2.714 285 714 293 48 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.714 285 714 293 48(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
2.714 285 714 293 48(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: 0.714 285 714 293 48.

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) 0.714 285 714 293 48 × 2 = 1 + 0.428 571 428 586 96;
  • 2) 0.428 571 428 586 96 × 2 = 0 + 0.857 142 857 173 92;
  • 3) 0.857 142 857 173 92 × 2 = 1 + 0.714 285 714 347 84;
  • 4) 0.714 285 714 347 84 × 2 = 1 + 0.428 571 428 695 68;
  • 5) 0.428 571 428 695 68 × 2 = 0 + 0.857 142 857 391 36;
  • 6) 0.857 142 857 391 36 × 2 = 1 + 0.714 285 714 782 72;
  • 7) 0.714 285 714 782 72 × 2 = 1 + 0.428 571 429 565 44;
  • 8) 0.428 571 429 565 44 × 2 = 0 + 0.857 142 859 130 88;
  • 9) 0.857 142 859 130 88 × 2 = 1 + 0.714 285 718 261 76;
  • 10) 0.714 285 718 261 76 × 2 = 1 + 0.428 571 436 523 52;
  • 11) 0.428 571 436 523 52 × 2 = 0 + 0.857 142 873 047 04;
  • 12) 0.857 142 873 047 04 × 2 = 1 + 0.714 285 746 094 08;
  • 13) 0.714 285 746 094 08 × 2 = 1 + 0.428 571 492 188 16;
  • 14) 0.428 571 492 188 16 × 2 = 0 + 0.857 142 984 376 32;
  • 15) 0.857 142 984 376 32 × 2 = 1 + 0.714 285 968 752 64;
  • 16) 0.714 285 968 752 64 × 2 = 1 + 0.428 571 937 505 28;
  • 17) 0.428 571 937 505 28 × 2 = 0 + 0.857 143 875 010 56;
  • 18) 0.857 143 875 010 56 × 2 = 1 + 0.714 287 750 021 12;
  • 19) 0.714 287 750 021 12 × 2 = 1 + 0.428 575 500 042 24;
  • 20) 0.428 575 500 042 24 × 2 = 0 + 0.857 151 000 084 48;
  • 21) 0.857 151 000 084 48 × 2 = 1 + 0.714 302 000 168 96;
  • 22) 0.714 302 000 168 96 × 2 = 1 + 0.428 604 000 337 92;
  • 23) 0.428 604 000 337 92 × 2 = 0 + 0.857 208 000 675 84;
  • 24) 0.857 208 000 675 84 × 2 = 1 + 0.714 416 001 351 68;
  • 25) 0.714 416 001 351 68 × 2 = 1 + 0.428 832 002 703 36;
  • 26) 0.428 832 002 703 36 × 2 = 0 + 0.857 664 005 406 72;
  • 27) 0.857 664 005 406 72 × 2 = 1 + 0.715 328 010 813 44;
  • 28) 0.715 328 010 813 44 × 2 = 1 + 0.430 656 021 626 88;
  • 29) 0.430 656 021 626 88 × 2 = 0 + 0.861 312 043 253 76;
  • 30) 0.861 312 043 253 76 × 2 = 1 + 0.722 624 086 507 52;
  • 31) 0.722 624 086 507 52 × 2 = 1 + 0.445 248 173 015 04;
  • 32) 0.445 248 173 015 04 × 2 = 0 + 0.890 496 346 030 08;
  • 33) 0.890 496 346 030 08 × 2 = 1 + 0.780 992 692 060 16;
  • 34) 0.780 992 692 060 16 × 2 = 1 + 0.561 985 384 120 32;
  • 35) 0.561 985 384 120 32 × 2 = 1 + 0.123 970 768 240 64;
  • 36) 0.123 970 768 240 64 × 2 = 0 + 0.247 941 536 481 28;
  • 37) 0.247 941 536 481 28 × 2 = 0 + 0.495 883 072 962 56;
  • 38) 0.495 883 072 962 56 × 2 = 0 + 0.991 766 145 925 12;
  • 39) 0.991 766 145 925 12 × 2 = 1 + 0.983 532 291 850 24;
  • 40) 0.983 532 291 850 24 × 2 = 1 + 0.967 064 583 700 48;
  • 41) 0.967 064 583 700 48 × 2 = 1 + 0.934 129 167 400 96;
  • 42) 0.934 129 167 400 96 × 2 = 1 + 0.868 258 334 801 92;
  • 43) 0.868 258 334 801 92 × 2 = 1 + 0.736 516 669 603 84;
  • 44) 0.736 516 669 603 84 × 2 = 1 + 0.473 033 339 207 68;
  • 45) 0.473 033 339 207 68 × 2 = 0 + 0.946 066 678 415 36;
  • 46) 0.946 066 678 415 36 × 2 = 1 + 0.892 133 356 830 72;
  • 47) 0.892 133 356 830 72 × 2 = 1 + 0.784 266 713 661 44;
  • 48) 0.784 266 713 661 44 × 2 = 1 + 0.568 533 427 322 88;
  • 49) 0.568 533 427 322 88 × 2 = 1 + 0.137 066 854 645 76;
  • 50) 0.137 066 854 645 76 × 2 = 0 + 0.274 133 709 291 52;
  • 51) 0.274 133 709 291 52 × 2 = 0 + 0.548 267 418 583 04;
  • 52) 0.548 267 418 583 04 × 2 = 1 + 0.096 534 837 166 08;
  • 53) 0.096 534 837 166 08 × 2 = 0 + 0.193 069 674 332 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:


0.714 285 714 293 48(10) =


0.1011 0110 1101 1011 0110 1101 1011 0110 1110 0011 1111 0111 1001 0(2)

5. Positive number before normalization:

2.714 285 714 293 48(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0011 1111 0111 1001 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:


2.714 285 714 293 48(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0011 1111 0111 1001 0(2) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0011 1111 0111 1001 0(2) × 20 =


1.0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 1111 1011 1100 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 0110 1101 1011 0110 1101 1011 0111 0001 1111 1011 1100 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 0110 1101 1011 0110 1101 1011 0111 0001 1111 1011 1100 10 =


0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 1111 1011 1100


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 0110 1101 1011 0110 1101 1011 0111 0001 1111 1011 1100


Decimal number 2.714 285 714 293 48 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 1111 1011 1100

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