2.714 285 714 285 712 96 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.714 285 714 285 712 96(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
2.714 285 714 285 712 96(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: 0.714 285 714 285 712 96.

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) 0.714 285 714 285 712 96 × 2 = 1 + 0.428 571 428 571 425 92;
  • 2) 0.428 571 428 571 425 92 × 2 = 0 + 0.857 142 857 142 851 84;
  • 3) 0.857 142 857 142 851 84 × 2 = 1 + 0.714 285 714 285 703 68;
  • 4) 0.714 285 714 285 703 68 × 2 = 1 + 0.428 571 428 571 407 36;
  • 5) 0.428 571 428 571 407 36 × 2 = 0 + 0.857 142 857 142 814 72;
  • 6) 0.857 142 857 142 814 72 × 2 = 1 + 0.714 285 714 285 629 44;
  • 7) 0.714 285 714 285 629 44 × 2 = 1 + 0.428 571 428 571 258 88;
  • 8) 0.428 571 428 571 258 88 × 2 = 0 + 0.857 142 857 142 517 76;
  • 9) 0.857 142 857 142 517 76 × 2 = 1 + 0.714 285 714 285 035 52;
  • 10) 0.714 285 714 285 035 52 × 2 = 1 + 0.428 571 428 570 071 04;
  • 11) 0.428 571 428 570 071 04 × 2 = 0 + 0.857 142 857 140 142 08;
  • 12) 0.857 142 857 140 142 08 × 2 = 1 + 0.714 285 714 280 284 16;
  • 13) 0.714 285 714 280 284 16 × 2 = 1 + 0.428 571 428 560 568 32;
  • 14) 0.428 571 428 560 568 32 × 2 = 0 + 0.857 142 857 121 136 64;
  • 15) 0.857 142 857 121 136 64 × 2 = 1 + 0.714 285 714 242 273 28;
  • 16) 0.714 285 714 242 273 28 × 2 = 1 + 0.428 571 428 484 546 56;
  • 17) 0.428 571 428 484 546 56 × 2 = 0 + 0.857 142 856 969 093 12;
  • 18) 0.857 142 856 969 093 12 × 2 = 1 + 0.714 285 713 938 186 24;
  • 19) 0.714 285 713 938 186 24 × 2 = 1 + 0.428 571 427 876 372 48;
  • 20) 0.428 571 427 876 372 48 × 2 = 0 + 0.857 142 855 752 744 96;
  • 21) 0.857 142 855 752 744 96 × 2 = 1 + 0.714 285 711 505 489 92;
  • 22) 0.714 285 711 505 489 92 × 2 = 1 + 0.428 571 423 010 979 84;
  • 23) 0.428 571 423 010 979 84 × 2 = 0 + 0.857 142 846 021 959 68;
  • 24) 0.857 142 846 021 959 68 × 2 = 1 + 0.714 285 692 043 919 36;
  • 25) 0.714 285 692 043 919 36 × 2 = 1 + 0.428 571 384 087 838 72;
  • 26) 0.428 571 384 087 838 72 × 2 = 0 + 0.857 142 768 175 677 44;
  • 27) 0.857 142 768 175 677 44 × 2 = 1 + 0.714 285 536 351 354 88;
  • 28) 0.714 285 536 351 354 88 × 2 = 1 + 0.428 571 072 702 709 76;
  • 29) 0.428 571 072 702 709 76 × 2 = 0 + 0.857 142 145 405 419 52;
  • 30) 0.857 142 145 405 419 52 × 2 = 1 + 0.714 284 290 810 839 04;
  • 31) 0.714 284 290 810 839 04 × 2 = 1 + 0.428 568 581 621 678 08;
  • 32) 0.428 568 581 621 678 08 × 2 = 0 + 0.857 137 163 243 356 16;
  • 33) 0.857 137 163 243 356 16 × 2 = 1 + 0.714 274 326 486 712 32;
  • 34) 0.714 274 326 486 712 32 × 2 = 1 + 0.428 548 652 973 424 64;
  • 35) 0.428 548 652 973 424 64 × 2 = 0 + 0.857 097 305 946 849 28;
  • 36) 0.857 097 305 946 849 28 × 2 = 1 + 0.714 194 611 893 698 56;
  • 37) 0.714 194 611 893 698 56 × 2 = 1 + 0.428 389 223 787 397 12;
  • 38) 0.428 389 223 787 397 12 × 2 = 0 + 0.856 778 447 574 794 24;
  • 39) 0.856 778 447 574 794 24 × 2 = 1 + 0.713 556 895 149 588 48;
  • 40) 0.713 556 895 149 588 48 × 2 = 1 + 0.427 113 790 299 176 96;
  • 41) 0.427 113 790 299 176 96 × 2 = 0 + 0.854 227 580 598 353 92;
  • 42) 0.854 227 580 598 353 92 × 2 = 1 + 0.708 455 161 196 707 84;
  • 43) 0.708 455 161 196 707 84 × 2 = 1 + 0.416 910 322 393 415 68;
  • 44) 0.416 910 322 393 415 68 × 2 = 0 + 0.833 820 644 786 831 36;
  • 45) 0.833 820 644 786 831 36 × 2 = 1 + 0.667 641 289 573 662 72;
  • 46) 0.667 641 289 573 662 72 × 2 = 1 + 0.335 282 579 147 325 44;
  • 47) 0.335 282 579 147 325 44 × 2 = 0 + 0.670 565 158 294 650 88;
  • 48) 0.670 565 158 294 650 88 × 2 = 1 + 0.341 130 316 589 301 76;
  • 49) 0.341 130 316 589 301 76 × 2 = 0 + 0.682 260 633 178 603 52;
  • 50) 0.682 260 633 178 603 52 × 2 = 1 + 0.364 521 266 357 207 04;
  • 51) 0.364 521 266 357 207 04 × 2 = 0 + 0.729 042 532 714 414 08;
  • 52) 0.729 042 532 714 414 08 × 2 = 1 + 0.458 085 065 428 828 16;
  • 53) 0.458 085 065 428 828 16 × 2 = 0 + 0.916 170 130 857 656 32;

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:


0.714 285 714 285 712 96(10) =


0.1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 1101 0101 0(2)

5. Positive number before normalization:

2.714 285 714 285 712 96(10) =


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


2.714 285 714 285 712 96(10) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 1101 0101 0(2) =


10.1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 1101 0101 0(2) × 20 =


1.0101 1011 0110 1101 1011 0110 1101 1011 0110 1101 1011 0110 1010 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 0110 1101 1011 0110 1010 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 0110 1101 1011 0110 1010 10 =


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


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 1010


Decimal number 2.714 285 714 285 712 96 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 1010


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