2.714 285 714 292 09 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.714 285 714 292 09(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
2.714 285 714 292 09(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: 0.714 285 714 292 09.

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) 0.714 285 714 292 09 × 2 = 1 + 0.428 571 428 584 18;
  • 2) 0.428 571 428 584 18 × 2 = 0 + 0.857 142 857 168 36;
  • 3) 0.857 142 857 168 36 × 2 = 1 + 0.714 285 714 336 72;
  • 4) 0.714 285 714 336 72 × 2 = 1 + 0.428 571 428 673 44;
  • 5) 0.428 571 428 673 44 × 2 = 0 + 0.857 142 857 346 88;
  • 6) 0.857 142 857 346 88 × 2 = 1 + 0.714 285 714 693 76;
  • 7) 0.714 285 714 693 76 × 2 = 1 + 0.428 571 429 387 52;
  • 8) 0.428 571 429 387 52 × 2 = 0 + 0.857 142 858 775 04;
  • 9) 0.857 142 858 775 04 × 2 = 1 + 0.714 285 717 550 08;
  • 10) 0.714 285 717 550 08 × 2 = 1 + 0.428 571 435 100 16;
  • 11) 0.428 571 435 100 16 × 2 = 0 + 0.857 142 870 200 32;
  • 12) 0.857 142 870 200 32 × 2 = 1 + 0.714 285 740 400 64;
  • 13) 0.714 285 740 400 64 × 2 = 1 + 0.428 571 480 801 28;
  • 14) 0.428 571 480 801 28 × 2 = 0 + 0.857 142 961 602 56;
  • 15) 0.857 142 961 602 56 × 2 = 1 + 0.714 285 923 205 12;
  • 16) 0.714 285 923 205 12 × 2 = 1 + 0.428 571 846 410 24;
  • 17) 0.428 571 846 410 24 × 2 = 0 + 0.857 143 692 820 48;
  • 18) 0.857 143 692 820 48 × 2 = 1 + 0.714 287 385 640 96;
  • 19) 0.714 287 385 640 96 × 2 = 1 + 0.428 574 771 281 92;
  • 20) 0.428 574 771 281 92 × 2 = 0 + 0.857 149 542 563 84;
  • 21) 0.857 149 542 563 84 × 2 = 1 + 0.714 299 085 127 68;
  • 22) 0.714 299 085 127 68 × 2 = 1 + 0.428 598 170 255 36;
  • 23) 0.428 598 170 255 36 × 2 = 0 + 0.857 196 340 510 72;
  • 24) 0.857 196 340 510 72 × 2 = 1 + 0.714 392 681 021 44;
  • 25) 0.714 392 681 021 44 × 2 = 1 + 0.428 785 362 042 88;
  • 26) 0.428 785 362 042 88 × 2 = 0 + 0.857 570 724 085 76;
  • 27) 0.857 570 724 085 76 × 2 = 1 + 0.715 141 448 171 52;
  • 28) 0.715 141 448 171 52 × 2 = 1 + 0.430 282 896 343 04;
  • 29) 0.430 282 896 343 04 × 2 = 0 + 0.860 565 792 686 08;
  • 30) 0.860 565 792 686 08 × 2 = 1 + 0.721 131 585 372 16;
  • 31) 0.721 131 585 372 16 × 2 = 1 + 0.442 263 170 744 32;
  • 32) 0.442 263 170 744 32 × 2 = 0 + 0.884 526 341 488 64;
  • 33) 0.884 526 341 488 64 × 2 = 1 + 0.769 052 682 977 28;
  • 34) 0.769 052 682 977 28 × 2 = 1 + 0.538 105 365 954 56;
  • 35) 0.538 105 365 954 56 × 2 = 1 + 0.076 210 731 909 12;
  • 36) 0.076 210 731 909 12 × 2 = 0 + 0.152 421 463 818 24;
  • 37) 0.152 421 463 818 24 × 2 = 0 + 0.304 842 927 636 48;
  • 38) 0.304 842 927 636 48 × 2 = 0 + 0.609 685 855 272 96;
  • 39) 0.609 685 855 272 96 × 2 = 1 + 0.219 371 710 545 92;
  • 40) 0.219 371 710 545 92 × 2 = 0 + 0.438 743 421 091 84;
  • 41) 0.438 743 421 091 84 × 2 = 0 + 0.877 486 842 183 68;
  • 42) 0.877 486 842 183 68 × 2 = 1 + 0.754 973 684 367 36;
  • 43) 0.754 973 684 367 36 × 2 = 1 + 0.509 947 368 734 72;
  • 44) 0.509 947 368 734 72 × 2 = 1 + 0.019 894 737 469 44;
  • 45) 0.019 894 737 469 44 × 2 = 0 + 0.039 789 474 938 88;
  • 46) 0.039 789 474 938 88 × 2 = 0 + 0.079 578 949 877 76;
  • 47) 0.079 578 949 877 76 × 2 = 0 + 0.159 157 899 755 52;
  • 48) 0.159 157 899 755 52 × 2 = 0 + 0.318 315 799 511 04;
  • 49) 0.318 315 799 511 04 × 2 = 0 + 0.636 631 599 022 08;
  • 50) 0.636 631 599 022 08 × 2 = 1 + 0.273 263 198 044 16;
  • 51) 0.273 263 198 044 16 × 2 = 0 + 0.546 526 396 088 32;
  • 52) 0.546 526 396 088 32 × 2 = 1 + 0.093 052 792 176 64;
  • 53) 0.093 052 792 176 64 × 2 = 0 + 0.186 105 584 353 28;

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:


0.714 285 714 292 09(10) =


0.1011 0110 1101 1011 0110 1101 1011 0110 1110 0010 0111 0000 0101 0(2)

5. Positive number before normalization:

2.714 285 714 292 09(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0010 0111 0000 0101 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:


2.714 285 714 292 09(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0010 0111 0000 0101 0(2) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 0010 0111 0000 0101 0(2) × 20 =


1.0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 0011 1000 0010 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 0011 1000 0010 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 0011 1000 0010 10 =


0101 1011 0110 1101 1011 0110 1101 1011 0111 0001 0011 1000 0010


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 0011 1000 0010


Decimal number 2.714 285 714 292 09 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 0011 1000 0010

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