2.714 285 714 285 713 88 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.714 285 714 285 713 88(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
2.714 285 714 285 713 88(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: 0.714 285 714 285 713 88.

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) 0.714 285 714 285 713 88 × 2 = 1 + 0.428 571 428 571 427 76;
  • 2) 0.428 571 428 571 427 76 × 2 = 0 + 0.857 142 857 142 855 52;
  • 3) 0.857 142 857 142 855 52 × 2 = 1 + 0.714 285 714 285 711 04;
  • 4) 0.714 285 714 285 711 04 × 2 = 1 + 0.428 571 428 571 422 08;
  • 5) 0.428 571 428 571 422 08 × 2 = 0 + 0.857 142 857 142 844 16;
  • 6) 0.857 142 857 142 844 16 × 2 = 1 + 0.714 285 714 285 688 32;
  • 7) 0.714 285 714 285 688 32 × 2 = 1 + 0.428 571 428 571 376 64;
  • 8) 0.428 571 428 571 376 64 × 2 = 0 + 0.857 142 857 142 753 28;
  • 9) 0.857 142 857 142 753 28 × 2 = 1 + 0.714 285 714 285 506 56;
  • 10) 0.714 285 714 285 506 56 × 2 = 1 + 0.428 571 428 571 013 12;
  • 11) 0.428 571 428 571 013 12 × 2 = 0 + 0.857 142 857 142 026 24;
  • 12) 0.857 142 857 142 026 24 × 2 = 1 + 0.714 285 714 284 052 48;
  • 13) 0.714 285 714 284 052 48 × 2 = 1 + 0.428 571 428 568 104 96;
  • 14) 0.428 571 428 568 104 96 × 2 = 0 + 0.857 142 857 136 209 92;
  • 15) 0.857 142 857 136 209 92 × 2 = 1 + 0.714 285 714 272 419 84;
  • 16) 0.714 285 714 272 419 84 × 2 = 1 + 0.428 571 428 544 839 68;
  • 17) 0.428 571 428 544 839 68 × 2 = 0 + 0.857 142 857 089 679 36;
  • 18) 0.857 142 857 089 679 36 × 2 = 1 + 0.714 285 714 179 358 72;
  • 19) 0.714 285 714 179 358 72 × 2 = 1 + 0.428 571 428 358 717 44;
  • 20) 0.428 571 428 358 717 44 × 2 = 0 + 0.857 142 856 717 434 88;
  • 21) 0.857 142 856 717 434 88 × 2 = 1 + 0.714 285 713 434 869 76;
  • 22) 0.714 285 713 434 869 76 × 2 = 1 + 0.428 571 426 869 739 52;
  • 23) 0.428 571 426 869 739 52 × 2 = 0 + 0.857 142 853 739 479 04;
  • 24) 0.857 142 853 739 479 04 × 2 = 1 + 0.714 285 707 478 958 08;
  • 25) 0.714 285 707 478 958 08 × 2 = 1 + 0.428 571 414 957 916 16;
  • 26) 0.428 571 414 957 916 16 × 2 = 0 + 0.857 142 829 915 832 32;
  • 27) 0.857 142 829 915 832 32 × 2 = 1 + 0.714 285 659 831 664 64;
  • 28) 0.714 285 659 831 664 64 × 2 = 1 + 0.428 571 319 663 329 28;
  • 29) 0.428 571 319 663 329 28 × 2 = 0 + 0.857 142 639 326 658 56;
  • 30) 0.857 142 639 326 658 56 × 2 = 1 + 0.714 285 278 653 317 12;
  • 31) 0.714 285 278 653 317 12 × 2 = 1 + 0.428 570 557 306 634 24;
  • 32) 0.428 570 557 306 634 24 × 2 = 0 + 0.857 141 114 613 268 48;
  • 33) 0.857 141 114 613 268 48 × 2 = 1 + 0.714 282 229 226 536 96;
  • 34) 0.714 282 229 226 536 96 × 2 = 1 + 0.428 564 458 453 073 92;
  • 35) 0.428 564 458 453 073 92 × 2 = 0 + 0.857 128 916 906 147 84;
  • 36) 0.857 128 916 906 147 84 × 2 = 1 + 0.714 257 833 812 295 68;
  • 37) 0.714 257 833 812 295 68 × 2 = 1 + 0.428 515 667 624 591 36;
  • 38) 0.428 515 667 624 591 36 × 2 = 0 + 0.857 031 335 249 182 72;
  • 39) 0.857 031 335 249 182 72 × 2 = 1 + 0.714 062 670 498 365 44;
  • 40) 0.714 062 670 498 365 44 × 2 = 1 + 0.428 125 340 996 730 88;
  • 41) 0.428 125 340 996 730 88 × 2 = 0 + 0.856 250 681 993 461 76;
  • 42) 0.856 250 681 993 461 76 × 2 = 1 + 0.712 501 363 986 923 52;
  • 43) 0.712 501 363 986 923 52 × 2 = 1 + 0.425 002 727 973 847 04;
  • 44) 0.425 002 727 973 847 04 × 2 = 0 + 0.850 005 455 947 694 08;
  • 45) 0.850 005 455 947 694 08 × 2 = 1 + 0.700 010 911 895 388 16;
  • 46) 0.700 010 911 895 388 16 × 2 = 1 + 0.400 021 823 790 776 32;
  • 47) 0.400 021 823 790 776 32 × 2 = 0 + 0.800 043 647 581 552 64;
  • 48) 0.800 043 647 581 552 64 × 2 = 1 + 0.600 087 295 163 105 28;
  • 49) 0.600 087 295 163 105 28 × 2 = 1 + 0.200 174 590 326 210 56;
  • 50) 0.200 174 590 326 210 56 × 2 = 0 + 0.400 349 180 652 421 12;
  • 51) 0.400 349 180 652 421 12 × 2 = 0 + 0.800 698 361 304 842 24;
  • 52) 0.800 698 361 304 842 24 × 2 = 1 + 0.601 396 722 609 684 48;
  • 53) 0.601 396 722 609 684 48 × 2 = 1 + 0.202 793 445 219 368 96;

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:


0.714 285 714 285 713 88(10) =


0.1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 1101 1001 1(2)

5. Positive number before normalization:

2.714 285 714 285 713 88(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 1101 1001 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:


2.714 285 714 285 713 88(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 1101 1001 1(2) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 1101 1001 1(2) × 20 =


1.0101 1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 1100 11(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 0110 1101 1011 0110 1100 11


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 0110 1101 1011 0110 1100 11 =


0101 1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 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 0110 1101 1011 0110 1100


Decimal number 2.714 285 714 285 713 88 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0101 1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 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