-24.901 900 000 000 014 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -24.901 900 000 000 014(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
-24.901 900 000 000 014(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:

|-24.901 900 000 000 014| = 24.901 900 000 000 014


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: 0.901 900 000 000 014.

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) 0.901 900 000 000 014 × 2 = 1 + 0.803 800 000 000 028;
  • 2) 0.803 800 000 000 028 × 2 = 1 + 0.607 600 000 000 056;
  • 3) 0.607 600 000 000 056 × 2 = 1 + 0.215 200 000 000 112;
  • 4) 0.215 200 000 000 112 × 2 = 0 + 0.430 400 000 000 224;
  • 5) 0.430 400 000 000 224 × 2 = 0 + 0.860 800 000 000 448;
  • 6) 0.860 800 000 000 448 × 2 = 1 + 0.721 600 000 000 896;
  • 7) 0.721 600 000 000 896 × 2 = 1 + 0.443 200 000 001 792;
  • 8) 0.443 200 000 001 792 × 2 = 0 + 0.886 400 000 003 584;
  • 9) 0.886 400 000 003 584 × 2 = 1 + 0.772 800 000 007 168;
  • 10) 0.772 800 000 007 168 × 2 = 1 + 0.545 600 000 014 336;
  • 11) 0.545 600 000 014 336 × 2 = 1 + 0.091 200 000 028 672;
  • 12) 0.091 200 000 028 672 × 2 = 0 + 0.182 400 000 057 344;
  • 13) 0.182 400 000 057 344 × 2 = 0 + 0.364 800 000 114 688;
  • 14) 0.364 800 000 114 688 × 2 = 0 + 0.729 600 000 229 376;
  • 15) 0.729 600 000 229 376 × 2 = 1 + 0.459 200 000 458 752;
  • 16) 0.459 200 000 458 752 × 2 = 0 + 0.918 400 000 917 504;
  • 17) 0.918 400 000 917 504 × 2 = 1 + 0.836 800 001 835 008;
  • 18) 0.836 800 001 835 008 × 2 = 1 + 0.673 600 003 670 016;
  • 19) 0.673 600 003 670 016 × 2 = 1 + 0.347 200 007 340 032;
  • 20) 0.347 200 007 340 032 × 2 = 0 + 0.694 400 014 680 064;
  • 21) 0.694 400 014 680 064 × 2 = 1 + 0.388 800 029 360 128;
  • 22) 0.388 800 029 360 128 × 2 = 0 + 0.777 600 058 720 256;
  • 23) 0.777 600 058 720 256 × 2 = 1 + 0.555 200 117 440 512;
  • 24) 0.555 200 117 440 512 × 2 = 1 + 0.110 400 234 881 024;
  • 25) 0.110 400 234 881 024 × 2 = 0 + 0.220 800 469 762 048;
  • 26) 0.220 800 469 762 048 × 2 = 0 + 0.441 600 939 524 096;
  • 27) 0.441 600 939 524 096 × 2 = 0 + 0.883 201 879 048 192;
  • 28) 0.883 201 879 048 192 × 2 = 1 + 0.766 403 758 096 384;
  • 29) 0.766 403 758 096 384 × 2 = 1 + 0.532 807 516 192 768;
  • 30) 0.532 807 516 192 768 × 2 = 1 + 0.065 615 032 385 536;
  • 31) 0.065 615 032 385 536 × 2 = 0 + 0.131 230 064 771 072;
  • 32) 0.131 230 064 771 072 × 2 = 0 + 0.262 460 129 542 144;
  • 33) 0.262 460 129 542 144 × 2 = 0 + 0.524 920 259 084 288;
  • 34) 0.524 920 259 084 288 × 2 = 1 + 0.049 840 518 168 576;
  • 35) 0.049 840 518 168 576 × 2 = 0 + 0.099 681 036 337 152;
  • 36) 0.099 681 036 337 152 × 2 = 0 + 0.199 362 072 674 304;
  • 37) 0.199 362 072 674 304 × 2 = 0 + 0.398 724 145 348 608;
  • 38) 0.398 724 145 348 608 × 2 = 0 + 0.797 448 290 697 216;
  • 39) 0.797 448 290 697 216 × 2 = 1 + 0.594 896 581 394 432;
  • 40) 0.594 896 581 394 432 × 2 = 1 + 0.189 793 162 788 864;
  • 41) 0.189 793 162 788 864 × 2 = 0 + 0.379 586 325 577 728;
  • 42) 0.379 586 325 577 728 × 2 = 0 + 0.759 172 651 155 456;
  • 43) 0.759 172 651 155 456 × 2 = 1 + 0.518 345 302 310 912;
  • 44) 0.518 345 302 310 912 × 2 = 1 + 0.036 690 604 621 824;
  • 45) 0.036 690 604 621 824 × 2 = 0 + 0.073 381 209 243 648;
  • 46) 0.073 381 209 243 648 × 2 = 0 + 0.146 762 418 487 296;
  • 47) 0.146 762 418 487 296 × 2 = 0 + 0.293 524 836 974 592;
  • 48) 0.293 524 836 974 592 × 2 = 0 + 0.587 049 673 949 184;
  • 49) 0.587 049 673 949 184 × 2 = 1 + 0.174 099 347 898 368;
  • 50) 0.174 099 347 898 368 × 2 = 0 + 0.348 198 695 796 736;
  • 51) 0.348 198 695 796 736 × 2 = 0 + 0.696 397 391 593 472;
  • 52) 0.696 397 391 593 472 × 2 = 1 + 0.392 794 783 186 944;
  • 53) 0.392 794 783 186 944 × 2 = 0 + 0.785 589 566 373 888;

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:


0.901 900 000 000 014(10) =


0.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0011 0000 1001 0(2)

6. Positive number before normalization:

24.901 900 000 000 014(10) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0011 0000 1001 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:


24.901 900 000 000 014(10) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0011 0000 1001 0(2) =


1 1000.1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0011 0000 1001 0(2) × 20 =


1.1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0011 0000 1001 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 0011 0000 1001 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 0011 0000 1 0010 =


1000 1110 0110 1110 0010 1110 1011 0001 1100 0100 0011 0011 0000


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 0011 0000


Decimal number -24.901 900 000 000 014 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 0011 0000


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