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

Convert decimal 17.035 500 000 000 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
17.035 500 000 000 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: 0.035 500 000 000 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) 0.035 500 000 000 4 × 2 = 0 + 0.071 000 000 000 8;
  • 2) 0.071 000 000 000 8 × 2 = 0 + 0.142 000 000 001 6;
  • 3) 0.142 000 000 001 6 × 2 = 0 + 0.284 000 000 003 2;
  • 4) 0.284 000 000 003 2 × 2 = 0 + 0.568 000 000 006 4;
  • 5) 0.568 000 000 006 4 × 2 = 1 + 0.136 000 000 012 8;
  • 6) 0.136 000 000 012 8 × 2 = 0 + 0.272 000 000 025 6;
  • 7) 0.272 000 000 025 6 × 2 = 0 + 0.544 000 000 051 2;
  • 8) 0.544 000 000 051 2 × 2 = 1 + 0.088 000 000 102 4;
  • 9) 0.088 000 000 102 4 × 2 = 0 + 0.176 000 000 204 8;
  • 10) 0.176 000 000 204 8 × 2 = 0 + 0.352 000 000 409 6;
  • 11) 0.352 000 000 409 6 × 2 = 0 + 0.704 000 000 819 2;
  • 12) 0.704 000 000 819 2 × 2 = 1 + 0.408 000 001 638 4;
  • 13) 0.408 000 001 638 4 × 2 = 0 + 0.816 000 003 276 8;
  • 14) 0.816 000 003 276 8 × 2 = 1 + 0.632 000 006 553 6;
  • 15) 0.632 000 006 553 6 × 2 = 1 + 0.264 000 013 107 2;
  • 16) 0.264 000 013 107 2 × 2 = 0 + 0.528 000 026 214 4;
  • 17) 0.528 000 026 214 4 × 2 = 1 + 0.056 000 052 428 8;
  • 18) 0.056 000 052 428 8 × 2 = 0 + 0.112 000 104 857 6;
  • 19) 0.112 000 104 857 6 × 2 = 0 + 0.224 000 209 715 2;
  • 20) 0.224 000 209 715 2 × 2 = 0 + 0.448 000 419 430 4;
  • 21) 0.448 000 419 430 4 × 2 = 0 + 0.896 000 838 860 8;
  • 22) 0.896 000 838 860 8 × 2 = 1 + 0.792 001 677 721 6;
  • 23) 0.792 001 677 721 6 × 2 = 1 + 0.584 003 355 443 2;
  • 24) 0.584 003 355 443 2 × 2 = 1 + 0.168 006 710 886 4;
  • 25) 0.168 006 710 886 4 × 2 = 0 + 0.336 013 421 772 8;
  • 26) 0.336 013 421 772 8 × 2 = 0 + 0.672 026 843 545 6;
  • 27) 0.672 026 843 545 6 × 2 = 1 + 0.344 053 687 091 2;
  • 28) 0.344 053 687 091 2 × 2 = 0 + 0.688 107 374 182 4;
  • 29) 0.688 107 374 182 4 × 2 = 1 + 0.376 214 748 364 8;
  • 30) 0.376 214 748 364 8 × 2 = 0 + 0.752 429 496 729 6;
  • 31) 0.752 429 496 729 6 × 2 = 1 + 0.504 858 993 459 2;
  • 32) 0.504 858 993 459 2 × 2 = 1 + 0.009 717 986 918 4;
  • 33) 0.009 717 986 918 4 × 2 = 0 + 0.019 435 973 836 8;
  • 34) 0.019 435 973 836 8 × 2 = 0 + 0.038 871 947 673 6;
  • 35) 0.038 871 947 673 6 × 2 = 0 + 0.077 743 895 347 2;
  • 36) 0.077 743 895 347 2 × 2 = 0 + 0.155 487 790 694 4;
  • 37) 0.155 487 790 694 4 × 2 = 0 + 0.310 975 581 388 8;
  • 38) 0.310 975 581 388 8 × 2 = 0 + 0.621 951 162 777 6;
  • 39) 0.621 951 162 777 6 × 2 = 1 + 0.243 902 325 555 2;
  • 40) 0.243 902 325 555 2 × 2 = 0 + 0.487 804 651 110 4;
  • 41) 0.487 804 651 110 4 × 2 = 0 + 0.975 609 302 220 8;
  • 42) 0.975 609 302 220 8 × 2 = 1 + 0.951 218 604 441 6;
  • 43) 0.951 218 604 441 6 × 2 = 1 + 0.902 437 208 883 2;
  • 44) 0.902 437 208 883 2 × 2 = 1 + 0.804 874 417 766 4;
  • 45) 0.804 874 417 766 4 × 2 = 1 + 0.609 748 835 532 8;
  • 46) 0.609 748 835 532 8 × 2 = 1 + 0.219 497 671 065 6;
  • 47) 0.219 497 671 065 6 × 2 = 0 + 0.438 995 342 131 2;
  • 48) 0.438 995 342 131 2 × 2 = 0 + 0.877 990 684 262 4;
  • 49) 0.877 990 684 262 4 × 2 = 1 + 0.755 981 368 524 8;
  • 50) 0.755 981 368 524 8 × 2 = 1 + 0.511 962 737 049 6;
  • 51) 0.511 962 737 049 6 × 2 = 1 + 0.023 925 474 099 2;
  • 52) 0.023 925 474 099 2 × 2 = 0 + 0.047 850 948 198 4;
  • 53) 0.047 850 948 198 4 × 2 = 0 + 0.095 701 896 396 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:


0.035 500 000 000 4(10) =


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

5. Positive number before normalization:

17.035 500 000 000 4(10) =


1 0001.0000 1001 0001 0110 1000 0111 0010 1011 0000 0010 0111 1100 1110 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 4(10) =


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


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


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


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


Mantissa (52 bits) =
0001 0000 1001 0001 0110 1000 0111 0010 1011 0000 0010 0111 1100


Decimal number 17.035 500 000 000 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 0010 0111 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