57.295 779 513 082 38 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 57.295 779 513 082 38(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
57.295 779 513 082 38(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: 57.
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;
  • 57 ÷ 2 = 28 + 1;
  • 28 ÷ 2 = 14 + 0;
  • 14 ÷ 2 = 7 + 0;
  • 7 ÷ 2 = 3 + 1;
  • 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.

57(10) =


11 1001(2)


3. Convert to binary (base 2) the fractional part: 0.295 779 513 082 38.

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) 0.295 779 513 082 38 × 2 = 0 + 0.591 559 026 164 76;
  • 2) 0.591 559 026 164 76 × 2 = 1 + 0.183 118 052 329 52;
  • 3) 0.183 118 052 329 52 × 2 = 0 + 0.366 236 104 659 04;
  • 4) 0.366 236 104 659 04 × 2 = 0 + 0.732 472 209 318 08;
  • 5) 0.732 472 209 318 08 × 2 = 1 + 0.464 944 418 636 16;
  • 6) 0.464 944 418 636 16 × 2 = 0 + 0.929 888 837 272 32;
  • 7) 0.929 888 837 272 32 × 2 = 1 + 0.859 777 674 544 64;
  • 8) 0.859 777 674 544 64 × 2 = 1 + 0.719 555 349 089 28;
  • 9) 0.719 555 349 089 28 × 2 = 1 + 0.439 110 698 178 56;
  • 10) 0.439 110 698 178 56 × 2 = 0 + 0.878 221 396 357 12;
  • 11) 0.878 221 396 357 12 × 2 = 1 + 0.756 442 792 714 24;
  • 12) 0.756 442 792 714 24 × 2 = 1 + 0.512 885 585 428 48;
  • 13) 0.512 885 585 428 48 × 2 = 1 + 0.025 771 170 856 96;
  • 14) 0.025 771 170 856 96 × 2 = 0 + 0.051 542 341 713 92;
  • 15) 0.051 542 341 713 92 × 2 = 0 + 0.103 084 683 427 84;
  • 16) 0.103 084 683 427 84 × 2 = 0 + 0.206 169 366 855 68;
  • 17) 0.206 169 366 855 68 × 2 = 0 + 0.412 338 733 711 36;
  • 18) 0.412 338 733 711 36 × 2 = 0 + 0.824 677 467 422 72;
  • 19) 0.824 677 467 422 72 × 2 = 1 + 0.649 354 934 845 44;
  • 20) 0.649 354 934 845 44 × 2 = 1 + 0.298 709 869 690 88;
  • 21) 0.298 709 869 690 88 × 2 = 0 + 0.597 419 739 381 76;
  • 22) 0.597 419 739 381 76 × 2 = 1 + 0.194 839 478 763 52;
  • 23) 0.194 839 478 763 52 × 2 = 0 + 0.389 678 957 527 04;
  • 24) 0.389 678 957 527 04 × 2 = 0 + 0.779 357 915 054 08;
  • 25) 0.779 357 915 054 08 × 2 = 1 + 0.558 715 830 108 16;
  • 26) 0.558 715 830 108 16 × 2 = 1 + 0.117 431 660 216 32;
  • 27) 0.117 431 660 216 32 × 2 = 0 + 0.234 863 320 432 64;
  • 28) 0.234 863 320 432 64 × 2 = 0 + 0.469 726 640 865 28;
  • 29) 0.469 726 640 865 28 × 2 = 0 + 0.939 453 281 730 56;
  • 30) 0.939 453 281 730 56 × 2 = 1 + 0.878 906 563 461 12;
  • 31) 0.878 906 563 461 12 × 2 = 1 + 0.757 813 126 922 24;
  • 32) 0.757 813 126 922 24 × 2 = 1 + 0.515 626 253 844 48;
  • 33) 0.515 626 253 844 48 × 2 = 1 + 0.031 252 507 688 96;
  • 34) 0.031 252 507 688 96 × 2 = 0 + 0.062 505 015 377 92;
  • 35) 0.062 505 015 377 92 × 2 = 0 + 0.125 010 030 755 84;
  • 36) 0.125 010 030 755 84 × 2 = 0 + 0.250 020 061 511 68;
  • 37) 0.250 020 061 511 68 × 2 = 0 + 0.500 040 123 023 36;
  • 38) 0.500 040 123 023 36 × 2 = 1 + 0.000 080 246 046 72;
  • 39) 0.000 080 246 046 72 × 2 = 0 + 0.000 160 492 093 44;
  • 40) 0.000 160 492 093 44 × 2 = 0 + 0.000 320 984 186 88;
  • 41) 0.000 320 984 186 88 × 2 = 0 + 0.000 641 968 373 76;
  • 42) 0.000 641 968 373 76 × 2 = 0 + 0.001 283 936 747 52;
  • 43) 0.001 283 936 747 52 × 2 = 0 + 0.002 567 873 495 04;
  • 44) 0.002 567 873 495 04 × 2 = 0 + 0.005 135 746 990 08;
  • 45) 0.005 135 746 990 08 × 2 = 0 + 0.010 271 493 980 16;
  • 46) 0.010 271 493 980 16 × 2 = 0 + 0.020 542 987 960 32;
  • 47) 0.020 542 987 960 32 × 2 = 0 + 0.041 085 975 920 64;
  • 48) 0.041 085 975 920 64 × 2 = 0 + 0.082 171 951 841 28;
  • 49) 0.082 171 951 841 28 × 2 = 0 + 0.164 343 903 682 56;
  • 50) 0.164 343 903 682 56 × 2 = 0 + 0.328 687 807 365 12;
  • 51) 0.328 687 807 365 12 × 2 = 0 + 0.657 375 614 730 24;
  • 52) 0.657 375 614 730 24 × 2 = 1 + 0.314 751 229 460 48;
  • 53) 0.314 751 229 460 48 × 2 = 0 + 0.629 502 458 920 96;

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:


0.295 779 513 082 38(10) =


0.0100 1011 1011 1000 0011 0100 1100 0111 1000 0100 0000 0000 0001 0(2)

5. Positive number before normalization:

57.295 779 513 082 38(10) =


11 1001.0100 1011 1011 1000 0011 0100 1100 0111 1000 0100 0000 0000 0001 0(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:


57.295 779 513 082 38(10) =


11 1001.0100 1011 1011 1000 0011 0100 1100 0111 1000 0100 0000 0000 0001 0(2) =


11 1001.0100 1011 1011 1000 0011 0100 1100 0111 1000 0100 0000 0000 0001 0(2) × 20 =


1.1100 1010 0101 1101 1100 0001 1010 0110 0011 1100 0010 0000 0000 0000 10(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):
1.1100 1010 0101 1101 1100 0001 1010 0110 0011 1100 0010 0000 0000 0000 10


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. 1100 1010 0101 1101 1100 0001 1010 0110 0011 1100 0010 0000 0000 00 0010 =


1100 1010 0101 1101 1100 0001 1010 0110 0011 1100 0010 0000 0000


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) =
1100 1010 0101 1101 1100 0001 1010 0110 0011 1100 0010 0000 0000


Decimal number 57.295 779 513 082 38 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0100 - 1100 1010 0101 1101 1100 0001 1010 0110 0011 1100 0010 0000 0000

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