17.035 500 000 004 4 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 17.035 500 000 004 4(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
17.035 500 000 004 4(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: 0.035 500 000 004 4.

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) 0.035 500 000 004 4 × 2 = 0 + 0.071 000 000 008 8;
  • 2) 0.071 000 000 008 8 × 2 = 0 + 0.142 000 000 017 6;
  • 3) 0.142 000 000 017 6 × 2 = 0 + 0.284 000 000 035 2;
  • 4) 0.284 000 000 035 2 × 2 = 0 + 0.568 000 000 070 4;
  • 5) 0.568 000 000 070 4 × 2 = 1 + 0.136 000 000 140 8;
  • 6) 0.136 000 000 140 8 × 2 = 0 + 0.272 000 000 281 6;
  • 7) 0.272 000 000 281 6 × 2 = 0 + 0.544 000 000 563 2;
  • 8) 0.544 000 000 563 2 × 2 = 1 + 0.088 000 001 126 4;
  • 9) 0.088 000 001 126 4 × 2 = 0 + 0.176 000 002 252 8;
  • 10) 0.176 000 002 252 8 × 2 = 0 + 0.352 000 004 505 6;
  • 11) 0.352 000 004 505 6 × 2 = 0 + 0.704 000 009 011 2;
  • 12) 0.704 000 009 011 2 × 2 = 1 + 0.408 000 018 022 4;
  • 13) 0.408 000 018 022 4 × 2 = 0 + 0.816 000 036 044 8;
  • 14) 0.816 000 036 044 8 × 2 = 1 + 0.632 000 072 089 6;
  • 15) 0.632 000 072 089 6 × 2 = 1 + 0.264 000 144 179 2;
  • 16) 0.264 000 144 179 2 × 2 = 0 + 0.528 000 288 358 4;
  • 17) 0.528 000 288 358 4 × 2 = 1 + 0.056 000 576 716 8;
  • 18) 0.056 000 576 716 8 × 2 = 0 + 0.112 001 153 433 6;
  • 19) 0.112 001 153 433 6 × 2 = 0 + 0.224 002 306 867 2;
  • 20) 0.224 002 306 867 2 × 2 = 0 + 0.448 004 613 734 4;
  • 21) 0.448 004 613 734 4 × 2 = 0 + 0.896 009 227 468 8;
  • 22) 0.896 009 227 468 8 × 2 = 1 + 0.792 018 454 937 6;
  • 23) 0.792 018 454 937 6 × 2 = 1 + 0.584 036 909 875 2;
  • 24) 0.584 036 909 875 2 × 2 = 1 + 0.168 073 819 750 4;
  • 25) 0.168 073 819 750 4 × 2 = 0 + 0.336 147 639 500 8;
  • 26) 0.336 147 639 500 8 × 2 = 0 + 0.672 295 279 001 6;
  • 27) 0.672 295 279 001 6 × 2 = 1 + 0.344 590 558 003 2;
  • 28) 0.344 590 558 003 2 × 2 = 0 + 0.689 181 116 006 4;
  • 29) 0.689 181 116 006 4 × 2 = 1 + 0.378 362 232 012 8;
  • 30) 0.378 362 232 012 8 × 2 = 0 + 0.756 724 464 025 6;
  • 31) 0.756 724 464 025 6 × 2 = 1 + 0.513 448 928 051 2;
  • 32) 0.513 448 928 051 2 × 2 = 1 + 0.026 897 856 102 4;
  • 33) 0.026 897 856 102 4 × 2 = 0 + 0.053 795 712 204 8;
  • 34) 0.053 795 712 204 8 × 2 = 0 + 0.107 591 424 409 6;
  • 35) 0.107 591 424 409 6 × 2 = 0 + 0.215 182 848 819 2;
  • 36) 0.215 182 848 819 2 × 2 = 0 + 0.430 365 697 638 4;
  • 37) 0.430 365 697 638 4 × 2 = 0 + 0.860 731 395 276 8;
  • 38) 0.860 731 395 276 8 × 2 = 1 + 0.721 462 790 553 6;
  • 39) 0.721 462 790 553 6 × 2 = 1 + 0.442 925 581 107 2;
  • 40) 0.442 925 581 107 2 × 2 = 0 + 0.885 851 162 214 4;
  • 41) 0.885 851 162 214 4 × 2 = 1 + 0.771 702 324 428 8;
  • 42) 0.771 702 324 428 8 × 2 = 1 + 0.543 404 648 857 6;
  • 43) 0.543 404 648 857 6 × 2 = 1 + 0.086 809 297 715 2;
  • 44) 0.086 809 297 715 2 × 2 = 0 + 0.173 618 595 430 4;
  • 45) 0.173 618 595 430 4 × 2 = 0 + 0.347 237 190 860 8;
  • 46) 0.347 237 190 860 8 × 2 = 0 + 0.694 474 381 721 6;
  • 47) 0.694 474 381 721 6 × 2 = 1 + 0.388 948 763 443 2;
  • 48) 0.388 948 763 443 2 × 2 = 0 + 0.777 897 526 886 4;
  • 49) 0.777 897 526 886 4 × 2 = 1 + 0.555 795 053 772 8;
  • 50) 0.555 795 053 772 8 × 2 = 1 + 0.111 590 107 545 6;
  • 51) 0.111 590 107 545 6 × 2 = 0 + 0.223 180 215 091 2;
  • 52) 0.223 180 215 091 2 × 2 = 0 + 0.446 360 430 182 4;
  • 53) 0.446 360 430 182 4 × 2 = 0 + 0.892 720 860 364 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:


0.035 500 000 004 4(10) =


0.0000 1001 0001 0110 1000 0111 0010 1011 0000 0110 1110 0010 1100 0(2)

5. Positive number before normalization:

17.035 500 000 004 4(10) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1011 0000 0110 1110 0010 1100 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:


17.035 500 000 004 4(10) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1011 0000 0110 1110 0010 1100 0(2) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1011 0000 0110 1110 0010 1100 0(2) × 20 =


1.0001 0000 1001 0001 0110 1000 0111 0010 1011 0000 0110 1110 0010 1100 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 0110 1110 0010 1100 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 0110 1110 0010 1 1000 =


0001 0000 1001 0001 0110 1000 0111 0010 1011 0000 0110 1110 0010


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 0110 1110 0010


Decimal number 17.035 500 000 004 4 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 0110 1110 0010


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