32.003 906 726 895 372 971 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 32.003 906 726 895 372 971 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
32.003 906 726 895 372 971 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: 32.
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;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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.

32(10) =


10 0000(2)


3. Convert to binary (base 2) the fractional part: 0.003 906 726 895 372 971 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) 0.003 906 726 895 372 971 2 × 2 = 0 + 0.007 813 453 790 745 942 4;
  • 2) 0.007 813 453 790 745 942 4 × 2 = 0 + 0.015 626 907 581 491 884 8;
  • 3) 0.015 626 907 581 491 884 8 × 2 = 0 + 0.031 253 815 162 983 769 6;
  • 4) 0.031 253 815 162 983 769 6 × 2 = 0 + 0.062 507 630 325 967 539 2;
  • 5) 0.062 507 630 325 967 539 2 × 2 = 0 + 0.125 015 260 651 935 078 4;
  • 6) 0.125 015 260 651 935 078 4 × 2 = 0 + 0.250 030 521 303 870 156 8;
  • 7) 0.250 030 521 303 870 156 8 × 2 = 0 + 0.500 061 042 607 740 313 6;
  • 8) 0.500 061 042 607 740 313 6 × 2 = 1 + 0.000 122 085 215 480 627 2;
  • 9) 0.000 122 085 215 480 627 2 × 2 = 0 + 0.000 244 170 430 961 254 4;
  • 10) 0.000 244 170 430 961 254 4 × 2 = 0 + 0.000 488 340 861 922 508 8;
  • 11) 0.000 488 340 861 922 508 8 × 2 = 0 + 0.000 976 681 723 845 017 6;
  • 12) 0.000 976 681 723 845 017 6 × 2 = 0 + 0.001 953 363 447 690 035 2;
  • 13) 0.001 953 363 447 690 035 2 × 2 = 0 + 0.003 906 726 895 380 070 4;
  • 14) 0.003 906 726 895 380 070 4 × 2 = 0 + 0.007 813 453 790 760 140 8;
  • 15) 0.007 813 453 790 760 140 8 × 2 = 0 + 0.015 626 907 581 520 281 6;
  • 16) 0.015 626 907 581 520 281 6 × 2 = 0 + 0.031 253 815 163 040 563 2;
  • 17) 0.031 253 815 163 040 563 2 × 2 = 0 + 0.062 507 630 326 081 126 4;
  • 18) 0.062 507 630 326 081 126 4 × 2 = 0 + 0.125 015 260 652 162 252 8;
  • 19) 0.125 015 260 652 162 252 8 × 2 = 0 + 0.250 030 521 304 324 505 6;
  • 20) 0.250 030 521 304 324 505 6 × 2 = 0 + 0.500 061 042 608 649 011 2;
  • 21) 0.500 061 042 608 649 011 2 × 2 = 1 + 0.000 122 085 217 298 022 4;
  • 22) 0.000 122 085 217 298 022 4 × 2 = 0 + 0.000 244 170 434 596 044 8;
  • 23) 0.000 244 170 434 596 044 8 × 2 = 0 + 0.000 488 340 869 192 089 6;
  • 24) 0.000 488 340 869 192 089 6 × 2 = 0 + 0.000 976 681 738 384 179 2;
  • 25) 0.000 976 681 738 384 179 2 × 2 = 0 + 0.001 953 363 476 768 358 4;
  • 26) 0.001 953 363 476 768 358 4 × 2 = 0 + 0.003 906 726 953 536 716 8;
  • 27) 0.003 906 726 953 536 716 8 × 2 = 0 + 0.007 813 453 907 073 433 6;
  • 28) 0.007 813 453 907 073 433 6 × 2 = 0 + 0.015 626 907 814 146 867 2;
  • 29) 0.015 626 907 814 146 867 2 × 2 = 0 + 0.031 253 815 628 293 734 4;
  • 30) 0.031 253 815 628 293 734 4 × 2 = 0 + 0.062 507 631 256 587 468 8;
  • 31) 0.062 507 631 256 587 468 8 × 2 = 0 + 0.125 015 262 513 174 937 6;
  • 32) 0.125 015 262 513 174 937 6 × 2 = 0 + 0.250 030 525 026 349 875 2;
  • 33) 0.250 030 525 026 349 875 2 × 2 = 0 + 0.500 061 050 052 699 750 4;
  • 34) 0.500 061 050 052 699 750 4 × 2 = 1 + 0.000 122 100 105 399 500 8;
  • 35) 0.000 122 100 105 399 500 8 × 2 = 0 + 0.000 244 200 210 799 001 6;
  • 36) 0.000 244 200 210 799 001 6 × 2 = 0 + 0.000 488 400 421 598 003 2;
  • 37) 0.000 488 400 421 598 003 2 × 2 = 0 + 0.000 976 800 843 196 006 4;
  • 38) 0.000 976 800 843 196 006 4 × 2 = 0 + 0.001 953 601 686 392 012 8;
  • 39) 0.001 953 601 686 392 012 8 × 2 = 0 + 0.003 907 203 372 784 025 6;
  • 40) 0.003 907 203 372 784 025 6 × 2 = 0 + 0.007 814 406 745 568 051 2;
  • 41) 0.007 814 406 745 568 051 2 × 2 = 0 + 0.015 628 813 491 136 102 4;
  • 42) 0.015 628 813 491 136 102 4 × 2 = 0 + 0.031 257 626 982 272 204 8;
  • 43) 0.031 257 626 982 272 204 8 × 2 = 0 + 0.062 515 253 964 544 409 6;
  • 44) 0.062 515 253 964 544 409 6 × 2 = 0 + 0.125 030 507 929 088 819 2;
  • 45) 0.125 030 507 929 088 819 2 × 2 = 0 + 0.250 061 015 858 177 638 4;
  • 46) 0.250 061 015 858 177 638 4 × 2 = 0 + 0.500 122 031 716 355 276 8;
  • 47) 0.500 122 031 716 355 276 8 × 2 = 1 + 0.000 244 063 432 710 553 6;
  • 48) 0.000 244 063 432 710 553 6 × 2 = 0 + 0.000 488 126 865 421 107 2;
  • 49) 0.000 488 126 865 421 107 2 × 2 = 0 + 0.000 976 253 730 842 214 4;
  • 50) 0.000 976 253 730 842 214 4 × 2 = 0 + 0.001 952 507 461 684 428 8;
  • 51) 0.001 952 507 461 684 428 8 × 2 = 0 + 0.003 905 014 923 368 857 6;
  • 52) 0.003 905 014 923 368 857 6 × 2 = 0 + 0.007 810 029 846 737 715 2;
  • 53) 0.007 810 029 846 737 715 2 × 2 = 0 + 0.015 620 059 693 475 430 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:


0.003 906 726 895 372 971 2(10) =


0.0000 0001 0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0(2)

5. Positive number before normalization:

32.003 906 726 895 372 971 2(10) =


10 0000.0000 0001 0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 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:


32.003 906 726 895 372 971 2(10) =


10 0000.0000 0001 0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0(2) =


10 0000.0000 0001 0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0(2) × 20 =


1.0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0001 0000 00(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):
1.0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0001 0000 00


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. 0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0001 00 0000 =


0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0001


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) =
0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0001


Decimal number 32.003 906 726 895 372 971 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0100 - 0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0001


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