2.718 281 828 458 98 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.718 281 828 458 98(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
2.718 281 828 458 98(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: 0.718 281 828 458 98.

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) 0.718 281 828 458 98 × 2 = 1 + 0.436 563 656 917 96;
  • 2) 0.436 563 656 917 96 × 2 = 0 + 0.873 127 313 835 92;
  • 3) 0.873 127 313 835 92 × 2 = 1 + 0.746 254 627 671 84;
  • 4) 0.746 254 627 671 84 × 2 = 1 + 0.492 509 255 343 68;
  • 5) 0.492 509 255 343 68 × 2 = 0 + 0.985 018 510 687 36;
  • 6) 0.985 018 510 687 36 × 2 = 1 + 0.970 037 021 374 72;
  • 7) 0.970 037 021 374 72 × 2 = 1 + 0.940 074 042 749 44;
  • 8) 0.940 074 042 749 44 × 2 = 1 + 0.880 148 085 498 88;
  • 9) 0.880 148 085 498 88 × 2 = 1 + 0.760 296 170 997 76;
  • 10) 0.760 296 170 997 76 × 2 = 1 + 0.520 592 341 995 52;
  • 11) 0.520 592 341 995 52 × 2 = 1 + 0.041 184 683 991 04;
  • 12) 0.041 184 683 991 04 × 2 = 0 + 0.082 369 367 982 08;
  • 13) 0.082 369 367 982 08 × 2 = 0 + 0.164 738 735 964 16;
  • 14) 0.164 738 735 964 16 × 2 = 0 + 0.329 477 471 928 32;
  • 15) 0.329 477 471 928 32 × 2 = 0 + 0.658 954 943 856 64;
  • 16) 0.658 954 943 856 64 × 2 = 1 + 0.317 909 887 713 28;
  • 17) 0.317 909 887 713 28 × 2 = 0 + 0.635 819 775 426 56;
  • 18) 0.635 819 775 426 56 × 2 = 1 + 0.271 639 550 853 12;
  • 19) 0.271 639 550 853 12 × 2 = 0 + 0.543 279 101 706 24;
  • 20) 0.543 279 101 706 24 × 2 = 1 + 0.086 558 203 412 48;
  • 21) 0.086 558 203 412 48 × 2 = 0 + 0.173 116 406 824 96;
  • 22) 0.173 116 406 824 96 × 2 = 0 + 0.346 232 813 649 92;
  • 23) 0.346 232 813 649 92 × 2 = 0 + 0.692 465 627 299 84;
  • 24) 0.692 465 627 299 84 × 2 = 1 + 0.384 931 254 599 68;
  • 25) 0.384 931 254 599 68 × 2 = 0 + 0.769 862 509 199 36;
  • 26) 0.769 862 509 199 36 × 2 = 1 + 0.539 725 018 398 72;
  • 27) 0.539 725 018 398 72 × 2 = 1 + 0.079 450 036 797 44;
  • 28) 0.079 450 036 797 44 × 2 = 0 + 0.158 900 073 594 88;
  • 29) 0.158 900 073 594 88 × 2 = 0 + 0.317 800 147 189 76;
  • 30) 0.317 800 147 189 76 × 2 = 0 + 0.635 600 294 379 52;
  • 31) 0.635 600 294 379 52 × 2 = 1 + 0.271 200 588 759 04;
  • 32) 0.271 200 588 759 04 × 2 = 0 + 0.542 401 177 518 08;
  • 33) 0.542 401 177 518 08 × 2 = 1 + 0.084 802 355 036 16;
  • 34) 0.084 802 355 036 16 × 2 = 0 + 0.169 604 710 072 32;
  • 35) 0.169 604 710 072 32 × 2 = 0 + 0.339 209 420 144 64;
  • 36) 0.339 209 420 144 64 × 2 = 0 + 0.678 418 840 289 28;
  • 37) 0.678 418 840 289 28 × 2 = 1 + 0.356 837 680 578 56;
  • 38) 0.356 837 680 578 56 × 2 = 0 + 0.713 675 361 157 12;
  • 39) 0.713 675 361 157 12 × 2 = 1 + 0.427 350 722 314 24;
  • 40) 0.427 350 722 314 24 × 2 = 0 + 0.854 701 444 628 48;
  • 41) 0.854 701 444 628 48 × 2 = 1 + 0.709 402 889 256 96;
  • 42) 0.709 402 889 256 96 × 2 = 1 + 0.418 805 778 513 92;
  • 43) 0.418 805 778 513 92 × 2 = 0 + 0.837 611 557 027 84;
  • 44) 0.837 611 557 027 84 × 2 = 1 + 0.675 223 114 055 68;
  • 45) 0.675 223 114 055 68 × 2 = 1 + 0.350 446 228 111 36;
  • 46) 0.350 446 228 111 36 × 2 = 0 + 0.700 892 456 222 72;
  • 47) 0.700 892 456 222 72 × 2 = 1 + 0.401 784 912 445 44;
  • 48) 0.401 784 912 445 44 × 2 = 0 + 0.803 569 824 890 88;
  • 49) 0.803 569 824 890 88 × 2 = 1 + 0.607 139 649 781 76;
  • 50) 0.607 139 649 781 76 × 2 = 1 + 0.214 279 299 563 52;
  • 51) 0.214 279 299 563 52 × 2 = 0 + 0.428 558 599 127 04;
  • 52) 0.428 558 599 127 04 × 2 = 0 + 0.857 117 198 254 08;
  • 53) 0.857 117 198 254 08 × 2 = 1 + 0.714 234 396 508 16;

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:


0.718 281 828 458 98(10) =


0.1011 0111 1110 0001 0101 0001 0110 0010 1000 1010 1101 1010 1100 1(2)

5. Positive number before normalization:

2.718 281 828 458 98(10) =


10.1011 0111 1110 0001 0101 0001 0110 0010 1000 1010 1101 1010 1100 1(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:


2.718 281 828 458 98(10) =


10.1011 0111 1110 0001 0101 0001 0110 0010 1000 1010 1101 1010 1100 1(2) =


10.1011 0111 1110 0001 0101 0001 0110 0010 1000 1010 1101 1010 1100 1(2) × 20 =


1.0101 1011 1111 0000 1010 1000 1011 0001 0100 0101 0110 1101 0110 01(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 0110 1101 0110 01


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 0110 1101 0110 01 =


0101 1011 1111 0000 1010 1000 1011 0001 0100 0101 0110 1101 0110


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 0110 1101 0110


Decimal number 2.718 281 828 458 98 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 0110 1101 0110

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