2.714 285 714 302 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.714 285 714 302(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
2.714 285 714 302(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: 0.714 285 714 302.

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) 0.714 285 714 302 × 2 = 1 + 0.428 571 428 604;
  • 2) 0.428 571 428 604 × 2 = 0 + 0.857 142 857 208;
  • 3) 0.857 142 857 208 × 2 = 1 + 0.714 285 714 416;
  • 4) 0.714 285 714 416 × 2 = 1 + 0.428 571 428 832;
  • 5) 0.428 571 428 832 × 2 = 0 + 0.857 142 857 664;
  • 6) 0.857 142 857 664 × 2 = 1 + 0.714 285 715 328;
  • 7) 0.714 285 715 328 × 2 = 1 + 0.428 571 430 656;
  • 8) 0.428 571 430 656 × 2 = 0 + 0.857 142 861 312;
  • 9) 0.857 142 861 312 × 2 = 1 + 0.714 285 722 624;
  • 10) 0.714 285 722 624 × 2 = 1 + 0.428 571 445 248;
  • 11) 0.428 571 445 248 × 2 = 0 + 0.857 142 890 496;
  • 12) 0.857 142 890 496 × 2 = 1 + 0.714 285 780 992;
  • 13) 0.714 285 780 992 × 2 = 1 + 0.428 571 561 984;
  • 14) 0.428 571 561 984 × 2 = 0 + 0.857 143 123 968;
  • 15) 0.857 143 123 968 × 2 = 1 + 0.714 286 247 936;
  • 16) 0.714 286 247 936 × 2 = 1 + 0.428 572 495 872;
  • 17) 0.428 572 495 872 × 2 = 0 + 0.857 144 991 744;
  • 18) 0.857 144 991 744 × 2 = 1 + 0.714 289 983 488;
  • 19) 0.714 289 983 488 × 2 = 1 + 0.428 579 966 976;
  • 20) 0.428 579 966 976 × 2 = 0 + 0.857 159 933 952;
  • 21) 0.857 159 933 952 × 2 = 1 + 0.714 319 867 904;
  • 22) 0.714 319 867 904 × 2 = 1 + 0.428 639 735 808;
  • 23) 0.428 639 735 808 × 2 = 0 + 0.857 279 471 616;
  • 24) 0.857 279 471 616 × 2 = 1 + 0.714 558 943 232;
  • 25) 0.714 558 943 232 × 2 = 1 + 0.429 117 886 464;
  • 26) 0.429 117 886 464 × 2 = 0 + 0.858 235 772 928;
  • 27) 0.858 235 772 928 × 2 = 1 + 0.716 471 545 856;
  • 28) 0.716 471 545 856 × 2 = 1 + 0.432 943 091 712;
  • 29) 0.432 943 091 712 × 2 = 0 + 0.865 886 183 424;
  • 30) 0.865 886 183 424 × 2 = 1 + 0.731 772 366 848;
  • 31) 0.731 772 366 848 × 2 = 1 + 0.463 544 733 696;
  • 32) 0.463 544 733 696 × 2 = 0 + 0.927 089 467 392;
  • 33) 0.927 089 467 392 × 2 = 1 + 0.854 178 934 784;
  • 34) 0.854 178 934 784 × 2 = 1 + 0.708 357 869 568;
  • 35) 0.708 357 869 568 × 2 = 1 + 0.416 715 739 136;
  • 36) 0.416 715 739 136 × 2 = 0 + 0.833 431 478 272;
  • 37) 0.833 431 478 272 × 2 = 1 + 0.666 862 956 544;
  • 38) 0.666 862 956 544 × 2 = 1 + 0.333 725 913 088;
  • 39) 0.333 725 913 088 × 2 = 0 + 0.667 451 826 176;
  • 40) 0.667 451 826 176 × 2 = 1 + 0.334 903 652 352;
  • 41) 0.334 903 652 352 × 2 = 0 + 0.669 807 304 704;
  • 42) 0.669 807 304 704 × 2 = 1 + 0.339 614 609 408;
  • 43) 0.339 614 609 408 × 2 = 0 + 0.679 229 218 816;
  • 44) 0.679 229 218 816 × 2 = 1 + 0.358 458 437 632;
  • 45) 0.358 458 437 632 × 2 = 0 + 0.716 916 875 264;
  • 46) 0.716 916 875 264 × 2 = 1 + 0.433 833 750 528;
  • 47) 0.433 833 750 528 × 2 = 0 + 0.867 667 501 056;
  • 48) 0.867 667 501 056 × 2 = 1 + 0.735 335 002 112;
  • 49) 0.735 335 002 112 × 2 = 1 + 0.470 670 004 224;
  • 50) 0.470 670 004 224 × 2 = 0 + 0.941 340 008 448;
  • 51) 0.941 340 008 448 × 2 = 1 + 0.882 680 016 896;
  • 52) 0.882 680 016 896 × 2 = 1 + 0.765 360 033 792;
  • 53) 0.765 360 033 792 × 2 = 1 + 0.530 720 067 584;

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:


0.714 285 714 302(10) =


0.1011 0110 1101 1011 0110 1101 1011 0110 1110 1101 0101 0101 1011 1(2)

5. Positive number before normalization:

2.714 285 714 302(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 1101 0101 0101 1011 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:


2.714 285 714 302(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 1101 0101 0101 1011 1(2) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1110 1101 0101 0101 1011 1(2) × 20 =


1.0101 1011 0110 1101 1011 0110 1101 1011 0111 0110 1010 1010 1101 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 0111 0110 1010 1010 1101 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 0111 0110 1010 1010 1101 11 =


0101 1011 0110 1101 1011 0110 1101 1011 0111 0110 1010 1010 1101


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 0110 1010 1010 1101


Decimal number 2.714 285 714 302 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 0110 1010 1010 1101

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