6.283 185 304 95 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 6.283 185 304 95(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
6.283 185 304 95(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: 6.
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;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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.

6(10) =


110(2)


3. Convert to binary (base 2) the fractional part: 0.283 185 304 95.

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) 0.283 185 304 95 × 2 = 0 + 0.566 370 609 9;
  • 2) 0.566 370 609 9 × 2 = 1 + 0.132 741 219 8;
  • 3) 0.132 741 219 8 × 2 = 0 + 0.265 482 439 6;
  • 4) 0.265 482 439 6 × 2 = 0 + 0.530 964 879 2;
  • 5) 0.530 964 879 2 × 2 = 1 + 0.061 929 758 4;
  • 6) 0.061 929 758 4 × 2 = 0 + 0.123 859 516 8;
  • 7) 0.123 859 516 8 × 2 = 0 + 0.247 719 033 6;
  • 8) 0.247 719 033 6 × 2 = 0 + 0.495 438 067 2;
  • 9) 0.495 438 067 2 × 2 = 0 + 0.990 876 134 4;
  • 10) 0.990 876 134 4 × 2 = 1 + 0.981 752 268 8;
  • 11) 0.981 752 268 8 × 2 = 1 + 0.963 504 537 6;
  • 12) 0.963 504 537 6 × 2 = 1 + 0.927 009 075 2;
  • 13) 0.927 009 075 2 × 2 = 1 + 0.854 018 150 4;
  • 14) 0.854 018 150 4 × 2 = 1 + 0.708 036 300 8;
  • 15) 0.708 036 300 8 × 2 = 1 + 0.416 072 601 6;
  • 16) 0.416 072 601 6 × 2 = 0 + 0.832 145 203 2;
  • 17) 0.832 145 203 2 × 2 = 1 + 0.664 290 406 4;
  • 18) 0.664 290 406 4 × 2 = 1 + 0.328 580 812 8;
  • 19) 0.328 580 812 8 × 2 = 0 + 0.657 161 625 6;
  • 20) 0.657 161 625 6 × 2 = 1 + 0.314 323 251 2;
  • 21) 0.314 323 251 2 × 2 = 0 + 0.628 646 502 4;
  • 22) 0.628 646 502 4 × 2 = 1 + 0.257 293 004 8;
  • 23) 0.257 293 004 8 × 2 = 0 + 0.514 586 009 6;
  • 24) 0.514 586 009 6 × 2 = 1 + 0.029 172 019 2;
  • 25) 0.029 172 019 2 × 2 = 0 + 0.058 344 038 4;
  • 26) 0.058 344 038 4 × 2 = 0 + 0.116 688 076 8;
  • 27) 0.116 688 076 8 × 2 = 0 + 0.233 376 153 6;
  • 28) 0.233 376 153 6 × 2 = 0 + 0.466 752 307 2;
  • 29) 0.466 752 307 2 × 2 = 0 + 0.933 504 614 4;
  • 30) 0.933 504 614 4 × 2 = 1 + 0.867 009 228 8;
  • 31) 0.867 009 228 8 × 2 = 1 + 0.734 018 457 6;
  • 32) 0.734 018 457 6 × 2 = 1 + 0.468 036 915 2;
  • 33) 0.468 036 915 2 × 2 = 0 + 0.936 073 830 4;
  • 34) 0.936 073 830 4 × 2 = 1 + 0.872 147 660 8;
  • 35) 0.872 147 660 8 × 2 = 1 + 0.744 295 321 6;
  • 36) 0.744 295 321 6 × 2 = 1 + 0.488 590 643 2;
  • 37) 0.488 590 643 2 × 2 = 0 + 0.977 181 286 4;
  • 38) 0.977 181 286 4 × 2 = 1 + 0.954 362 572 8;
  • 39) 0.954 362 572 8 × 2 = 1 + 0.908 725 145 6;
  • 40) 0.908 725 145 6 × 2 = 1 + 0.817 450 291 2;
  • 41) 0.817 450 291 2 × 2 = 1 + 0.634 900 582 4;
  • 42) 0.634 900 582 4 × 2 = 1 + 0.269 801 164 8;
  • 43) 0.269 801 164 8 × 2 = 0 + 0.539 602 329 6;
  • 44) 0.539 602 329 6 × 2 = 1 + 0.079 204 659 2;
  • 45) 0.079 204 659 2 × 2 = 0 + 0.158 409 318 4;
  • 46) 0.158 409 318 4 × 2 = 0 + 0.316 818 636 8;
  • 47) 0.316 818 636 8 × 2 = 0 + 0.633 637 273 6;
  • 48) 0.633 637 273 6 × 2 = 1 + 0.267 274 547 2;
  • 49) 0.267 274 547 2 × 2 = 0 + 0.534 549 094 4;
  • 50) 0.534 549 094 4 × 2 = 1 + 0.069 098 188 8;
  • 51) 0.069 098 188 8 × 2 = 0 + 0.138 196 377 6;
  • 52) 0.138 196 377 6 × 2 = 0 + 0.276 392 755 2;
  • 53) 0.276 392 755 2 × 2 = 0 + 0.552 785 510 4;

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:


0.283 185 304 95(10) =


0.0100 1000 0111 1110 1101 0101 0000 0111 0111 0111 1101 0001 0100 0(2)

5. Positive number before normalization:

6.283 185 304 95(10) =


110.0100 1000 0111 1110 1101 0101 0000 0111 0111 0111 1101 0001 0100 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 2 positions to the left, so that only one non zero digit remains to the left of it:


6.283 185 304 95(10) =


110.0100 1000 0111 1110 1101 0101 0000 0111 0111 0111 1101 0001 0100 0(2) =


110.0100 1000 0111 1110 1101 0101 0000 0111 0111 0111 1101 0001 0100 0(2) × 20 =


1.1001 0010 0001 1111 1011 0101 0100 0001 1101 1101 1111 0100 0101 000(2) × 22


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): 2


Mantissa (not normalized):
1.1001 0010 0001 1111 1011 0101 0100 0001 1101 1101 1111 0100 0101 000


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


2 + 2(11-1) - 1 =


(2 + 1 023)(10) =


1 025(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;
  • 1 025 ÷ 2 = 512 + 1;
  • 512 ÷ 2 = 256 + 0;
  • 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) =


1025(10) =


100 0000 0001(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. 1001 0010 0001 1111 1011 0101 0100 0001 1101 1101 1111 0100 0101 000 =


1001 0010 0001 1111 1011 0101 0100 0001 1101 1101 1111 0100 0101


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 0001


Mantissa (52 bits) =
1001 0010 0001 1111 1011 0101 0100 0001 1101 1101 1111 0100 0101


Decimal number 6.283 185 304 95 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0001 - 1001 0010 0001 1111 1011 0101 0100 0001 1101 1101 1111 0100 0101


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