ 2 = 33 + 1;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


1081(10) =


100 0011 1001(2)


8. 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. 1011 0100 0000 0000 0000 0000 0000 0001 1001 0111 0010 1100 1111 01 0110 =


1011 0100 0000 0000 0000 0000 0000 0001 1001 0111 0010 1100 1111


9. 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 0011 1001


Mantissa (52 bits) =
1011 0100 0000 0000 0000 0000 0000 0001 1001 0111 0010 1100 1111


The base ten decimal number 490 892 359 490 122 710 converted and written in 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0011 1001 - 1011 0100 0000 0000 0000 0000 0000 0001 1001 0111 0010 1100 1111

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