0.338 327 950 288 417 9 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 0.338 327 950 288 417 9(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
0.338 327 950 288 417 9(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: 0.
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;
  • 0 ÷ 2 = 0 + 0;

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.

0(10) =


0(2)


3. Convert to binary (base 2) the fractional part: 0.338 327 950 288 417 9.

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) 0.338 327 950 288 417 9 × 2 = 0 + 0.676 655 900 576 835 8;
  • 2) 0.676 655 900 576 835 8 × 2 = 1 + 0.353 311 801 153 671 6;
  • 3) 0.353 311 801 153 671 6 × 2 = 0 + 0.706 623 602 307 343 2;
  • 4) 0.706 623 602 307 343 2 × 2 = 1 + 0.413 247 204 614 686 4;
  • 5) 0.413 247 204 614 686 4 × 2 = 0 + 0.826 494 409 229 372 8;
  • 6) 0.826 494 409 229 372 8 × 2 = 1 + 0.652 988 818 458 745 6;
  • 7) 0.652 988 818 458 745 6 × 2 = 1 + 0.305 977 636 917 491 2;
  • 8) 0.305 977 636 917 491 2 × 2 = 0 + 0.611 955 273 834 982 4;
  • 9) 0.611 955 273 834 982 4 × 2 = 1 + 0.223 910 547 669 964 8;
  • 10) 0.223 910 547 669 964 8 × 2 = 0 + 0.447 821 095 339 929 6;
  • 11) 0.447 821 095 339 929 6 × 2 = 0 + 0.895 642 190 679 859 2;
  • 12) 0.895 642 190 679 859 2 × 2 = 1 + 0.791 284 381 359 718 4;
  • 13) 0.791 284 381 359 718 4 × 2 = 1 + 0.582 568 762 719 436 8;
  • 14) 0.582 568 762 719 436 8 × 2 = 1 + 0.165 137 525 438 873 6;
  • 15) 0.165 137 525 438 873 6 × 2 = 0 + 0.330 275 050 877 747 2;
  • 16) 0.330 275 050 877 747 2 × 2 = 0 + 0.660 550 101 755 494 4;
  • 17) 0.660 550 101 755 494 4 × 2 = 1 + 0.321 100 203 510 988 8;
  • 18) 0.321 100 203 510 988 8 × 2 = 0 + 0.642 200 407 021 977 6;
  • 19) 0.642 200 407 021 977 6 × 2 = 1 + 0.284 400 814 043 955 2;
  • 20) 0.284 400 814 043 955 2 × 2 = 0 + 0.568 801 628 087 910 4;
  • 21) 0.568 801 628 087 910 4 × 2 = 1 + 0.137 603 256 175 820 8;
  • 22) 0.137 603 256 175 820 8 × 2 = 0 + 0.275 206 512 351 641 6;
  • 23) 0.275 206 512 351 641 6 × 2 = 0 + 0.550 413 024 703 283 2;
  • 24) 0.550 413 024 703 283 2 × 2 = 1 + 0.100 826 049 406 566 4;
  • 25) 0.100 826 049 406 566 4 × 2 = 0 + 0.201 652 098 813 132 8;
  • 26) 0.201 652 098 813 132 8 × 2 = 0 + 0.403 304 197 626 265 6;
  • 27) 0.403 304 197 626 265 6 × 2 = 0 + 0.806 608 395 252 531 2;
  • 28) 0.806 608 395 252 531 2 × 2 = 1 + 0.613 216 790 505 062 4;
  • 29) 0.613 216 790 505 062 4 × 2 = 1 + 0.226 433 581 010 124 8;
  • 30) 0.226 433 581 010 124 8 × 2 = 0 + 0.452 867 162 020 249 6;
  • 31) 0.452 867 162 020 249 6 × 2 = 0 + 0.905 734 324 040 499 2;
  • 32) 0.905 734 324 040 499 2 × 2 = 1 + 0.811 468 648 080 998 4;
  • 33) 0.811 468 648 080 998 4 × 2 = 1 + 0.622 937 296 161 996 8;
  • 34) 0.622 937 296 161 996 8 × 2 = 1 + 0.245 874 592 323 993 6;
  • 35) 0.245 874 592 323 993 6 × 2 = 0 + 0.491 749 184 647 987 2;
  • 36) 0.491 749 184 647 987 2 × 2 = 0 + 0.983 498 369 295 974 4;
  • 37) 0.983 498 369 295 974 4 × 2 = 1 + 0.966 996 738 591 948 8;
  • 38) 0.966 996 738 591 948 8 × 2 = 1 + 0.933 993 477 183 897 6;
  • 39) 0.933 993 477 183 897 6 × 2 = 1 + 0.867 986 954 367 795 2;
  • 40) 0.867 986 954 367 795 2 × 2 = 1 + 0.735 973 908 735 590 4;
  • 41) 0.735 973 908 735 590 4 × 2 = 1 + 0.471 947 817 471 180 8;
  • 42) 0.471 947 817 471 180 8 × 2 = 0 + 0.943 895 634 942 361 6;
  • 43) 0.943 895 634 942 361 6 × 2 = 1 + 0.887 791 269 884 723 2;
  • 44) 0.887 791 269 884 723 2 × 2 = 1 + 0.775 582 539 769 446 4;
  • 45) 0.775 582 539 769 446 4 × 2 = 1 + 0.551 165 079 538 892 8;
  • 46) 0.551 165 079 538 892 8 × 2 = 1 + 0.102 330 159 077 785 6;
  • 47) 0.102 330 159 077 785 6 × 2 = 0 + 0.204 660 318 155 571 2;
  • 48) 0.204 660 318 155 571 2 × 2 = 0 + 0.409 320 636 311 142 4;
  • 49) 0.409 320 636 311 142 4 × 2 = 0 + 0.818 641 272 622 284 8;
  • 50) 0.818 641 272 622 284 8 × 2 = 1 + 0.637 282 545 244 569 6;
  • 51) 0.637 282 545 244 569 6 × 2 = 1 + 0.274 565 090 489 139 2;
  • 52) 0.274 565 090 489 139 2 × 2 = 0 + 0.549 130 180 978 278 4;
  • 53) 0.549 130 180 978 278 4 × 2 = 1 + 0.098 260 361 956 556 8;
  • 54) 0.098 260 361 956 556 8 × 2 = 0 + 0.196 520 723 913 113 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:


