3.200 000 047 771 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 3.200 000 047 771 7(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
3.200 000 047 771 7(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: 3.
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;
  • 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.

3(10) =


11(2)


3. Convert to binary (base 2) the fractional part: 0.200 000 047 771 7.

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) 0.200 000 047 771 7 × 2 = 0 + 0.400 000 095 543 4;
  • 2) 0.400 000 095 543 4 × 2 = 0 + 0.800 000 191 086 8;
  • 3) 0.800 000 191 086 8 × 2 = 1 + 0.600 000 382 173 6;
  • 4) 0.600 000 382 173 6 × 2 = 1 + 0.200 000 764 347 2;
  • 5) 0.200 000 764 347 2 × 2 = 0 + 0.400 001 528 694 4;
  • 6) 0.400 001 528 694 4 × 2 = 0 + 0.800 003 057 388 8;
  • 7) 0.800 003 057 388 8 × 2 = 1 + 0.600 006 114 777 6;
  • 8) 0.600 006 114 777 6 × 2 = 1 + 0.200 012 229 555 2;
  • 9) 0.200 012 229 555 2 × 2 = 0 + 0.400 024 459 110 4;
  • 10) 0.400 024 459 110 4 × 2 = 0 + 0.800 048 918 220 8;
  • 11) 0.800 048 918 220 8 × 2 = 1 + 0.600 097 836 441 6;
  • 12) 0.600 097 836 441 6 × 2 = 1 + 0.200 195 672 883 2;
  • 13) 0.200 195 672 883 2 × 2 = 0 + 0.400 391 345 766 4;
  • 14) 0.400 391 345 766 4 × 2 = 0 + 0.800 782 691 532 8;
  • 15) 0.800 782 691 532 8 × 2 = 1 + 0.601 565 383 065 6;
  • 16) 0.601 565 383 065 6 × 2 = 1 + 0.203 130 766 131 2;
  • 17) 0.203 130 766 131 2 × 2 = 0 + 0.406 261 532 262 4;
  • 18) 0.406 261 532 262 4 × 2 = 0 + 0.812 523 064 524 8;
  • 19) 0.812 523 064 524 8 × 2 = 1 + 0.625 046 129 049 6;
  • 20) 0.625 046 129 049 6 × 2 = 1 + 0.250 092 258 099 2;
  • 21) 0.250 092 258 099 2 × 2 = 0 + 0.500 184 516 198 4;
  • 22) 0.500 184 516 198 4 × 2 = 1 + 0.000 369 032 396 8;
  • 23) 0.000 369 032 396 8 × 2 = 0 + 0.000 738 064 793 6;
  • 24) 0.000 738 064 793 6 × 2 = 0 + 0.001 476 129 587 2;
  • 25) 0.001 476 129 587 2 × 2 = 0 + 0.002 952 259 174 4;
  • 26) 0.002 952 259 174 4 × 2 = 0 + 0.005 904 518 348 8;
  • 27) 0.005 904 518 348 8 × 2 = 0 + 0.011 809 036 697 6;
  • 28) 0.011 809 036 697 6 × 2 = 0 + 0.023 618 073 395 2;
  • 29) 0.023 618 073 395 2 × 2 = 0 + 0.047 236 146 790 4;
  • 30) 0.047 236 146 790 4 × 2 = 0 + 0.094 472 293 580 8;
  • 31) 0.094 472 293 580 8 × 2 = 0 + 0.188 944 587 161 6;
  • 32) 0.188 944 587 161 6 × 2 = 0 + 0.377 889 174 323 2;
  • 33) 0.377 889 174 323 2 × 2 = 0 + 0.755 778 348 646 4;
  • 34) 0.755 778 348 646 4 × 2 = 1 + 0.511 556 697 292 8;
  • 35) 0.511 556 697 292 8 × 2 = 1 + 0.023 113 394 585 6;
  • 36) 0.023 113 394 585 6 × 2 = 0 + 0.046 226 789 171 2;
  • 37) 0.046 226 789 171 2 × 2 = 0 + 0.092 453 578 342 4;
  • 38) 0.092 453 578 342 4 × 2 = 0 + 0.184 907 156 684 8;
  • 39) 0.184 907 156 684 8 × 2 = 0 + 0.369 814 313 369 6;
  • 40) 0.369 814 313 369 6 × 2 = 0 + 0.739 628 626 739 2;
  • 41) 0.739 628 626 739 2 × 2 = 1 + 0.479 257 253 478 4;
  • 42) 0.479 257 253 478 4 × 2 = 0 + 0.958 514 506 956 8;
  • 43) 0.958 514 506 956 8 × 2 = 1 + 0.917 029 013 913 6;
  • 44) 0.917 029 013 913 6 × 2 = 1 + 0.834 058 027 827 2;
  • 45) 0.834 058 027 827 2 × 2 = 1 + 0.668 116 055 654 4;
  • 46) 0.668 116 055 654 4 × 2 = 1 + 0.336 232 111 308 8;
  • 47) 0.336 232 111 308 8 × 2 = 0 + 0.672 464 222 617 6;
  • 48) 0.672 464 222 617 6 × 2 = 1 + 0.344 928 445 235 2;
  • 49) 0.344 928 445 235 2 × 2 = 0 + 0.689 856 890 470 4;
  • 50) 0.689 856 890 470 4 × 2 = 1 + 0.379 713 780 940 8;
  • 51) 0.379 713 780 940 8 × 2 = 0 + 0.759 427 561 881 6;
  • 52) 0.759 427 561 881 6 × 2 = 1 + 0.518 855 123 763 2;
  • 53) 0.518 855 123 763 2 × 2 = 1 + 0.037 710 247 526 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:


0.200 000 047 771 7(10) =


0.0011 0011 0011 0011 0011 0100 0000 0000 0110 0000 1011 1101 0101 1(2)

5. Positive number before normalization:

3.200 000 047 771 7(10) =


11.0011 0011 0011 0011 0011 0100 0000 0000 0110 0000 1011 1101 0101 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the left, so that only one non zero digit remains to the left of it:


3.200 000 047 771 7(10) =


11.0011 0011 0011 0011 0011 0100 0000 0000 0110 0000 1011 1101 0101 1(2) =


11.0011 0011 0011 0011 0011 0100 0000 0000 0110 0000 1011 1101 0101 1(2) × 20 =


1.1001 1001 1001 1001 1001 1010 0000 0000 0011 0000 0101 1110 1010 11(2) × 21


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): 1


Mantissa (not normalized):
1.1001 1001 1001 1001 1001 1010 0000 0000 0011 0000 0101 1110 1010 11


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


1 + 2(11-1) - 1 =


(1 + 1 023)(10) =


1 024(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;
  • 1 024 ÷ 2 = 512 + 0;
  • 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) =


1024(10) =


100 0000 0000(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 1001 1001 1001 1001 1010 0000 0000 0011 0000 0101 1110 1010 11 =


1001 1001 1001 1001 1001 1010 0000 0000 0011 0000 0101 1110 1010


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 0000


Mantissa (52 bits) =
1001 1001 1001 1001 1001 1010 0000 0000 0011 0000 0101 1110 1010


Decimal number 3.200 000 047 771 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 1001 1001 1001 1001 1001 1010 0000 0000 0011 0000 0101 1110 1010


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