38.812 000 000 055 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 38.812 000 000 055 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
38.812 000 000 055 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: 38.
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;
  • 38 ÷ 2 = 19 + 0;
  • 19 ÷ 2 = 9 + 1;
  • 9 ÷ 2 = 4 + 1;
  • 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.

38(10) =


10 0110(2)


3. Convert to binary (base 2) the fractional part: 0.812 000 000 055 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) 0.812 000 000 055 6 × 2 = 1 + 0.624 000 000 111 2;
  • 2) 0.624 000 000 111 2 × 2 = 1 + 0.248 000 000 222 4;
  • 3) 0.248 000 000 222 4 × 2 = 0 + 0.496 000 000 444 8;
  • 4) 0.496 000 000 444 8 × 2 = 0 + 0.992 000 000 889 6;
  • 5) 0.992 000 000 889 6 × 2 = 1 + 0.984 000 001 779 2;
  • 6) 0.984 000 001 779 2 × 2 = 1 + 0.968 000 003 558 4;
  • 7) 0.968 000 003 558 4 × 2 = 1 + 0.936 000 007 116 8;
  • 8) 0.936 000 007 116 8 × 2 = 1 + 0.872 000 014 233 6;
  • 9) 0.872 000 014 233 6 × 2 = 1 + 0.744 000 028 467 2;
  • 10) 0.744 000 028 467 2 × 2 = 1 + 0.488 000 056 934 4;
  • 11) 0.488 000 056 934 4 × 2 = 0 + 0.976 000 113 868 8;
  • 12) 0.976 000 113 868 8 × 2 = 1 + 0.952 000 227 737 6;
  • 13) 0.952 000 227 737 6 × 2 = 1 + 0.904 000 455 475 2;
  • 14) 0.904 000 455 475 2 × 2 = 1 + 0.808 000 910 950 4;
  • 15) 0.808 000 910 950 4 × 2 = 1 + 0.616 001 821 900 8;
  • 16) 0.616 001 821 900 8 × 2 = 1 + 0.232 003 643 801 6;
  • 17) 0.232 003 643 801 6 × 2 = 0 + 0.464 007 287 603 2;
  • 18) 0.464 007 287 603 2 × 2 = 0 + 0.928 014 575 206 4;
  • 19) 0.928 014 575 206 4 × 2 = 1 + 0.856 029 150 412 8;
  • 20) 0.856 029 150 412 8 × 2 = 1 + 0.712 058 300 825 6;
  • 21) 0.712 058 300 825 6 × 2 = 1 + 0.424 116 601 651 2;
  • 22) 0.424 116 601 651 2 × 2 = 0 + 0.848 233 203 302 4;
  • 23) 0.848 233 203 302 4 × 2 = 1 + 0.696 466 406 604 8;
  • 24) 0.696 466 406 604 8 × 2 = 1 + 0.392 932 813 209 6;
  • 25) 0.392 932 813 209 6 × 2 = 0 + 0.785 865 626 419 2;
  • 26) 0.785 865 626 419 2 × 2 = 1 + 0.571 731 252 838 4;
  • 27) 0.571 731 252 838 4 × 2 = 1 + 0.143 462 505 676 8;
  • 28) 0.143 462 505 676 8 × 2 = 0 + 0.286 925 011 353 6;
  • 29) 0.286 925 011 353 6 × 2 = 0 + 0.573 850 022 707 2;
  • 30) 0.573 850 022 707 2 × 2 = 1 + 0.147 700 045 414 4;
  • 31) 0.147 700 045 414 4 × 2 = 0 + 0.295 400 090 828 8;
  • 32) 0.295 400 090 828 8 × 2 = 0 + 0.590 800 181 657 6;
  • 33) 0.590 800 181 657 6 × 2 = 1 + 0.181 600 363 315 2;
  • 34) 0.181 600 363 315 2 × 2 = 0 + 0.363 200 726 630 4;
  • 35) 0.363 200 726 630 4 × 2 = 0 + 0.726 401 453 260 8;
  • 36) 0.726 401 453 260 8 × 2 = 1 + 0.452 802 906 521 6;
  • 37) 0.452 802 906 521 6 × 2 = 0 + 0.905 605 813 043 2;
  • 38) 0.905 605 813 043 2 × 2 = 1 + 0.811 211 626 086 4;
  • 39) 0.811 211 626 086 4 × 2 = 1 + 0.622 423 252 172 8;
  • 40) 0.622 423 252 172 8 × 2 = 1 + 0.244 846 504 345 6;
  • 41) 0.244 846 504 345 6 × 2 = 0 + 0.489 693 008 691 2;
  • 42) 0.489 693 008 691 2 × 2 = 0 + 0.979 386 017 382 4;
  • 43) 0.979 386 017 382 4 × 2 = 1 + 0.958 772 034 764 8;
  • 44) 0.958 772 034 764 8 × 2 = 1 + 0.917 544 069 529 6;
  • 45) 0.917 544 069 529 6 × 2 = 1 + 0.835 088 139 059 2;
  • 46) 0.835 088 139 059 2 × 2 = 1 + 0.670 176 278 118 4;
  • 47) 0.670 176 278 118 4 × 2 = 1 + 0.340 352 556 236 8;
  • 48) 0.340 352 556 236 8 × 2 = 0 + 0.680 705 112 473 6;
  • 49) 0.680 705 112 473 6 × 2 = 1 + 0.361 410 224 947 2;
  • 50) 0.361 410 224 947 2 × 2 = 0 + 0.722 820 449 894 4;
  • 51) 0.722 820 449 894 4 × 2 = 1 + 0.445 640 899 788 8;
  • 52) 0.445 640 899 788 8 × 2 = 0 + 0.891 281 799 577 6;
  • 53) 0.891 281 799 577 6 × 2 = 1 + 0.782 563 599 155 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:


0.812 000 000 055 6(10) =


0.1100 1111 1101 1111 0011 1011 0110 0100 1001 0111 0011 1110 1010 1(2)

5. Positive number before normalization:

38.812 000 000 055 6(10) =


10 0110.1100 1111 1101 1111 0011 1011 0110 0100 1001 0111 0011 1110 1010 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 5 positions to the left, so that only one non zero digit remains to the left of it:


38.812 000 000 055 6(10) =


10 0110.1100 1111 1101 1111 0011 1011 0110 0100 1001 0111 0011 1110 1010 1(2) =


10 0110.1100 1111 1101 1111 0011 1011 0110 0100 1001 0111 0011 1110 1010 1(2) × 20 =


1.0011 0110 0111 1110 1111 1001 1101 1011 0010 0100 1011 1001 1111 0101 01(2) × 25


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): 5


Mantissa (not normalized):
1.0011 0110 0111 1110 1111 1001 1101 1011 0010 0100 1011 1001 1111 0101 01


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


5 + 2(11-1) - 1 =


(5 + 1 023)(10) =


1 028(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;
  • 1 028 ÷ 2 = 514 + 0;
  • 514 ÷ 2 = 257 + 0;
  • 257 ÷ 2 = 128 + 1;
  • 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) =


1028(10) =


100 0000 0100(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. 0011 0110 0111 1110 1111 1001 1101 1011 0010 0100 1011 1001 1111 01 0101 =


0011 0110 0111 1110 1111 1001 1101 1011 0010 0100 1011 1001 1111


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 0100


Mantissa (52 bits) =
0011 0110 0111 1110 1111 1001 1101 1011 0010 0100 1011 1001 1111


Decimal number 38.812 000 000 055 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0100 - 0011 0110 0111 1110 1111 1001 1101 1011 0010 0100 1011 1001 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