2.718 281 828 460 8 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.718 281 828 460 8(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
2.718 281 828 460 8(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: 0.718 281 828 460 8.

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) 0.718 281 828 460 8 × 2 = 1 + 0.436 563 656 921 6;
  • 2) 0.436 563 656 921 6 × 2 = 0 + 0.873 127 313 843 2;
  • 3) 0.873 127 313 843 2 × 2 = 1 + 0.746 254 627 686 4;
  • 4) 0.746 254 627 686 4 × 2 = 1 + 0.492 509 255 372 8;
  • 5) 0.492 509 255 372 8 × 2 = 0 + 0.985 018 510 745 6;
  • 6) 0.985 018 510 745 6 × 2 = 1 + 0.970 037 021 491 2;
  • 7) 0.970 037 021 491 2 × 2 = 1 + 0.940 074 042 982 4;
  • 8) 0.940 074 042 982 4 × 2 = 1 + 0.880 148 085 964 8;
  • 9) 0.880 148 085 964 8 × 2 = 1 + 0.760 296 171 929 6;
  • 10) 0.760 296 171 929 6 × 2 = 1 + 0.520 592 343 859 2;
  • 11) 0.520 592 343 859 2 × 2 = 1 + 0.041 184 687 718 4;
  • 12) 0.041 184 687 718 4 × 2 = 0 + 0.082 369 375 436 8;
  • 13) 0.082 369 375 436 8 × 2 = 0 + 0.164 738 750 873 6;
  • 14) 0.164 738 750 873 6 × 2 = 0 + 0.329 477 501 747 2;
  • 15) 0.329 477 501 747 2 × 2 = 0 + 0.658 955 003 494 4;
  • 16) 0.658 955 003 494 4 × 2 = 1 + 0.317 910 006 988 8;
  • 17) 0.317 910 006 988 8 × 2 = 0 + 0.635 820 013 977 6;
  • 18) 0.635 820 013 977 6 × 2 = 1 + 0.271 640 027 955 2;
  • 19) 0.271 640 027 955 2 × 2 = 0 + 0.543 280 055 910 4;
  • 20) 0.543 280 055 910 4 × 2 = 1 + 0.086 560 111 820 8;
  • 21) 0.086 560 111 820 8 × 2 = 0 + 0.173 120 223 641 6;
  • 22) 0.173 120 223 641 6 × 2 = 0 + 0.346 240 447 283 2;
  • 23) 0.346 240 447 283 2 × 2 = 0 + 0.692 480 894 566 4;
  • 24) 0.692 480 894 566 4 × 2 = 1 + 0.384 961 789 132 8;
  • 25) 0.384 961 789 132 8 × 2 = 0 + 0.769 923 578 265 6;
  • 26) 0.769 923 578 265 6 × 2 = 1 + 0.539 847 156 531 2;
  • 27) 0.539 847 156 531 2 × 2 = 1 + 0.079 694 313 062 4;
  • 28) 0.079 694 313 062 4 × 2 = 0 + 0.159 388 626 124 8;
  • 29) 0.159 388 626 124 8 × 2 = 0 + 0.318 777 252 249 6;
  • 30) 0.318 777 252 249 6 × 2 = 0 + 0.637 554 504 499 2;
  • 31) 0.637 554 504 499 2 × 2 = 1 + 0.275 109 008 998 4;
  • 32) 0.275 109 008 998 4 × 2 = 0 + 0.550 218 017 996 8;
  • 33) 0.550 218 017 996 8 × 2 = 1 + 0.100 436 035 993 6;
  • 34) 0.100 436 035 993 6 × 2 = 0 + 0.200 872 071 987 2;
  • 35) 0.200 872 071 987 2 × 2 = 0 + 0.401 744 143 974 4;
  • 36) 0.401 744 143 974 4 × 2 = 0 + 0.803 488 287 948 8;
  • 37) 0.803 488 287 948 8 × 2 = 1 + 0.606 976 575 897 6;
  • 38) 0.606 976 575 897 6 × 2 = 1 + 0.213 953 151 795 2;
  • 39) 0.213 953 151 795 2 × 2 = 0 + 0.427 906 303 590 4;
  • 40) 0.427 906 303 590 4 × 2 = 0 + 0.855 812 607 180 8;
  • 41) 0.855 812 607 180 8 × 2 = 1 + 0.711 625 214 361 6;
  • 42) 0.711 625 214 361 6 × 2 = 1 + 0.423 250 428 723 2;
  • 43) 0.423 250 428 723 2 × 2 = 0 + 0.846 500 857 446 4;
  • 44) 0.846 500 857 446 4 × 2 = 1 + 0.693 001 714 892 8;
  • 45) 0.693 001 714 892 8 × 2 = 1 + 0.386 003 429 785 6;
  • 46) 0.386 003 429 785 6 × 2 = 0 + 0.772 006 859 571 2;
  • 47) 0.772 006 859 571 2 × 2 = 1 + 0.544 013 719 142 4;
  • 48) 0.544 013 719 142 4 × 2 = 1 + 0.088 027 438 284 8;
  • 49) 0.088 027 438 284 8 × 2 = 0 + 0.176 054 876 569 6;
  • 50) 0.176 054 876 569 6 × 2 = 0 + 0.352 109 753 139 2;
  • 51) 0.352 109 753 139 2 × 2 = 0 + 0.704 219 506 278 4;
  • 52) 0.704 219 506 278 4 × 2 = 1 + 0.408 439 012 556 8;
  • 53) 0.408 439 012 556 8 × 2 = 0 + 0.816 878 025 113 6;

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:


0.718 281 828 460 8(10) =

0.1011 0111 1110 0001 0101 0001 0110 0010 1000 1100 1101 1011 0001 0(2)

5. Positive number before normalization:

2.718 281 828 460 8(10) =

10.1011 0111 1110 0001 0101 0001 0110 0010 1000 1100 1101 1011 0001 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:


2.718 281 828 460 8(10) =

10.1011 0111 1110 0001 0101 0001 0110 0010 1000 1100 1101 1011 0001 0(2) =

10.1011 0111 1110 0001 0101 0001 0110 0010 1000 1100 1101 1011 0001 0(2) × 20 =

1.0101 1011 1111 0000 1010 1000 1011 0001 0100 0110 0110 1101 1000 10(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 0110 0110 1101 1000 10


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 0110 0110 1101 1000 10 =

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


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 0110 0110 1101 1000


Decimal number 2.718 281 828 460 8 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 0110 0110 1101 1000

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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