53.232 860 565 185 76 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 53.232 860 565 185 76(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
53.232 860 565 185 76(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: 53.
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;
  • 53 ÷ 2 = 26 + 1;
  • 26 ÷ 2 = 13 + 0;
  • 13 ÷ 2 = 6 + 1;
  • 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.

53(10) =


11 0101(2)


3. Convert to binary (base 2) the fractional part: 0.232 860 565 185 76.

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) 0.232 860 565 185 76 × 2 = 0 + 0.465 721 130 371 52;
  • 2) 0.465 721 130 371 52 × 2 = 0 + 0.931 442 260 743 04;
  • 3) 0.931 442 260 743 04 × 2 = 1 + 0.862 884 521 486 08;
  • 4) 0.862 884 521 486 08 × 2 = 1 + 0.725 769 042 972 16;
  • 5) 0.725 769 042 972 16 × 2 = 1 + 0.451 538 085 944 32;
  • 6) 0.451 538 085 944 32 × 2 = 0 + 0.903 076 171 888 64;
  • 7) 0.903 076 171 888 64 × 2 = 1 + 0.806 152 343 777 28;
  • 8) 0.806 152 343 777 28 × 2 = 1 + 0.612 304 687 554 56;
  • 9) 0.612 304 687 554 56 × 2 = 1 + 0.224 609 375 109 12;
  • 10) 0.224 609 375 109 12 × 2 = 0 + 0.449 218 750 218 24;
  • 11) 0.449 218 750 218 24 × 2 = 0 + 0.898 437 500 436 48;
  • 12) 0.898 437 500 436 48 × 2 = 1 + 0.796 875 000 872 96;
  • 13) 0.796 875 000 872 96 × 2 = 1 + 0.593 750 001 745 92;
  • 14) 0.593 750 001 745 92 × 2 = 1 + 0.187 500 003 491 84;
  • 15) 0.187 500 003 491 84 × 2 = 0 + 0.375 000 006 983 68;
  • 16) 0.375 000 006 983 68 × 2 = 0 + 0.750 000 013 967 36;
  • 17) 0.750 000 013 967 36 × 2 = 1 + 0.500 000 027 934 72;
  • 18) 0.500 000 027 934 72 × 2 = 1 + 0.000 000 055 869 44;
  • 19) 0.000 000 055 869 44 × 2 = 0 + 0.000 000 111 738 88;
  • 20) 0.000 000 111 738 88 × 2 = 0 + 0.000 000 223 477 76;
  • 21) 0.000 000 223 477 76 × 2 = 0 + 0.000 000 446 955 52;
  • 22) 0.000 000 446 955 52 × 2 = 0 + 0.000 000 893 911 04;
  • 23) 0.000 000 893 911 04 × 2 = 0 + 0.000 001 787 822 08;
  • 24) 0.000 001 787 822 08 × 2 = 0 + 0.000 003 575 644 16;
  • 25) 0.000 003 575 644 16 × 2 = 0 + 0.000 007 151 288 32;
  • 26) 0.000 007 151 288 32 × 2 = 0 + 0.000 014 302 576 64;
  • 27) 0.000 014 302 576 64 × 2 = 0 + 0.000 028 605 153 28;
  • 28) 0.000 028 605 153 28 × 2 = 0 + 0.000 057 210 306 56;
  • 29) 0.000 057 210 306 56 × 2 = 0 + 0.000 114 420 613 12;
  • 30) 0.000 114 420 613 12 × 2 = 0 + 0.000 228 841 226 24;
  • 31) 0.000 228 841 226 24 × 2 = 0 + 0.000 457 682 452 48;
  • 32) 0.000 457 682 452 48 × 2 = 0 + 0.000 915 364 904 96;
  • 33) 0.000 915 364 904 96 × 2 = 0 + 0.001 830 729 809 92;
  • 34) 0.001 830 729 809 92 × 2 = 0 + 0.003 661 459 619 84;
  • 35) 0.003 661 459 619 84 × 2 = 0 + 0.007 322 919 239 68;
  • 36) 0.007 322 919 239 68 × 2 = 0 + 0.014 645 838 479 36;
  • 37) 0.014 645 838 479 36 × 2 = 0 + 0.029 291 676 958 72;
  • 38) 0.029 291 676 958 72 × 2 = 0 + 0.058 583 353 917 44;
  • 39) 0.058 583 353 917 44 × 2 = 0 + 0.117 166 707 834 88;
  • 40) 0.117 166 707 834 88 × 2 = 0 + 0.234 333 415 669 76;
  • 41) 0.234 333 415 669 76 × 2 = 0 + 0.468 666 831 339 52;
  • 42) 0.468 666 831 339 52 × 2 = 0 + 0.937 333 662 679 04;
  • 43) 0.937 333 662 679 04 × 2 = 1 + 0.874 667 325 358 08;
  • 44) 0.874 667 325 358 08 × 2 = 1 + 0.749 334 650 716 16;
  • 45) 0.749 334 650 716 16 × 2 = 1 + 0.498 669 301 432 32;
  • 46) 0.498 669 301 432 32 × 2 = 0 + 0.997 338 602 864 64;
  • 47) 0.997 338 602 864 64 × 2 = 1 + 0.994 677 205 729 28;
  • 48) 0.994 677 205 729 28 × 2 = 1 + 0.989 354 411 458 56;
  • 49) 0.989 354 411 458 56 × 2 = 1 + 0.978 708 822 917 12;
  • 50) 0.978 708 822 917 12 × 2 = 1 + 0.957 417 645 834 24;
  • 51) 0.957 417 645 834 24 × 2 = 1 + 0.914 835 291 668 48;
  • 52) 0.914 835 291 668 48 × 2 = 1 + 0.829 670 583 336 96;
  • 53) 0.829 670 583 336 96 × 2 = 1 + 0.659 341 166 673 92;

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:


0.232 860 565 185 76(10) =


0.0011 1011 1001 1100 1100 0000 0000 0000 0000 0000 0011 1011 1111 1(2)

5. Positive number before normalization:

53.232 860 565 185 76(10) =


11 0101.0011 1011 1001 1100 1100 0000 0000 0000 0000 0000 0011 1011 1111 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:


53.232 860 565 185 76(10) =


11 0101.0011 1011 1001 1100 1100 0000 0000 0000 0000 0000 0011 1011 1111 1(2) =


11 0101.0011 1011 1001 1100 1100 0000 0000 0000 0000 0000 0011 1011 1111 1(2) × 20 =


1.1010 1001 1101 1100 1110 0110 0000 0000 0000 0000 0000 0001 1101 1111 11(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):
1.1010 1001 1101 1100 1110 0110 0000 0000 0000 0000 0000 0001 1101 1111 11


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. 1010 1001 1101 1100 1110 0110 0000 0000 0000 0000 0000 0001 1101 11 1111 =


1010 1001 1101 1100 1110 0110 0000 0000 0000 0000 0000 0001 1101


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) =
1010 1001 1101 1100 1110 0110 0000 0000 0000 0000 0000 0001 1101


Decimal number 53.232 860 565 185 76 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0100 - 1010 1001 1101 1100 1110 0110 0000 0000 0000 0000 0000 0001 1101


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