2.718 281 828 459 32 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.718 281 828 459 32(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
2.718 281 828 459 32(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: 2.
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;
  • 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.

2(10) =


10(2)


3. Convert to binary (base 2) the fractional part: 0.718 281 828 459 32.

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) 0.718 281 828 459 32 × 2 = 1 + 0.436 563 656 918 64;
  • 2) 0.436 563 656 918 64 × 2 = 0 + 0.873 127 313 837 28;
  • 3) 0.873 127 313 837 28 × 2 = 1 + 0.746 254 627 674 56;
  • 4) 0.746 254 627 674 56 × 2 = 1 + 0.492 509 255 349 12;
  • 5) 0.492 509 255 349 12 × 2 = 0 + 0.985 018 510 698 24;
  • 6) 0.985 018 510 698 24 × 2 = 1 + 0.970 037 021 396 48;
  • 7) 0.970 037 021 396 48 × 2 = 1 + 0.940 074 042 792 96;
  • 8) 0.940 074 042 792 96 × 2 = 1 + 0.880 148 085 585 92;
  • 9) 0.880 148 085 585 92 × 2 = 1 + 0.760 296 171 171 84;
  • 10) 0.760 296 171 171 84 × 2 = 1 + 0.520 592 342 343 68;
  • 11) 0.520 592 342 343 68 × 2 = 1 + 0.041 184 684 687 36;
  • 12) 0.041 184 684 687 36 × 2 = 0 + 0.082 369 369 374 72;
  • 13) 0.082 369 369 374 72 × 2 = 0 + 0.164 738 738 749 44;
  • 14) 0.164 738 738 749 44 × 2 = 0 + 0.329 477 477 498 88;
  • 15) 0.329 477 477 498 88 × 2 = 0 + 0.658 954 954 997 76;
  • 16) 0.658 954 954 997 76 × 2 = 1 + 0.317 909 909 995 52;
  • 17) 0.317 909 909 995 52 × 2 = 0 + 0.635 819 819 991 04;
  • 18) 0.635 819 819 991 04 × 2 = 1 + 0.271 639 639 982 08;
  • 19) 0.271 639 639 982 08 × 2 = 0 + 0.543 279 279 964 16;
  • 20) 0.543 279 279 964 16 × 2 = 1 + 0.086 558 559 928 32;
  • 21) 0.086 558 559 928 32 × 2 = 0 + 0.173 117 119 856 64;
  • 22) 0.173 117 119 856 64 × 2 = 0 + 0.346 234 239 713 28;
  • 23) 0.346 234 239 713 28 × 2 = 0 + 0.692 468 479 426 56;
  • 24) 0.692 468 479 426 56 × 2 = 1 + 0.384 936 958 853 12;
  • 25) 0.384 936 958 853 12 × 2 = 0 + 0.769 873 917 706 24;
  • 26) 0.769 873 917 706 24 × 2 = 1 + 0.539 747 835 412 48;
  • 27) 0.539 747 835 412 48 × 2 = 1 + 0.079 495 670 824 96;
  • 28) 0.079 495 670 824 96 × 2 = 0 + 0.158 991 341 649 92;
  • 29) 0.158 991 341 649 92 × 2 = 0 + 0.317 982 683 299 84;
  • 30) 0.317 982 683 299 84 × 2 = 0 + 0.635 965 366 599 68;
  • 31) 0.635 965 366 599 68 × 2 = 1 + 0.271 930 733 199 36;
  • 32) 0.271 930 733 199 36 × 2 = 0 + 0.543 861 466 398 72;
  • 33) 0.543 861 466 398 72 × 2 = 1 + 0.087 722 932 797 44;
  • 34) 0.087 722 932 797 44 × 2 = 0 + 0.175 445 865 594 88;
  • 35) 0.175 445 865 594 88 × 2 = 0 + 0.350 891 731 189 76;
  • 36) 0.350 891 731 189 76 × 2 = 0 + 0.701 783 462 379 52;
  • 37) 0.701 783 462 379 52 × 2 = 1 + 0.403 566 924 759 04;
  • 38) 0.403 566 924 759 04 × 2 = 0 + 0.807 133 849 518 08;
  • 39) 0.807 133 849 518 08 × 2 = 1 + 0.614 267 699 036 16;
  • 40) 0.614 267 699 036 16 × 2 = 1 + 0.228 535 398 072 32;
  • 41) 0.228 535 398 072 32 × 2 = 0 + 0.457 070 796 144 64;
  • 42) 0.457 070 796 144 64 × 2 = 0 + 0.914 141 592 289 28;
  • 43) 0.914 141 592 289 28 × 2 = 1 + 0.828 283 184 578 56;
  • 44) 0.828 283 184 578 56 × 2 = 1 + 0.656 566 369 157 12;
  • 45) 0.656 566 369 157 12 × 2 = 1 + 0.313 132 738 314 24;
  • 46) 0.313 132 738 314 24 × 2 = 0 + 0.626 265 476 628 48;
  • 47) 0.626 265 476 628 48 × 2 = 1 + 0.252 530 953 256 96;
  • 48) 0.252 530 953 256 96 × 2 = 0 + 0.505 061 906 513 92;
  • 49) 0.505 061 906 513 92 × 2 = 1 + 0.010 123 813 027 84;
  • 50) 0.010 123 813 027 84 × 2 = 0 + 0.020 247 626 055 68;
  • 51) 0.020 247 626 055 68 × 2 = 0 + 0.040 495 252 111 36;
  • 52) 0.040 495 252 111 36 × 2 = 0 + 0.080 990 504 222 72;
  • 53) 0.080 990 504 222 72 × 2 = 0 + 0.161 981 008 445 44;

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:


0.718 281 828 459 32(10) =


0.1011 0111 1110 0001 0101 0001 0110 0010 1000 1011 0011 1010 1000 0(2)

5. Positive number before normalization:

2.718 281 828 459 32(10) =


10.1011 0111 1110 0001 0101 0001 0110 0010 1000 1011 0011 1010 1000 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the left, so that only one non zero digit remains to the left of it:


2.718 281 828 459 32(10) =


10.1011 0111 1110 0001 0101 0001 0110 0010 1000 1011 0011 1010 1000 0(2) =


10.1011 0111 1110 0001 0101 0001 0110 0010 1000 1011 0011 1010 1000 0(2) × 20 =


1.0101 1011 1111 0000 1010 1000 1011 0001 0100 0101 1001 1101 0100 00(2) × 21


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): 1


Mantissa (not normalized):
1.0101 1011 1111 0000 1010 1000 1011 0001 0100 0101 1001 1101 0100 00


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


1 + 2(11-1) - 1 =


(1 + 1 023)(10) =


1 024(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;
  • 1 024 ÷ 2 = 512 + 0;
  • 512 ÷ 2 = 256 + 0;
  • 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) =


1024(10) =


100 0000 0000(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. 0101 1011 1111 0000 1010 1000 1011 0001 0100 0101 1001 1101 0100 00 =


0101 1011 1111 0000 1010 1000 1011 0001 0100 0101 1001 1101 0100


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 0000


Mantissa (52 bits) =
0101 1011 1111 0000 1010 1000 1011 0001 0100 0101 1001 1101 0100


Decimal number 2.718 281 828 459 32 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0101 1011 1111 0000 1010 1000 1011 0001 0100 0101 1001 1101 0100

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