33.780 086 699 999 765 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 765(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
33.780 086 699 999 765(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: 33.
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;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 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.

33(10) =


10 0001(2)


3. Convert to binary (base 2) the fractional part: 0.780 086 699 999 765.

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) 0.780 086 699 999 765 × 2 = 1 + 0.560 173 399 999 53;
  • 2) 0.560 173 399 999 53 × 2 = 1 + 0.120 346 799 999 06;
  • 3) 0.120 346 799 999 06 × 2 = 0 + 0.240 693 599 998 12;
  • 4) 0.240 693 599 998 12 × 2 = 0 + 0.481 387 199 996 24;
  • 5) 0.481 387 199 996 24 × 2 = 0 + 0.962 774 399 992 48;
  • 6) 0.962 774 399 992 48 × 2 = 1 + 0.925 548 799 984 96;
  • 7) 0.925 548 799 984 96 × 2 = 1 + 0.851 097 599 969 92;
  • 8) 0.851 097 599 969 92 × 2 = 1 + 0.702 195 199 939 84;
  • 9) 0.702 195 199 939 84 × 2 = 1 + 0.404 390 399 879 68;
  • 10) 0.404 390 399 879 68 × 2 = 0 + 0.808 780 799 759 36;
  • 11) 0.808 780 799 759 36 × 2 = 1 + 0.617 561 599 518 72;
  • 12) 0.617 561 599 518 72 × 2 = 1 + 0.235 123 199 037 44;
  • 13) 0.235 123 199 037 44 × 2 = 0 + 0.470 246 398 074 88;
  • 14) 0.470 246 398 074 88 × 2 = 0 + 0.940 492 796 149 76;
  • 15) 0.940 492 796 149 76 × 2 = 1 + 0.880 985 592 299 52;
  • 16) 0.880 985 592 299 52 × 2 = 1 + 0.761 971 184 599 04;
  • 17) 0.761 971 184 599 04 × 2 = 1 + 0.523 942 369 198 08;
  • 18) 0.523 942 369 198 08 × 2 = 1 + 0.047 884 738 396 16;
  • 19) 0.047 884 738 396 16 × 2 = 0 + 0.095 769 476 792 32;
  • 20) 0.095 769 476 792 32 × 2 = 0 + 0.191 538 953 584 64;
  • 21) 0.191 538 953 584 64 × 2 = 0 + 0.383 077 907 169 28;
  • 22) 0.383 077 907 169 28 × 2 = 0 + 0.766 155 814 338 56;
  • 23) 0.766 155 814 338 56 × 2 = 1 + 0.532 311 628 677 12;
  • 24) 0.532 311 628 677 12 × 2 = 1 + 0.064 623 257 354 24;
  • 25) 0.064 623 257 354 24 × 2 = 0 + 0.129 246 514 708 48;
  • 26) 0.129 246 514 708 48 × 2 = 0 + 0.258 493 029 416 96;
  • 27) 0.258 493 029 416 96 × 2 = 0 + 0.516 986 058 833 92;
  • 28) 0.516 986 058 833 92 × 2 = 1 + 0.033 972 117 667 84;
  • 29) 0.033 972 117 667 84 × 2 = 0 + 0.067 944 235 335 68;
  • 30) 0.067 944 235 335 68 × 2 = 0 + 0.135 888 470 671 36;
  • 31) 0.135 888 470 671 36 × 2 = 0 + 0.271 776 941 342 72;
  • 32) 0.271 776 941 342 72 × 2 = 0 + 0.543 553 882 685 44;
  • 33) 0.543 553 882 685 44 × 2 = 1 + 0.087 107 765 370 88;
  • 34) 0.087 107 765 370 88 × 2 = 0 + 0.174 215 530 741 76;
  • 35) 0.174 215 530 741 76 × 2 = 0 + 0.348 431 061 483 52;
  • 36) 0.348 431 061 483 52 × 2 = 0 + 0.696 862 122 967 04;
  • 37) 0.696 862 122 967 04 × 2 = 1 + 0.393 724 245 934 08;
  • 38) 0.393 724 245 934 08 × 2 = 0 + 0.787 448 491 868 16;
  • 39) 0.787 448 491 868 16 × 2 = 1 + 0.574 896 983 736 32;
  • 40) 0.574 896 983 736 32 × 2 = 1 + 0.149 793 967 472 64;
  • 41) 0.149 793 967 472 64 × 2 = 0 + 0.299 587 934 945 28;
  • 42) 0.299 587 934 945 28 × 2 = 0 + 0.599 175 869 890 56;
  • 43) 0.599 175 869 890 56 × 2 = 1 + 0.198 351 739 781 12;
  • 44) 0.198 351 739 781 12 × 2 = 0 + 0.396 703 479 562 24;
  • 45) 0.396 703 479 562 24 × 2 = 0 + 0.793 406 959 124 48;
  • 46) 0.793 406 959 124 48 × 2 = 1 + 0.586 813 918 248 96;
  • 47) 0.586 813 918 248 96 × 2 = 1 + 0.173 627 836 497 92;
  • 48) 0.173 627 836 497 92 × 2 = 0 + 0.347 255 672 995 84;
  • 49) 0.347 255 672 995 84 × 2 = 0 + 0.694 511 345 991 68;
  • 50) 0.694 511 345 991 68 × 2 = 1 + 0.389 022 691 983 36;
  • 51) 0.389 022 691 983 36 × 2 = 0 + 0.778 045 383 966 72;
  • 52) 0.778 045 383 966 72 × 2 = 1 + 0.556 090 767 933 44;
  • 53) 0.556 090 767 933 44 × 2 = 1 + 0.112 181 535 866 88;

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:


0.780 086 699 999 765(10) =


0.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0010 0110 0101 1(2)

5. Positive number before normalization:

33.780 086 699 999 765(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0010 0110 0101 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 5 positions to the left, so that only one non zero digit remains to the left of it:


33.780 086 699 999 765(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0010 0110 0101 1(2) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0010 0110 0101 1(2) × 20 =


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 0011 0010 11(2) × 25


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): 5


Mantissa (not normalized):
1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 0011 0010 11


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


5 + 2(11-1) - 1 =


(5 + 1 023)(10) =


1 028(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;
  • 1 028 ÷ 2 = 514 + 0;
  • 514 ÷ 2 = 257 + 0;
  • 257 ÷ 2 = 128 + 1;
  • 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) =


1028(10) =


100 0000 0100(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. 0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 0011 00 1011 =


0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 0011


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 0100


Mantissa (52 bits) =
0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 0011


Decimal number 33.780 086 699 999 765 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0100 - 0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 0011


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