0.338 327 950 288 417 9(10) =


0.0101 0110 1001 1100 1010 1001 0001 1001 1100 1111 1011 1100 0110 10(2)

5. Positive number before normalization:

0.338 327 950 288 417 9(10) =


0.0101 0110 1001 1100 1010 1001 0001 1001 1100 1111 1011 1100 0110 10(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 2 positions to the right, so that only one non zero digit remains to the left of it:


0.338 327 950 288 417 9(10) =


0.0101 0110 1001 1100 1010 1001 0001 1001 1100 1111 1011 1100 0110 10(2) =


0.0101 0110 1001 1100 1010 1001 0001 1001 1100 1111 1011 1100 0110 10(2) × 20 =


1.0101 1010 0111 0010 1010 0100 0110 0111 0011 1110 1111 0001 1010(2) × 2-2


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): -2


Mantissa (not normalized):
1.0101 1010 0111 0010 1010 0100 0110 0111 0011 1110 1111 0001 1010


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


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


(-2 + 1 023)(10) =


1 021(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;
  • 1 021 ÷ 2 = 510 + 1;
  • 510 ÷ 2 = 255 + 0;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1021(10) =


011 1111 1101(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 0101 1010 0111 0010 1010 0100 0110 0111 0011 1110 1111 0001 1010 =


0101 1010 0111 0010 1010 0100 0110 0111 0011 1110 1111 0001 1010


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) =
011 1111 1101


Mantissa (52 bits) =
0101 1010 0111 0010 1010 0100 0110 0111 0011 1110 1111 0001 1010


Decimal number 0.338 327 950 288 417 9 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1101 - 0101 1010 0111 0010 1010 0100 0110 0111 0011 1110 1111 0001 1010


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