-24.901 900 000 000 011 5 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -24.901 900 000 000 011 5(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
-24.901 900 000 000 011 5(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. Start with the positive version of the number:

|-24.901 900 000 000 011 5| = 24.901 900 000 000 011 5


2. First, convert to binary (in base 2) the integer part: 24.
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;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

3. 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.

24(10) =


1 1000(2)


4. Convert to binary (base 2) the fractional part: 0.901 900 000 000 011 5.

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) 0.901 900 000 000 011 5 × 2 = 1 + 0.803 800 000 000 023;
  • 2) 0.803 800 000 000 023 × 2 = 1 + 0.607 600 000 000 046;
  • 3) 0.607 600 000 000 046 × 2 = 1 + 0.215 200 000 000 092;
  • 4) 0.215 200 000 000 092 × 2 = 0 + 0.430 400 000 000 184;
  • 5) 0.430 400 000 000 184 × 2 = 0 + 0.860 800 000 000 368;
  • 6) 0.860 800 000 000 368 × 2 = 1 + 0.721 600 000 000 736;
  • 7) 0.721 600 000 000 736 × 2 = 1 + 0.443 200 000 001 472;
  • 8) 0.443 200 000 001 472 × 2 = 0 + 0.886 400 000 002 944;
  • 9) 0.886 400 000 002 944 × 2 = 1 + 0.772 800 000 005 888;
  • 10) 0.772 800 000 005 888 × 2 = 1 + 0.545 600 000 011 776;
  • 11) 0.545 600 000 011 776 × 2 = 1 + 0.091 200 000 023 552;
  • 12) 0.091 200 000 023 552 × 2 = 0 + 0.182 400 000 047 104;
  • 13) 0.182 400 000 047 104 × 2 = 0 + 0.364 800 000 094 208;
  • 14) 0.364 800 000 094 208 × 2 = 0 + 0.729 600 000 188 416;
  • 15) 0.729 600 000 188 416 × 2 = 1 + 0.459 200 000 376 832;
  • 16) 0.459 200 000 376 832 × 2 = 0 + 0.918 400 000 753 664;
  • 17) 0.918 400 000 753 664 × 2 = 1 + 0.836 800 001 507 328;
  • 18) 0.836 800 001 507 328 × 2 = 1 + 0.673 600 003 014 656;
  • 19) 0.673 600 003 014 656 × 2 = 1 + 0.347 200 006 029 312;
  • 20) 0.347 200 006 029 312 × 2 = 0 + 0.694 400 012 058 624;
  • 21) 0.694 400 012 058 624 × 2 = 1 + 0.388 800 024 117 248;
  • 22) 0.388 800 024 117 248 × 2 = 0 + 0.777 600 048 234 496;
  • 23) 0.777 600 048 234 496 × 2 = 1 + 0.555 200 096 468 992;
  • 24) 0.555 200 096 468 992 × 2 = 1 + 0.110 400 192 937 984;
  • 25) 0.110 400 192 937 984 × 2 = 0 + 0.220 800 385 875 968;
  • 26) 0.220 800 385 875 968 × 2 = 0 + 0.441 600 771 751 936;
  • 27) 0.441 600 771 751 936 × 2 = 0 + 0.883 201 543 503 872;
  • 28) 0.883 201 543 503 872 × 2 = 1 + 0.766 403 087 007 744;
  • 29) 0.766 403 087 007 744 × 2 = 1 + 0.532 806 174 015 488;
  • 30) 0.532 806 174 015 488 × 2 = 1 + 0.065 612 348 030 976;
  • 31) 0.065 612 348 030 976 × 2 = 0 + 0.131 224 696 061 952;
  • 32) 0.131 224 696 061 952 × 2 = 0 + 0.262 449 392 123 904;
  • 33) 0.262 449 392 123 904 × 2 = 0 + 0.524 898 784 247 808;
  • 34) 0.524 898 784 247 808 × 2 = 1 + 0.049 797 568 495 616;
  • 35) 0.049 797 568 495 616 × 2 = 0 + 0.099 595 136 991 232;
  • 36) 0.099 595 136 991 232 × 2 = 0 + 0.199 190 273 982 464;
  • 37) 0.199 190 273 982 464 × 2 = 0 + 0.398 380 547 964 928;
  • 38) 0.398 380 547 964 928 × 2 = 0 + 0.796 761 095 929 856;
  • 39) 0.796 761 095 929 856 × 2 = 1 + 0.593 522 191 859 712;
  • 40) 0.593 522 191 859 712 × 2 = 1 + 0.187 044 383 719 424;
  • 41) 0.187 044 383 719 424 × 2 = 0 + 0.374 088 767 438 848;
  • 42) 0.374 088 767 438 848 × 2 = 0 + 0.748 177 534 877 696;
  • 43) 0.748 177 534 877 696 × 2 = 1 + 0.496 355 069 755 392;
  • 44) 0.496 355 069 755 392 × 2 = 0 + 0.992 710 139 510 784;
  • 45) 0.992 710 139 510 784 × 2 = 1 + 0.985 420 279 021 568;
  • 46) 0.985 420 279 021 568 × 2 = 1 + 0.970 840 558 043 136;
  • 47) 0.970 840 558 043 136 × 2 = 1 + 0.941 681 116 086 272;
  • 48) 0.941 681 116 086 272 × 2 = 1 + 0.883 362 232 172 544;
  • 49) 0.883 362 232 172 544 × 2 = 1 + 0.766 724 464 345 088;
  • 50) 0.766 724 464 345 088 × 2 = 1 + 0.533 448 928 690 176;
  • 51) 0.533 448 928 690 176 × 2 = 1 + 0.066 897 857 380 352;
  • 52) 0.066 897 857 380 352 × 2 = 0 + 0.133 795 714 760 704;
  • 53) 0.133 795 714 760 704 × 2 = 0 + 0.267 591 429 521 408;

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).


5. 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:


0.901 900 000 000 011 5(10) =


0.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111 1110 0(2)

6. Positive number before normalization:

24.901 900 000 000 011 5(10) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111 1110 0(2)

7. 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:


24.901 900 000 000 011 5(10) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111 1110 0(2) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111 1110 0(2) × 20 =


1.1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111 1110 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):
1.1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111 1110 0


9. 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)


10. 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;

11. 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)


12. 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. 1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111 1 1100 =


1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
100 0000 0011


Mantissa (52 bits) =
1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111


Decimal number -24.901 900 000 000 011 5 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0011 - 1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0010 1111


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