27.257 299 999 999 997 263 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 27.257 299 999 999 997 263 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
27.257 299 999 999 997 263 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: 27.
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;
  • 27 ÷ 2 = 13 + 1;
  • 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.

27(10) =


1 1011(2)


3. Convert to binary (base 2) the fractional part: 0.257 299 999 999 997 263 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) 0.257 299 999 999 997 263 3 × 2 = 0 + 0.514 599 999 999 994 526 6;
  • 2) 0.514 599 999 999 994 526 6 × 2 = 1 + 0.029 199 999 999 989 053 2;
  • 3) 0.029 199 999 999 989 053 2 × 2 = 0 + 0.058 399 999 999 978 106 4;
  • 4) 0.058 399 999 999 978 106 4 × 2 = 0 + 0.116 799 999 999 956 212 8;
  • 5) 0.116 799 999 999 956 212 8 × 2 = 0 + 0.233 599 999 999 912 425 6;
  • 6) 0.233 599 999 999 912 425 6 × 2 = 0 + 0.467 199 999 999 824 851 2;
  • 7) 0.467 199 999 999 824 851 2 × 2 = 0 + 0.934 399 999 999 649 702 4;
  • 8) 0.934 399 999 999 649 702 4 × 2 = 1 + 0.868 799 999 999 299 404 8;
  • 9) 0.868 799 999 999 299 404 8 × 2 = 1 + 0.737 599 999 998 598 809 6;
  • 10) 0.737 599 999 998 598 809 6 × 2 = 1 + 0.475 199 999 997 197 619 2;
  • 11) 0.475 199 999 997 197 619 2 × 2 = 0 + 0.950 399 999 994 395 238 4;
  • 12) 0.950 399 999 994 395 238 4 × 2 = 1 + 0.900 799 999 988 790 476 8;
  • 13) 0.900 799 999 988 790 476 8 × 2 = 1 + 0.801 599 999 977 580 953 6;
  • 14) 0.801 599 999 977 580 953 6 × 2 = 1 + 0.603 199 999 955 161 907 2;
  • 15) 0.603 199 999 955 161 907 2 × 2 = 1 + 0.206 399 999 910 323 814 4;
  • 16) 0.206 399 999 910 323 814 4 × 2 = 0 + 0.412 799 999 820 647 628 8;
  • 17) 0.412 799 999 820 647 628 8 × 2 = 0 + 0.825 599 999 641 295 257 6;
  • 18) 0.825 599 999 641 295 257 6 × 2 = 1 + 0.651 199 999 282 590 515 2;
  • 19) 0.651 199 999 282 590 515 2 × 2 = 1 + 0.302 399 998 565 181 030 4;
  • 20) 0.302 399 998 565 181 030 4 × 2 = 0 + 0.604 799 997 130 362 060 8;
  • 21) 0.604 799 997 130 362 060 8 × 2 = 1 + 0.209 599 994 260 724 121 6;
  • 22) 0.209 599 994 260 724 121 6 × 2 = 0 + 0.419 199 988 521 448 243 2;
  • 23) 0.419 199 988 521 448 243 2 × 2 = 0 + 0.838 399 977 042 896 486 4;
  • 24) 0.838 399 977 042 896 486 4 × 2 = 1 + 0.676 799 954 085 792 972 8;
  • 25) 0.676 799 954 085 792 972 8 × 2 = 1 + 0.353 599 908 171 585 945 6;
  • 26) 0.353 599 908 171 585 945 6 × 2 = 0 + 0.707 199 816 343 171 891 2;
  • 27) 0.707 199 816 343 171 891 2 × 2 = 1 + 0.414 399 632 686 343 782 4;
  • 28) 0.414 399 632 686 343 782 4 × 2 = 0 + 0.828 799 265 372 687 564 8;
  • 29) 0.828 799 265 372 687 564 8 × 2 = 1 + 0.657 598 530 745 375 129 6;
  • 30) 0.657 598 530 745 375 129 6 × 2 = 1 + 0.315 197 061 490 750 259 2;
  • 31) 0.315 197 061 490 750 259 2 × 2 = 0 + 0.630 394 122 981 500 518 4;
  • 32) 0.630 394 122 981 500 518 4 × 2 = 1 + 0.260 788 245 963 001 036 8;
  • 33) 0.260 788 245 963 001 036 8 × 2 = 0 + 0.521 576 491 926 002 073 6;
  • 34) 0.521 576 491 926 002 073 6 × 2 = 1 + 0.043 152 983 852 004 147 2;
  • 35) 0.043 152 983 852 004 147 2 × 2 = 0 + 0.086 305 967 704 008 294 4;
  • 36) 0.086 305 967 704 008 294 4 × 2 = 0 + 0.172 611 935 408 016 588 8;
  • 37) 0.172 611 935 408 016 588 8 × 2 = 0 + 0.345 223 870 816 033 177 6;
  • 38) 0.345 223 870 816 033 177 6 × 2 = 0 + 0.690 447 741 632 066 355 2;
  • 39) 0.690 447 741 632 066 355 2 × 2 = 1 + 0.380 895 483 264 132 710 4;
  • 40) 0.380 895 483 264 132 710 4 × 2 = 0 + 0.761 790 966 528 265 420 8;
  • 41) 0.761 790 966 528 265 420 8 × 2 = 1 + 0.523 581 933 056 530 841 6;
  • 42) 0.523 581 933 056 530 841 6 × 2 = 1 + 0.047 163 866 113 061 683 2;
  • 43) 0.047 163 866 113 061 683 2 × 2 = 0 + 0.094 327 732 226 123 366 4;
  • 44) 0.094 327 732 226 123 366 4 × 2 = 0 + 0.188 655 464 452 246 732 8;
  • 45) 0.188 655 464 452 246 732 8 × 2 = 0 + 0.377 310 928 904 493 465 6;
  • 46) 0.377 310 928 904 493 465 6 × 2 = 0 + 0.754 621 857 808 986 931 2;
  • 47) 0.754 621 857 808 986 931 2 × 2 = 1 + 0.509 243 715 617 973 862 4;
  • 48) 0.509 243 715 617 973 862 4 × 2 = 1 + 0.018 487 431 235 947 724 8;
  • 49) 0.018 487 431 235 947 724 8 × 2 = 0 + 0.036 974 862 471 895 449 6;
  • 50) 0.036 974 862 471 895 449 6 × 2 = 0 + 0.073 949 724 943 790 899 2;
  • 51) 0.073 949 724 943 790 899 2 × 2 = 0 + 0.147 899 449 887 581 798 4;
  • 52) 0.147 899 449 887 581 798 4 × 2 = 0 + 0.295 798 899 775 163 596 8;
  • 53) 0.295 798 899 775 163 596 8 × 2 = 0 + 0.591 597 799 550 327 193 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:


0.257 299 999 999 997 263 3(10) =


0.0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0000 0(2)

5. Positive number before normalization:

27.257 299 999 999 997 263 3(10) =


1 1011.0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0000 0(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:


27.257 299 999 999 997 263 3(10) =


1 1011.0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0000 0(2) =


1 1011.0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0000 0(2) × 20 =


1.1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0000 0(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):
1.1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0000 0


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. 1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011 0 0000 =


1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011


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) =
1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011


Decimal number 27.257 299 999 999 997 263 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0011 - 1011 0100 0001 1101 1110 0110 1001 1010 1101 0100 0010 1100 0011


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