3.123 145 321 678 998 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 3.123 145 321 678 998 6(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
3.123 145 321 678 998 6(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: 3.
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;
  • 3 ÷ 2 = 1 + 1;
  • 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.

3(10) =


11(2)


3. Convert to binary (base 2) the fractional part: 0.123 145 321 678 998 6.

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) 0.123 145 321 678 998 6 × 2 = 0 + 0.246 290 643 357 997 2;
  • 2) 0.246 290 643 357 997 2 × 2 = 0 + 0.492 581 286 715 994 4;
  • 3) 0.492 581 286 715 994 4 × 2 = 0 + 0.985 162 573 431 988 8;
  • 4) 0.985 162 573 431 988 8 × 2 = 1 + 0.970 325 146 863 977 6;
  • 5) 0.970 325 146 863 977 6 × 2 = 1 + 0.940 650 293 727 955 2;
  • 6) 0.940 650 293 727 955 2 × 2 = 1 + 0.881 300 587 455 910 4;
  • 7) 0.881 300 587 455 910 4 × 2 = 1 + 0.762 601 174 911 820 8;
  • 8) 0.762 601 174 911 820 8 × 2 = 1 + 0.525 202 349 823 641 6;
  • 9) 0.525 202 349 823 641 6 × 2 = 1 + 0.050 404 699 647 283 2;
  • 10) 0.050 404 699 647 283 2 × 2 = 0 + 0.100 809 399 294 566 4;
  • 11) 0.100 809 399 294 566 4 × 2 = 0 + 0.201 618 798 589 132 8;
  • 12) 0.201 618 798 589 132 8 × 2 = 0 + 0.403 237 597 178 265 6;
  • 13) 0.403 237 597 178 265 6 × 2 = 0 + 0.806 475 194 356 531 2;
  • 14) 0.806 475 194 356 531 2 × 2 = 1 + 0.612 950 388 713 062 4;
  • 15) 0.612 950 388 713 062 4 × 2 = 1 + 0.225 900 777 426 124 8;
  • 16) 0.225 900 777 426 124 8 × 2 = 0 + 0.451 801 554 852 249 6;
  • 17) 0.451 801 554 852 249 6 × 2 = 0 + 0.903 603 109 704 499 2;
  • 18) 0.903 603 109 704 499 2 × 2 = 1 + 0.807 206 219 408 998 4;
  • 19) 0.807 206 219 408 998 4 × 2 = 1 + 0.614 412 438 817 996 8;
  • 20) 0.614 412 438 817 996 8 × 2 = 1 + 0.228 824 877 635 993 6;
  • 21) 0.228 824 877 635 993 6 × 2 = 0 + 0.457 649 755 271 987 2;
  • 22) 0.457 649 755 271 987 2 × 2 = 0 + 0.915 299 510 543 974 4;
  • 23) 0.915 299 510 543 974 4 × 2 = 1 + 0.830 599 021 087 948 8;
  • 24) 0.830 599 021 087 948 8 × 2 = 1 + 0.661 198 042 175 897 6;
  • 25) 0.661 198 042 175 897 6 × 2 = 1 + 0.322 396 084 351 795 2;
  • 26) 0.322 396 084 351 795 2 × 2 = 0 + 0.644 792 168 703 590 4;
  • 27) 0.644 792 168 703 590 4 × 2 = 1 + 0.289 584 337 407 180 8;
  • 28) 0.289 584 337 407 180 8 × 2 = 0 + 0.579 168 674 814 361 6;
  • 29) 0.579 168 674 814 361 6 × 2 = 1 + 0.158 337 349 628 723 2;
  • 30) 0.158 337 349 628 723 2 × 2 = 0 + 0.316 674 699 257 446 4;
  • 31) 0.316 674 699 257 446 4 × 2 = 0 + 0.633 349 398 514 892 8;
  • 32) 0.633 349 398 514 892 8 × 2 = 1 + 0.266 698 797 029 785 6;
  • 33) 0.266 698 797 029 785 6 × 2 = 0 + 0.533 397 594 059 571 2;
  • 34) 0.533 397 594 059 571 2 × 2 = 1 + 0.066 795 188 119 142 4;
  • 35) 0.066 795 188 119 142 4 × 2 = 0 + 0.133 590 376 238 284 8;
  • 36) 0.133 590 376 238 284 8 × 2 = 0 + 0.267 180 752 476 569 6;
  • 37) 0.267 180 752 476 569 6 × 2 = 0 + 0.534 361 504 953 139 2;
  • 38) 0.534 361 504 953 139 2 × 2 = 1 + 0.068 723 009 906 278 4;
  • 39) 0.068 723 009 906 278 4 × 2 = 0 + 0.137 446 019 812 556 8;
  • 40) 0.137 446 019 812 556 8 × 2 = 0 + 0.274 892 039 625 113 6;
  • 41) 0.274 892 039 625 113 6 × 2 = 0 + 0.549 784 079 250 227 2;
  • 42) 0.549 784 079 250 227 2 × 2 = 1 + 0.099 568 158 500 454 4;
  • 43) 0.099 568 158 500 454 4 × 2 = 0 + 0.199 136 317 000 908 8;
  • 44) 0.199 136 317 000 908 8 × 2 = 0 + 0.398 272 634 001 817 6;
  • 45) 0.398 272 634 001 817 6 × 2 = 0 + 0.796 545 268 003 635 2;
  • 46) 0.796 545 268 003 635 2 × 2 = 1 + 0.593 090 536 007 270 4;
  • 47) 0.593 090 536 007 270 4 × 2 = 1 + 0.186 181 072 014 540 8;
  • 48) 0.186 181 072 014 540 8 × 2 = 0 + 0.372 362 144 029 081 6;
  • 49) 0.372 362 144 029 081 6 × 2 = 0 + 0.744 724 288 058 163 2;
  • 50) 0.744 724 288 058 163 2 × 2 = 1 + 0.489 448 576 116 326 4;
  • 51) 0.489 448 576 116 326 4 × 2 = 0 + 0.978 897 152 232 652 8;
  • 52) 0.978 897 152 232 652 8 × 2 = 1 + 0.957 794 304 465 305 6;
  • 53) 0.957 794 304 465 305 6 × 2 = 1 + 0.915 588 608 930 611 2;

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:


0.123 145 321 678 998 6(10) =


0.0001 1111 1000 0110 0111 0011 1010 1001 0100 0100 0100 0110 0101 1(2)

5. Positive number before normalization:

3.123 145 321 678 998 6(10) =


11.0001 1111 1000 0110 0111 0011 1010 1001 0100 0100 0100 0110 0101 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:


3.123 145 321 678 998 6(10) =


11.0001 1111 1000 0110 0111 0011 1010 1001 0100 0100 0100 0110 0101 1(2) =


11.0001 1111 1000 0110 0111 0011 1010 1001 0100 0100 0100 0110 0101 1(2) × 20 =


1.1000 1111 1100 0011 0011 1001 1101 0100 1010 0010 0010 0011 0010 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):
1.1000 1111 1100 0011 0011 1001 1101 0100 1010 0010 0010 0011 0010 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. 1000 1111 1100 0011 0011 1001 1101 0100 1010 0010 0010 0011 0010 11 =


1000 1111 1100 0011 0011 1001 1101 0100 1010 0010 0010 0011 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) =
1000 1111 1100 0011 0011 1001 1101 0100 1010 0010 0010 0011 0010


Decimal number 3.123 145 321 678 998 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 1000 1111 1100 0011 0011 1001 1101 0100 1010 0010 0010 0011 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