27.257 299 999 999 997 258 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 27.257 299 999 999 997 258 2(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
27.257 299 999 999 997 258 2(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: 0.257 299 999 999 997 258 2.

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) 0.257 299 999 999 997 258 2 × 2 = 0 + 0.514 599 999 999 994 516 4;
  • 2) 0.514 599 999 999 994 516 4 × 2 = 1 + 0.029 199 999 999 989 032 8;
  • 3) 0.029 199 999 999 989 032 8 × 2 = 0 + 0.058 399 999 999 978 065 6;
  • 4) 0.058 399 999 999 978 065 6 × 2 = 0 + 0.116 799 999 999 956 131 2;
  • 5) 0.116 799 999 999 956 131 2 × 2 = 0 + 0.233 599 999 999 912 262 4;
  • 6) 0.233 599 999 999 912 262 4 × 2 = 0 + 0.467 199 999 999 824 524 8;
  • 7) 0.467 199 999 999 824 524 8 × 2 = 0 + 0.934 399 999 999 649 049 6;
  • 8) 0.934 399 999 999 649 049 6 × 2 = 1 + 0.868 799 999 999 298 099 2;
  • 9) 0.868 799 999 999 298 099 2 × 2 = 1 + 0.737 599 999 998 596 198 4;
  • 10) 0.737 599 999 998 596 198 4 × 2 = 1 + 0.475 199 999 997 192 396 8;
  • 11) 0.475 199 999 997 192 396 8 × 2 = 0 + 0.950 399 999 994 384 793 6;
  • 12) 0.950 399 999 994 384 793 6 × 2 = 1 + 0.900 799 999 988 769 587 2;
  • 13) 0.900 799 999 988 769 587 2 × 2 = 1 + 0.801 599 999 977 539 174 4;
  • 14) 0.801 599 999 977 539 174 4 × 2 = 1 + 0.603 199 999 955 078 348 8;
  • 15) 0.603 199 999 955 078 348 8 × 2 = 1 + 0.206 399 999 910 156 697 6;
  • 16) 0.206 399 999 910 156 697 6 × 2 = 0 + 0.412 799 999 820 313 395 2;
  • 17) 0.412 799 999 820 313 395 2 × 2 = 0 + 0.825 599 999 640 626 790 4;
  • 18) 0.825 599 999 640 626 790 4 × 2 = 1 + 0.651 199 999 281 253 580 8;
  • 19) 0.651 199 999 281 253 580 8 × 2 = 1 + 0.302 399 998 562 507 161 6;
  • 20) 0.302 399 998 562 507 161 6 × 2 = 0 + 0.604 799 997 125 014 323 2;
  • 21) 0.604 799 997 125 014 323 2 × 2 = 1 + 0.209 599 994 250 028 646 4;
  • 22) 0.209 599 994 250 028 646 4 × 2 = 0 + 0.419 199 988 500 057 292 8;
  • 23) 0.419 199 988 500 057 292 8 × 2 = 0 + 0.838 399 977 000 114 585 6;
  • 24) 0.838 399 977 000 114 585 6 × 2 = 1 + 0.676 799 954 000 229 171 2;
  • 25) 0.676 799 954 000 229 171 2 × 2 = 1 + 0.353 599 908 000 458 342 4;
  • 26) 0.353 599 908 000 458 342 4 × 2 = 0 + 0.707 199 816 000 916 684 8;
  • 27) 0.707 199 816 000 916 684 8 × 2 = 1 + 0.414 399 632 001 833 369 6;
  • 28) 0.414 399 632 001 833 369 6 × 2 = 0 + 0.828 799 264 003 666 739 2;
  • 29) 0.828 799 264 003 666 739 2 × 2 = 1 + 0.657 598 528 007 333 478 4;
  • 30) 0.657 598 528 007 333 478 4 × 2 = 1 + 0.315 197 056 014 666 956 8;
  • 31) 0.315 197 056 014 666 956 8 × 2 = 0 + 0.630 394 112 029 333 913 6;
  • 32) 0.630 394 112 029 333 913 6 × 2 = 1 + 0.260 788 224 058 667 827 2;
  • 33) 0.260 788 224 058 667 827 2 × 2 = 0 + 0.521 576 448 117 335 654 4;
  • 34) 0.521 576 448 117 335 654 4 × 2 = 1 + 0.043 152 896 234 671 308 8;
  • 35) 0.043 152 896 234 671 308 8 × 2 = 0 + 0.086 305 792 469 342 617 6;
  • 36) 0.086 305 792 469 342 617 6 × 2 = 0 + 0.172 611 584 938 685 235 2;
  • 37) 0.172 611 584 938 685 235 2 × 2 = 0 + 0.345 223 169 877 370 470 4;
  • 38) 0.345 223 169 877 370 470 4 × 2 = 0 + 0.690 446 339 754 740 940 8;
  • 39) 0.690 446 339 754 740 940 8 × 2 = 1 + 0.380 892 679 509 481 881 6;
  • 40) 0.380 892 679 509 481 881 6 × 2 = 0 + 0.761 785 359 018 963 763 2;
  • 41) 0.761 785 359 018 963 763 2 × 2 = 1 + 0.523 570 718 037 927 526 4;
  • 42) 0.523 570 718 037 927 526 4 × 2 = 1 + 0.047 141 436 075 855 052 8;
  • 43) 0.047 141 436 075 855 052 8 × 2 = 0 + 0.094 282 872 151 710 105 6;
  • 44) 0.094 282 872 151 710 105 6 × 2 = 0 + 0.188 565 744 303 420 211 2;
  • 45) 0.188 565 744 303 420 211 2 × 2 = 0 + 0.377 131 488 606 840 422 4;
  • 46) 0.377 131 488 606 840 422 4 × 2 = 0 + 0.754 262 977 213 680 844 8;
  • 47) 0.754 262 977 213 680 844 8 × 2 = 1 + 0.508 525 954 427 361 689 6;
  • 48) 0.508 525 954 427 361 689 6 × 2 = 1 + 0.017 051 908 854 723 379 2;
  • 49) 0.017 051 908 854 723 379 2 × 2 = 0 + 0.034 103 817 709 446 758 4;
  • 50) 0.034 103 817 709 446 758 4 × 2 = 0 + 0.068 207 635 418 893 516 8;
  • 51) 0.068 207 635 418 893 516 8 × 2 = 0 + 0.136 415 270 837 787 033 6;
  • 52) 0.136 415 270 837 787 033 6 × 2 = 0 + 0.272 830 541 675 574 067 2;
  • 53) 0.272 830 541 675 574 067 2 × 2 = 0 + 0.545 661 083 351 148 134 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:


0.257 299 999 999 997 258 2(10) =


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

5. Positive number before normalization:

27.257 299 999 999 997 258 2(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:


27.257 299 999 999 997 258 2(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 27.257 299 999 999 997 258 2 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