24.777 777 777 797 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 24.777 777 777 797 3(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
24.777 777 777 797 3(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: 24.
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;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 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.

24(10) =


1 1000(2)


3. Convert to binary (base 2) the fractional part: 0.777 777 777 797 3.

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) 0.777 777 777 797 3 × 2 = 1 + 0.555 555 555 594 6;
  • 2) 0.555 555 555 594 6 × 2 = 1 + 0.111 111 111 189 2;
  • 3) 0.111 111 111 189 2 × 2 = 0 + 0.222 222 222 378 4;
  • 4) 0.222 222 222 378 4 × 2 = 0 + 0.444 444 444 756 8;
  • 5) 0.444 444 444 756 8 × 2 = 0 + 0.888 888 889 513 6;
  • 6) 0.888 888 889 513 6 × 2 = 1 + 0.777 777 779 027 2;
  • 7) 0.777 777 779 027 2 × 2 = 1 + 0.555 555 558 054 4;
  • 8) 0.555 555 558 054 4 × 2 = 1 + 0.111 111 116 108 8;
  • 9) 0.111 111 116 108 8 × 2 = 0 + 0.222 222 232 217 6;
  • 10) 0.222 222 232 217 6 × 2 = 0 + 0.444 444 464 435 2;
  • 11) 0.444 444 464 435 2 × 2 = 0 + 0.888 888 928 870 4;
  • 12) 0.888 888 928 870 4 × 2 = 1 + 0.777 777 857 740 8;
  • 13) 0.777 777 857 740 8 × 2 = 1 + 0.555 555 715 481 6;
  • 14) 0.555 555 715 481 6 × 2 = 1 + 0.111 111 430 963 2;
  • 15) 0.111 111 430 963 2 × 2 = 0 + 0.222 222 861 926 4;
  • 16) 0.222 222 861 926 4 × 2 = 0 + 0.444 445 723 852 8;
  • 17) 0.444 445 723 852 8 × 2 = 0 + 0.888 891 447 705 6;
  • 18) 0.888 891 447 705 6 × 2 = 1 + 0.777 782 895 411 2;
  • 19) 0.777 782 895 411 2 × 2 = 1 + 0.555 565 790 822 4;
  • 20) 0.555 565 790 822 4 × 2 = 1 + 0.111 131 581 644 8;
  • 21) 0.111 131 581 644 8 × 2 = 0 + 0.222 263 163 289 6;
  • 22) 0.222 263 163 289 6 × 2 = 0 + 0.444 526 326 579 2;
  • 23) 0.444 526 326 579 2 × 2 = 0 + 0.889 052 653 158 4;
  • 24) 0.889 052 653 158 4 × 2 = 1 + 0.778 105 306 316 8;
  • 25) 0.778 105 306 316 8 × 2 = 1 + 0.556 210 612 633 6;
  • 26) 0.556 210 612 633 6 × 2 = 1 + 0.112 421 225 267 2;
  • 27) 0.112 421 225 267 2 × 2 = 0 + 0.224 842 450 534 4;
  • 28) 0.224 842 450 534 4 × 2 = 0 + 0.449 684 901 068 8;
  • 29) 0.449 684 901 068 8 × 2 = 0 + 0.899 369 802 137 6;
  • 30) 0.899 369 802 137 6 × 2 = 1 + 0.798 739 604 275 2;
  • 31) 0.798 739 604 275 2 × 2 = 1 + 0.597 479 208 550 4;
  • 32) 0.597 479 208 550 4 × 2 = 1 + 0.194 958 417 100 8;
  • 33) 0.194 958 417 100 8 × 2 = 0 + 0.389 916 834 201 6;
  • 34) 0.389 916 834 201 6 × 2 = 0 + 0.779 833 668 403 2;
  • 35) 0.779 833 668 403 2 × 2 = 1 + 0.559 667 336 806 4;
  • 36) 0.559 667 336 806 4 × 2 = 1 + 0.119 334 673 612 8;
  • 37) 0.119 334 673 612 8 × 2 = 0 + 0.238 669 347 225 6;
  • 38) 0.238 669 347 225 6 × 2 = 0 + 0.477 338 694 451 2;
  • 39) 0.477 338 694 451 2 × 2 = 0 + 0.954 677 388 902 4;
  • 40) 0.954 677 388 902 4 × 2 = 1 + 0.909 354 777 804 8;
  • 41) 0.909 354 777 804 8 × 2 = 1 + 0.818 709 555 609 6;
  • 42) 0.818 709 555 609 6 × 2 = 1 + 0.637 419 111 219 2;
  • 43) 0.637 419 111 219 2 × 2 = 1 + 0.274 838 222 438 4;
  • 44) 0.274 838 222 438 4 × 2 = 0 + 0.549 676 444 876 8;
  • 45) 0.549 676 444 876 8 × 2 = 1 + 0.099 352 889 753 6;
  • 46) 0.099 352 889 753 6 × 2 = 0 + 0.198 705 779 507 2;
  • 47) 0.198 705 779 507 2 × 2 = 0 + 0.397 411 559 014 4;
  • 48) 0.397 411 559 014 4 × 2 = 0 + 0.794 823 118 028 8;
  • 49) 0.794 823 118 028 8 × 2 = 1 + 0.589 646 236 057 6;
  • 50) 0.589 646 236 057 6 × 2 = 1 + 0.179 292 472 115 2;
  • 51) 0.179 292 472 115 2 × 2 = 0 + 0.358 584 944 230 4;
  • 52) 0.358 584 944 230 4 × 2 = 0 + 0.717 169 888 460 8;
  • 53) 0.717 169 888 460 8 × 2 = 1 + 0.434 339 776 921 6;

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:


0.777 777 777 797 3(10) =


0.1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000 1100 1(2)

5. Positive number before normalization:

24.777 777 777 797 3(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000 1100 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 4 positions to the left, so that only one non zero digit remains to the left of it:


24.777 777 777 797 3(10) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000 1100 1(2) =


1 1000.1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000 1100 1(2) × 20 =


1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000 1100 1(2) × 24


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): 4


Mantissa (not normalized):
1.1000 1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000 1100 1


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


4 + 2(11-1) - 1 =


(4 + 1 023)(10) =


1 027(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;
  • 1 027 ÷ 2 = 513 + 1;
  • 513 ÷ 2 = 256 + 1;
  • 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) =


1027(10) =


100 0000 0011(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. 1000 1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000 1 1001 =


1000 1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000


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 0011


Mantissa (52 bits) =
1000 1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000


Decimal number 24.777 777 777 797 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0011 - 1000 1100 0111 0001 1100 0111 0001 1100 0111 0011 0001 1110 1000


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