17.035 499 999 997 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 17.035 499 999 997 9(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
17.035 499 999 997 9(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: 17.
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;
  • 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.

17(10) =


1 0001(2)


3. Convert to binary (base 2) the fractional part: 0.035 499 999 997 9.

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) 0.035 499 999 997 9 × 2 = 0 + 0.070 999 999 995 8;
  • 2) 0.070 999 999 995 8 × 2 = 0 + 0.141 999 999 991 6;
  • 3) 0.141 999 999 991 6 × 2 = 0 + 0.283 999 999 983 2;
  • 4) 0.283 999 999 983 2 × 2 = 0 + 0.567 999 999 966 4;
  • 5) 0.567 999 999 966 4 × 2 = 1 + 0.135 999 999 932 8;
  • 6) 0.135 999 999 932 8 × 2 = 0 + 0.271 999 999 865 6;
  • 7) 0.271 999 999 865 6 × 2 = 0 + 0.543 999 999 731 2;
  • 8) 0.543 999 999 731 2 × 2 = 1 + 0.087 999 999 462 4;
  • 9) 0.087 999 999 462 4 × 2 = 0 + 0.175 999 998 924 8;
  • 10) 0.175 999 998 924 8 × 2 = 0 + 0.351 999 997 849 6;
  • 11) 0.351 999 997 849 6 × 2 = 0 + 0.703 999 995 699 2;
  • 12) 0.703 999 995 699 2 × 2 = 1 + 0.407 999 991 398 4;
  • 13) 0.407 999 991 398 4 × 2 = 0 + 0.815 999 982 796 8;
  • 14) 0.815 999 982 796 8 × 2 = 1 + 0.631 999 965 593 6;
  • 15) 0.631 999 965 593 6 × 2 = 1 + 0.263 999 931 187 2;
  • 16) 0.263 999 931 187 2 × 2 = 0 + 0.527 999 862 374 4;
  • 17) 0.527 999 862 374 4 × 2 = 1 + 0.055 999 724 748 8;
  • 18) 0.055 999 724 748 8 × 2 = 0 + 0.111 999 449 497 6;
  • 19) 0.111 999 449 497 6 × 2 = 0 + 0.223 998 898 995 2;
  • 20) 0.223 998 898 995 2 × 2 = 0 + 0.447 997 797 990 4;
  • 21) 0.447 997 797 990 4 × 2 = 0 + 0.895 995 595 980 8;
  • 22) 0.895 995 595 980 8 × 2 = 1 + 0.791 991 191 961 6;
  • 23) 0.791 991 191 961 6 × 2 = 1 + 0.583 982 383 923 2;
  • 24) 0.583 982 383 923 2 × 2 = 1 + 0.167 964 767 846 4;
  • 25) 0.167 964 767 846 4 × 2 = 0 + 0.335 929 535 692 8;
  • 26) 0.335 929 535 692 8 × 2 = 0 + 0.671 859 071 385 6;
  • 27) 0.671 859 071 385 6 × 2 = 1 + 0.343 718 142 771 2;
  • 28) 0.343 718 142 771 2 × 2 = 0 + 0.687 436 285 542 4;
  • 29) 0.687 436 285 542 4 × 2 = 1 + 0.374 872 571 084 8;
  • 30) 0.374 872 571 084 8 × 2 = 0 + 0.749 745 142 169 6;
  • 31) 0.749 745 142 169 6 × 2 = 1 + 0.499 490 284 339 2;
  • 32) 0.499 490 284 339 2 × 2 = 0 + 0.998 980 568 678 4;
  • 33) 0.998 980 568 678 4 × 2 = 1 + 0.997 961 137 356 8;
  • 34) 0.997 961 137 356 8 × 2 = 1 + 0.995 922 274 713 6;
  • 35) 0.995 922 274 713 6 × 2 = 1 + 0.991 844 549 427 2;
  • 36) 0.991 844 549 427 2 × 2 = 1 + 0.983 689 098 854 4;
  • 37) 0.983 689 098 854 4 × 2 = 1 + 0.967 378 197 708 8;
  • 38) 0.967 378 197 708 8 × 2 = 1 + 0.934 756 395 417 6;
  • 39) 0.934 756 395 417 6 × 2 = 1 + 0.869 512 790 835 2;
  • 40) 0.869 512 790 835 2 × 2 = 1 + 0.739 025 581 670 4;
  • 41) 0.739 025 581 670 4 × 2 = 1 + 0.478 051 163 340 8;
  • 42) 0.478 051 163 340 8 × 2 = 0 + 0.956 102 326 681 6;
  • 43) 0.956 102 326 681 6 × 2 = 1 + 0.912 204 653 363 2;
  • 44) 0.912 204 653 363 2 × 2 = 1 + 0.824 409 306 726 4;
  • 45) 0.824 409 306 726 4 × 2 = 1 + 0.648 818 613 452 8;
  • 46) 0.648 818 613 452 8 × 2 = 1 + 0.297 637 226 905 6;
  • 47) 0.297 637 226 905 6 × 2 = 0 + 0.595 274 453 811 2;
  • 48) 0.595 274 453 811 2 × 2 = 1 + 0.190 548 907 622 4;
  • 49) 0.190 548 907 622 4 × 2 = 0 + 0.381 097 815 244 8;
  • 50) 0.381 097 815 244 8 × 2 = 0 + 0.762 195 630 489 6;
  • 51) 0.762 195 630 489 6 × 2 = 1 + 0.524 391 260 979 2;
  • 52) 0.524 391 260 979 2 × 2 = 1 + 0.048 782 521 958 4;
  • 53) 0.048 782 521 958 4 × 2 = 0 + 0.097 565 043 916 8;

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:


0.035 499 999 997 9(10) =


0.0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101 0011 0(2)

5. Positive number before normalization:

17.035 499 999 997 9(10) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101 0011 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the left, so that only one non zero digit remains to the left of it:


17.035 499 999 997 9(10) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101 0011 0(2) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101 0011 0(2) × 20 =


1.0001 0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101 0011 0(2) × 24


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): 4


Mantissa (not normalized):
1.0001 0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101 0011 0


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


4 + 2(11-1) - 1 =


(4 + 1 023)(10) =


1 027(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;
  • 1 027 ÷ 2 = 513 + 1;
  • 513 ÷ 2 = 256 + 1;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 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) =


1027(10) =


100 0000 0011(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 0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101 0 0110 =


0001 0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101


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 0011


Mantissa (52 bits) =
0001 0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101


Decimal number 17.035 499 999 997 9 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0011 - 0001 0000 1001 0001 0110 1000 0111 0010 1010 1111 1111 1011 1101


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