64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 0.012 048 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 0.012 048(10) converted and written in 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: 0.
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;
  • 0 ÷ 2 = 0 + 0;

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.


0(10) =


0(2)


3. Convert to binary (base 2) the fractional part: 0.012 048.

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) 0.012 048 × 2 = 0 + 0.024 096;
  • 2) 0.024 096 × 2 = 0 + 0.048 192;
  • 3) 0.048 192 × 2 = 0 + 0.096 384;
  • 4) 0.096 384 × 2 = 0 + 0.192 768;
  • 5) 0.192 768 × 2 = 0 + 0.385 536;
  • 6) 0.385 536 × 2 = 0 + 0.771 072;
  • 7) 0.771 072 × 2 = 1 + 0.542 144;
  • 8) 0.542 144 × 2 = 1 + 0.084 288;
  • 9) 0.084 288 × 2 = 0 + 0.168 576;
  • 10) 0.168 576 × 2 = 0 + 0.337 152;
  • 11) 0.337 152 × 2 = 0 + 0.674 304;
  • 12) 0.674 304 × 2 = 1 + 0.348 608;
  • 13) 0.348 608 × 2 = 0 + 0.697 216;
  • 14) 0.697 216 × 2 = 1 + 0.394 432;
  • 15) 0.394 432 × 2 = 0 + 0.788 864;
  • 16) 0.788 864 × 2 = 1 + 0.577 728;
  • 17) 0.577 728 × 2 = 1 + 0.155 456;
  • 18) 0.155 456 × 2 = 0 + 0.310 912;
  • 19) 0.310 912 × 2 = 0 + 0.621 824;
  • 20) 0.621 824 × 2 = 1 + 0.243 648;
  • 21) 0.243 648 × 2 = 0 + 0.487 296;
  • 22) 0.487 296 × 2 = 0 + 0.974 592;
  • 23) 0.974 592 × 2 = 1 + 0.949 184;
  • 24) 0.949 184 × 2 = 1 + 0.898 368;
  • 25) 0.898 368 × 2 = 1 + 0.796 736;
  • 26) 0.796 736 × 2 = 1 + 0.593 472;
  • 27) 0.593 472 × 2 = 1 + 0.186 944;
  • 28) 0.186 944 × 2 = 0 + 0.373 888;
  • 29) 0.373 888 × 2 = 0 + 0.747 776;
  • 30) 0.747 776 × 2 = 1 + 0.495 552;
  • 31) 0.495 552 × 2 = 0 + 0.991 104;
  • 32) 0.991 104 × 2 = 1 + 0.982 208;
  • 33) 0.982 208 × 2 = 1 + 0.964 416;
  • 34) 0.964 416 × 2 = 1 + 0.928 832;
  • 35) 0.928 832 × 2 = 1 + 0.857 664;
  • 36) 0.857 664 × 2 = 1 + 0.715 328;
  • 37) 0.715 328 × 2 = 1 + 0.430 656;
  • 38) 0.430 656 × 2 = 0 + 0.861 312;
  • 39) 0.861 312 × 2 = 1 + 0.722 624;
  • 40) 0.722 624 × 2 = 1 + 0.445 248;
  • 41) 0.445 248 × 2 = 0 + 0.890 496;
  • 42) 0.890 496 × 2 = 1 + 0.780 992;
  • 43) 0.780 992 × 2 = 1 + 0.561 984;
  • 44) 0.561 984 × 2 = 1 + 0.123 968;
  • 45) 0.123 968 × 2 = 0 + 0.247 936;
  • 46) 0.247 936 × 2 = 0 + 0.495 872;
  • 47) 0.495 872 × 2 = 0 + 0.991 744;
  • 48) 0.991 744 × 2 = 1 + 0.983 488;
  • 49) 0.983 488 × 2 = 1 + 0.966 976;
  • 50) 0.966 976 × 2 = 1 + 0.933 952;
  • 51) 0.933 952 × 2 = 1 + 0.867 904;
  • 52) 0.867 904 × 2 = 1 + 0.735 808;
  • 53) 0.735 808 × 2 = 1 + 0.471 616;
  • 54) 0.471 616 × 2 = 0 + 0.943 232;
  • 55) 0.943 232 × 2 = 1 + 0.886 464;
  • 56) 0.886 464 × 2 = 1 + 0.772 928;
  • 57) 0.772 928 × 2 = 1 + 0.545 856;
  • 58) 0.545 856 × 2 = 1 + 0.091 712;
  • 59) 0.091 712 × 2 = 0 + 0.183 424;

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...)


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:


0.012 048(10) =


0.0000 0011 0001 0101 1001 0011 1110 0101 1111 1011 0111 0001 1111 1011 110(2)


5. Positive number before normalization:

0.012 048(10) =


0.0000 0011 0001 0101 1001 0011 1110 0101 1111 1011 0111 0001 1111 1011 110(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 7 positions to the right, so that only one non zero digit remains to the left of it:


0.012 048(10) =


0.0000 0011 0001 0101 1001 0011 1110 0101 1111 1011 0111 0001 1111 1011 110(2) =


0.0000 0011 0001 0101 1001 0011 1110 0101 1111 1011 0111 0001 1111 1011 110(2) × 20 =


1.1000 1010 1100 1001 1111 0010 1111 1101 1011 1000 1111 1101 1110(2) × 2-7


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): -7


Mantissa (not normalized):
1.1000 1010 1100 1001 1111 0010 1111 1101 1011 1000 1111 1101 1110


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-7 + 2(11-1) - 1 =


(-7 + 1 023)(10) =


1 016(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;
  • 1 016 ÷ 2 = 508 + 0;
  • 508 ÷ 2 = 254 + 0;
  • 254 ÷ 2 = 127 + 0;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1016(10) =


011 1111 1000(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 1000 1010 1100 1001 1111 0010 1111 1101 1011 1000 1111 1101 1110 =


1000 1010 1100 1001 1111 0010 1111 1101 1011 1000 1111 1101 1110


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) =
011 1111 1000


Mantissa (52 bits) =
1000 1010 1100 1001 1111 0010 1111 1101 1011 1000 1111 1101 1110


The base ten decimal number 0.012 048 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 011 1111 1000 - 1000 1010 1100 1001 1111 0010 1111 1101 1011 1000 1111 1101 1110

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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