33.780 086 699 999 913 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 913(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
33.780 086 699 999 913(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: 0.780 086 699 999 913.

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) 0.780 086 699 999 913 × 2 = 1 + 0.560 173 399 999 826;
  • 2) 0.560 173 399 999 826 × 2 = 1 + 0.120 346 799 999 652;
  • 3) 0.120 346 799 999 652 × 2 = 0 + 0.240 693 599 999 304;
  • 4) 0.240 693 599 999 304 × 2 = 0 + 0.481 387 199 998 608;
  • 5) 0.481 387 199 998 608 × 2 = 0 + 0.962 774 399 997 216;
  • 6) 0.962 774 399 997 216 × 2 = 1 + 0.925 548 799 994 432;
  • 7) 0.925 548 799 994 432 × 2 = 1 + 0.851 097 599 988 864;
  • 8) 0.851 097 599 988 864 × 2 = 1 + 0.702 195 199 977 728;
  • 9) 0.702 195 199 977 728 × 2 = 1 + 0.404 390 399 955 456;
  • 10) 0.404 390 399 955 456 × 2 = 0 + 0.808 780 799 910 912;
  • 11) 0.808 780 799 910 912 × 2 = 1 + 0.617 561 599 821 824;
  • 12) 0.617 561 599 821 824 × 2 = 1 + 0.235 123 199 643 648;
  • 13) 0.235 123 199 643 648 × 2 = 0 + 0.470 246 399 287 296;
  • 14) 0.470 246 399 287 296 × 2 = 0 + 0.940 492 798 574 592;
  • 15) 0.940 492 798 574 592 × 2 = 1 + 0.880 985 597 149 184;
  • 16) 0.880 985 597 149 184 × 2 = 1 + 0.761 971 194 298 368;
  • 17) 0.761 971 194 298 368 × 2 = 1 + 0.523 942 388 596 736;
  • 18) 0.523 942 388 596 736 × 2 = 1 + 0.047 884 777 193 472;
  • 19) 0.047 884 777 193 472 × 2 = 0 + 0.095 769 554 386 944;
  • 20) 0.095 769 554 386 944 × 2 = 0 + 0.191 539 108 773 888;
  • 21) 0.191 539 108 773 888 × 2 = 0 + 0.383 078 217 547 776;
  • 22) 0.383 078 217 547 776 × 2 = 0 + 0.766 156 435 095 552;
  • 23) 0.766 156 435 095 552 × 2 = 1 + 0.532 312 870 191 104;
  • 24) 0.532 312 870 191 104 × 2 = 1 + 0.064 625 740 382 208;
  • 25) 0.064 625 740 382 208 × 2 = 0 + 0.129 251 480 764 416;
  • 26) 0.129 251 480 764 416 × 2 = 0 + 0.258 502 961 528 832;
  • 27) 0.258 502 961 528 832 × 2 = 0 + 0.517 005 923 057 664;
  • 28) 0.517 005 923 057 664 × 2 = 1 + 0.034 011 846 115 328;
  • 29) 0.034 011 846 115 328 × 2 = 0 + 0.068 023 692 230 656;
  • 30) 0.068 023 692 230 656 × 2 = 0 + 0.136 047 384 461 312;
  • 31) 0.136 047 384 461 312 × 2 = 0 + 0.272 094 768 922 624;
  • 32) 0.272 094 768 922 624 × 2 = 0 + 0.544 189 537 845 248;
  • 33) 0.544 189 537 845 248 × 2 = 1 + 0.088 379 075 690 496;
  • 34) 0.088 379 075 690 496 × 2 = 0 + 0.176 758 151 380 992;
  • 35) 0.176 758 151 380 992 × 2 = 0 + 0.353 516 302 761 984;
  • 36) 0.353 516 302 761 984 × 2 = 0 + 0.707 032 605 523 968;
  • 37) 0.707 032 605 523 968 × 2 = 1 + 0.414 065 211 047 936;
  • 38) 0.414 065 211 047 936 × 2 = 0 + 0.828 130 422 095 872;
  • 39) 0.828 130 422 095 872 × 2 = 1 + 0.656 260 844 191 744;
  • 40) 0.656 260 844 191 744 × 2 = 1 + 0.312 521 688 383 488;
  • 41) 0.312 521 688 383 488 × 2 = 0 + 0.625 043 376 766 976;
  • 42) 0.625 043 376 766 976 × 2 = 1 + 0.250 086 753 533 952;
  • 43) 0.250 086 753 533 952 × 2 = 0 + 0.500 173 507 067 904;
  • 44) 0.500 173 507 067 904 × 2 = 1 + 0.000 347 014 135 808;
  • 45) 0.000 347 014 135 808 × 2 = 0 + 0.000 694 028 271 616;
  • 46) 0.000 694 028 271 616 × 2 = 0 + 0.001 388 056 543 232;
  • 47) 0.001 388 056 543 232 × 2 = 0 + 0.002 776 113 086 464;
  • 48) 0.002 776 113 086 464 × 2 = 0 + 0.005 552 226 172 928;
  • 49) 0.005 552 226 172 928 × 2 = 0 + 0.011 104 452 345 856;
  • 50) 0.011 104 452 345 856 × 2 = 0 + 0.022 208 904 691 712;
  • 51) 0.022 208 904 691 712 × 2 = 0 + 0.044 417 809 383 424;
  • 52) 0.044 417 809 383 424 × 2 = 0 + 0.088 835 618 766 848;
  • 53) 0.088 835 618 766 848 × 2 = 0 + 0.177 671 237 533 696;

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:


0.780 086 699 999 913(10) =


0.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0101 0000 0000 0(2)

5. Positive number before normalization:

33.780 086 699 999 913(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0101 0000 0000 0(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:


33.780 086 699 999 913(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0101 0000 0000 0(2) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0101 0000 0000 0(2) × 20 =


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 1000 0000 00(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 1010 1000 0000 00


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 1010 1000 00 0000 =


0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 1000


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 1010 1000


Decimal number 33.780 086 699 999 913 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 1010 1000


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