17.035 500 000 000 016 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 17.035 500 000 000 016 6(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
17.035 500 000 000 016 6(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: 0.035 500 000 000 016 6.

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) 0.035 500 000 000 016 6 × 2 = 0 + 0.071 000 000 000 033 2;
  • 2) 0.071 000 000 000 033 2 × 2 = 0 + 0.142 000 000 000 066 4;
  • 3) 0.142 000 000 000 066 4 × 2 = 0 + 0.284 000 000 000 132 8;
  • 4) 0.284 000 000 000 132 8 × 2 = 0 + 0.568 000 000 000 265 6;
  • 5) 0.568 000 000 000 265 6 × 2 = 1 + 0.136 000 000 000 531 2;
  • 6) 0.136 000 000 000 531 2 × 2 = 0 + 0.272 000 000 001 062 4;
  • 7) 0.272 000 000 001 062 4 × 2 = 0 + 0.544 000 000 002 124 8;
  • 8) 0.544 000 000 002 124 8 × 2 = 1 + 0.088 000 000 004 249 6;
  • 9) 0.088 000 000 004 249 6 × 2 = 0 + 0.176 000 000 008 499 2;
  • 10) 0.176 000 000 008 499 2 × 2 = 0 + 0.352 000 000 016 998 4;
  • 11) 0.352 000 000 016 998 4 × 2 = 0 + 0.704 000 000 033 996 8;
  • 12) 0.704 000 000 033 996 8 × 2 = 1 + 0.408 000 000 067 993 6;
  • 13) 0.408 000 000 067 993 6 × 2 = 0 + 0.816 000 000 135 987 2;
  • 14) 0.816 000 000 135 987 2 × 2 = 1 + 0.632 000 000 271 974 4;
  • 15) 0.632 000 000 271 974 4 × 2 = 1 + 0.264 000 000 543 948 8;
  • 16) 0.264 000 000 543 948 8 × 2 = 0 + 0.528 000 001 087 897 6;
  • 17) 0.528 000 001 087 897 6 × 2 = 1 + 0.056 000 002 175 795 2;
  • 18) 0.056 000 002 175 795 2 × 2 = 0 + 0.112 000 004 351 590 4;
  • 19) 0.112 000 004 351 590 4 × 2 = 0 + 0.224 000 008 703 180 8;
  • 20) 0.224 000 008 703 180 8 × 2 = 0 + 0.448 000 017 406 361 6;
  • 21) 0.448 000 017 406 361 6 × 2 = 0 + 0.896 000 034 812 723 2;
  • 22) 0.896 000 034 812 723 2 × 2 = 1 + 0.792 000 069 625 446 4;
  • 23) 0.792 000 069 625 446 4 × 2 = 1 + 0.584 000 139 250 892 8;
  • 24) 0.584 000 139 250 892 8 × 2 = 1 + 0.168 000 278 501 785 6;
  • 25) 0.168 000 278 501 785 6 × 2 = 0 + 0.336 000 557 003 571 2;
  • 26) 0.336 000 557 003 571 2 × 2 = 0 + 0.672 001 114 007 142 4;
  • 27) 0.672 001 114 007 142 4 × 2 = 1 + 0.344 002 228 014 284 8;
  • 28) 0.344 002 228 014 284 8 × 2 = 0 + 0.688 004 456 028 569 6;
  • 29) 0.688 004 456 028 569 6 × 2 = 1 + 0.376 008 912 057 139 2;
  • 30) 0.376 008 912 057 139 2 × 2 = 0 + 0.752 017 824 114 278 4;
  • 31) 0.752 017 824 114 278 4 × 2 = 1 + 0.504 035 648 228 556 8;
  • 32) 0.504 035 648 228 556 8 × 2 = 1 + 0.008 071 296 457 113 6;
  • 33) 0.008 071 296 457 113 6 × 2 = 0 + 0.016 142 592 914 227 2;
  • 34) 0.016 142 592 914 227 2 × 2 = 0 + 0.032 285 185 828 454 4;
  • 35) 0.032 285 185 828 454 4 × 2 = 0 + 0.064 570 371 656 908 8;
  • 36) 0.064 570 371 656 908 8 × 2 = 0 + 0.129 140 743 313 817 6;
  • 37) 0.129 140 743 313 817 6 × 2 = 0 + 0.258 281 486 627 635 2;
  • 38) 0.258 281 486 627 635 2 × 2 = 0 + 0.516 562 973 255 270 4;
  • 39) 0.516 562 973 255 270 4 × 2 = 1 + 0.033 125 946 510 540 8;
  • 40) 0.033 125 946 510 540 8 × 2 = 0 + 0.066 251 893 021 081 6;
  • 41) 0.066 251 893 021 081 6 × 2 = 0 + 0.132 503 786 042 163 2;
  • 42) 0.132 503 786 042 163 2 × 2 = 0 + 0.265 007 572 084 326 4;
  • 43) 0.265 007 572 084 326 4 × 2 = 0 + 0.530 015 144 168 652 8;
  • 44) 0.530 015 144 168 652 8 × 2 = 1 + 0.060 030 288 337 305 6;
  • 45) 0.060 030 288 337 305 6 × 2 = 0 + 0.120 060 576 674 611 2;
  • 46) 0.120 060 576 674 611 2 × 2 = 0 + 0.240 121 153 349 222 4;
  • 47) 0.240 121 153 349 222 4 × 2 = 0 + 0.480 242 306 698 444 8;
  • 48) 0.480 242 306 698 444 8 × 2 = 0 + 0.960 484 613 396 889 6;
  • 49) 0.960 484 613 396 889 6 × 2 = 1 + 0.920 969 226 793 779 2;
  • 50) 0.920 969 226 793 779 2 × 2 = 1 + 0.841 938 453 587 558 4;
  • 51) 0.841 938 453 587 558 4 × 2 = 1 + 0.683 876 907 175 116 8;
  • 52) 0.683 876 907 175 116 8 × 2 = 1 + 0.367 753 814 350 233 6;
  • 53) 0.367 753 814 350 233 6 × 2 = 0 + 0.735 507 628 700 467 2;

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:


0.035 500 000 000 016 6(10) =


0.0000 1001 0001 0110 1000 0111 0010 1011 0000 0010 0001 0000 1111 0(2)

5. Positive number before normalization:

17.035 500 000 000 016 6(10) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1011 0000 0010 0001 0000 1111 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:


17.035 500 000 000 016 6(10) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1011 0000 0010 0001 0000 1111 0(2) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1011 0000 0010 0001 0000 1111 0(2) × 20 =


1.0001 0000 1001 0001 0110 1000 0111 0010 1011 0000 0010 0001 0000 1111 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 1011 0000 0010 0001 0000 1111 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 1011 0000 0010 0001 0000 1 1110 =


0001 0000 1001 0001 0110 1000 0111 0010 1011 0000 0010 0001 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 0011


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


Decimal number 17.035 500 000 000 016 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

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