3.231 254 577 636 745 1 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 3.231 254 577 636 745 1(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
3.231 254 577 636 745 1(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: 0.231 254 577 636 745 1.

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) 0.231 254 577 636 745 1 × 2 = 0 + 0.462 509 155 273 490 2;
  • 2) 0.462 509 155 273 490 2 × 2 = 0 + 0.925 018 310 546 980 4;
  • 3) 0.925 018 310 546 980 4 × 2 = 1 + 0.850 036 621 093 960 8;
  • 4) 0.850 036 621 093 960 8 × 2 = 1 + 0.700 073 242 187 921 6;
  • 5) 0.700 073 242 187 921 6 × 2 = 1 + 0.400 146 484 375 843 2;
  • 6) 0.400 146 484 375 843 2 × 2 = 0 + 0.800 292 968 751 686 4;
  • 7) 0.800 292 968 751 686 4 × 2 = 1 + 0.600 585 937 503 372 8;
  • 8) 0.600 585 937 503 372 8 × 2 = 1 + 0.201 171 875 006 745 6;
  • 9) 0.201 171 875 006 745 6 × 2 = 0 + 0.402 343 750 013 491 2;
  • 10) 0.402 343 750 013 491 2 × 2 = 0 + 0.804 687 500 026 982 4;
  • 11) 0.804 687 500 026 982 4 × 2 = 1 + 0.609 375 000 053 964 8;
  • 12) 0.609 375 000 053 964 8 × 2 = 1 + 0.218 750 000 107 929 6;
  • 13) 0.218 750 000 107 929 6 × 2 = 0 + 0.437 500 000 215 859 2;
  • 14) 0.437 500 000 215 859 2 × 2 = 0 + 0.875 000 000 431 718 4;
  • 15) 0.875 000 000 431 718 4 × 2 = 1 + 0.750 000 000 863 436 8;
  • 16) 0.750 000 000 863 436 8 × 2 = 1 + 0.500 000 001 726 873 6;
  • 17) 0.500 000 001 726 873 6 × 2 = 1 + 0.000 000 003 453 747 2;
  • 18) 0.000 000 003 453 747 2 × 2 = 0 + 0.000 000 006 907 494 4;
  • 19) 0.000 000 006 907 494 4 × 2 = 0 + 0.000 000 013 814 988 8;
  • 20) 0.000 000 013 814 988 8 × 2 = 0 + 0.000 000 027 629 977 6;
  • 21) 0.000 000 027 629 977 6 × 2 = 0 + 0.000 000 055 259 955 2;
  • 22) 0.000 000 055 259 955 2 × 2 = 0 + 0.000 000 110 519 910 4;
  • 23) 0.000 000 110 519 910 4 × 2 = 0 + 0.000 000 221 039 820 8;
  • 24) 0.000 000 221 039 820 8 × 2 = 0 + 0.000 000 442 079 641 6;
  • 25) 0.000 000 442 079 641 6 × 2 = 0 + 0.000 000 884 159 283 2;
  • 26) 0.000 000 884 159 283 2 × 2 = 0 + 0.000 001 768 318 566 4;
  • 27) 0.000 001 768 318 566 4 × 2 = 0 + 0.000 003 536 637 132 8;
  • 28) 0.000 003 536 637 132 8 × 2 = 0 + 0.000 007 073 274 265 6;
  • 29) 0.000 007 073 274 265 6 × 2 = 0 + 0.000 014 146 548 531 2;
  • 30) 0.000 014 146 548 531 2 × 2 = 0 + 0.000 028 293 097 062 4;
  • 31) 0.000 028 293 097 062 4 × 2 = 0 + 0.000 056 586 194 124 8;
  • 32) 0.000 056 586 194 124 8 × 2 = 0 + 0.000 113 172 388 249 6;
  • 33) 0.000 113 172 388 249 6 × 2 = 0 + 0.000 226 344 776 499 2;
  • 34) 0.000 226 344 776 499 2 × 2 = 0 + 0.000 452 689 552 998 4;
  • 35) 0.000 452 689 552 998 4 × 2 = 0 + 0.000 905 379 105 996 8;
  • 36) 0.000 905 379 105 996 8 × 2 = 0 + 0.001 810 758 211 993 6;
  • 37) 0.001 810 758 211 993 6 × 2 = 0 + 0.003 621 516 423 987 2;
  • 38) 0.003 621 516 423 987 2 × 2 = 0 + 0.007 243 032 847 974 4;
  • 39) 0.007 243 032 847 974 4 × 2 = 0 + 0.014 486 065 695 948 8;
  • 40) 0.014 486 065 695 948 8 × 2 = 0 + 0.028 972 131 391 897 6;
  • 41) 0.028 972 131 391 897 6 × 2 = 0 + 0.057 944 262 783 795 2;
  • 42) 0.057 944 262 783 795 2 × 2 = 0 + 0.115 888 525 567 590 4;
  • 43) 0.115 888 525 567 590 4 × 2 = 0 + 0.231 777 051 135 180 8;
  • 44) 0.231 777 051 135 180 8 × 2 = 0 + 0.463 554 102 270 361 6;
  • 45) 0.463 554 102 270 361 6 × 2 = 0 + 0.927 108 204 540 723 2;
  • 46) 0.927 108 204 540 723 2 × 2 = 1 + 0.854 216 409 081 446 4;
  • 47) 0.854 216 409 081 446 4 × 2 = 1 + 0.708 432 818 162 892 8;
  • 48) 0.708 432 818 162 892 8 × 2 = 1 + 0.416 865 636 325 785 6;
  • 49) 0.416 865 636 325 785 6 × 2 = 0 + 0.833 731 272 651 571 2;
  • 50) 0.833 731 272 651 571 2 × 2 = 1 + 0.667 462 545 303 142 4;
  • 51) 0.667 462 545 303 142 4 × 2 = 1 + 0.334 925 090 606 284 8;
  • 52) 0.334 925 090 606 284 8 × 2 = 0 + 0.669 850 181 212 569 6;
  • 53) 0.669 850 181 212 569 6 × 2 = 1 + 0.339 700 362 425 139 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:


0.231 254 577 636 745 1(10) =


0.0011 1011 0011 0011 1000 0000 0000 0000 0000 0000 0000 0111 0110 1(2)

5. Positive number before normalization:

3.231 254 577 636 745 1(10) =


11.0011 1011 0011 0011 1000 0000 0000 0000 0000 0000 0000 0111 0110 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:


3.231 254 577 636 745 1(10) =


11.0011 1011 0011 0011 1000 0000 0000 0000 0000 0000 0000 0111 0110 1(2) =


11.0011 1011 0011 0011 1000 0000 0000 0000 0000 0000 0000 0111 0110 1(2) × 20 =


1.1001 1101 1001 1001 1100 0000 0000 0000 0000 0000 0000 0011 1011 01(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):
1.1001 1101 1001 1001 1100 0000 0000 0000 0000 0000 0000 0011 1011 01


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. 1001 1101 1001 1001 1100 0000 0000 0000 0000 0000 0000 0011 1011 01 =


1001 1101 1001 1001 1100 0000 0000 0000 0000 0000 0000 0011 1011


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) =
1001 1101 1001 1001 1100 0000 0000 0000 0000 0000 0000 0011 1011


Decimal number 3.231 254 577 636 745 1 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 1001 1101 1001 1001 1100 0000 0000 0000 0000 0000 0000 0011 1011

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