33.780 086 699 999 866 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 866(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
33.780 086 699 999 866(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: 0.780 086 699 999 866.

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) 0.780 086 699 999 866 × 2 = 1 + 0.560 173 399 999 732;
  • 2) 0.560 173 399 999 732 × 2 = 1 + 0.120 346 799 999 464;
  • 3) 0.120 346 799 999 464 × 2 = 0 + 0.240 693 599 998 928;
  • 4) 0.240 693 599 998 928 × 2 = 0 + 0.481 387 199 997 856;
  • 5) 0.481 387 199 997 856 × 2 = 0 + 0.962 774 399 995 712;
  • 6) 0.962 774 399 995 712 × 2 = 1 + 0.925 548 799 991 424;
  • 7) 0.925 548 799 991 424 × 2 = 1 + 0.851 097 599 982 848;
  • 8) 0.851 097 599 982 848 × 2 = 1 + 0.702 195 199 965 696;
  • 9) 0.702 195 199 965 696 × 2 = 1 + 0.404 390 399 931 392;
  • 10) 0.404 390 399 931 392 × 2 = 0 + 0.808 780 799 862 784;
  • 11) 0.808 780 799 862 784 × 2 = 1 + 0.617 561 599 725 568;
  • 12) 0.617 561 599 725 568 × 2 = 1 + 0.235 123 199 451 136;
  • 13) 0.235 123 199 451 136 × 2 = 0 + 0.470 246 398 902 272;
  • 14) 0.470 246 398 902 272 × 2 = 0 + 0.940 492 797 804 544;
  • 15) 0.940 492 797 804 544 × 2 = 1 + 0.880 985 595 609 088;
  • 16) 0.880 985 595 609 088 × 2 = 1 + 0.761 971 191 218 176;
  • 17) 0.761 971 191 218 176 × 2 = 1 + 0.523 942 382 436 352;
  • 18) 0.523 942 382 436 352 × 2 = 1 + 0.047 884 764 872 704;
  • 19) 0.047 884 764 872 704 × 2 = 0 + 0.095 769 529 745 408;
  • 20) 0.095 769 529 745 408 × 2 = 0 + 0.191 539 059 490 816;
  • 21) 0.191 539 059 490 816 × 2 = 0 + 0.383 078 118 981 632;
  • 22) 0.383 078 118 981 632 × 2 = 0 + 0.766 156 237 963 264;
  • 23) 0.766 156 237 963 264 × 2 = 1 + 0.532 312 475 926 528;
  • 24) 0.532 312 475 926 528 × 2 = 1 + 0.064 624 951 853 056;
  • 25) 0.064 624 951 853 056 × 2 = 0 + 0.129 249 903 706 112;
  • 26) 0.129 249 903 706 112 × 2 = 0 + 0.258 499 807 412 224;
  • 27) 0.258 499 807 412 224 × 2 = 0 + 0.516 999 614 824 448;
  • 28) 0.516 999 614 824 448 × 2 = 1 + 0.033 999 229 648 896;
  • 29) 0.033 999 229 648 896 × 2 = 0 + 0.067 998 459 297 792;
  • 30) 0.067 998 459 297 792 × 2 = 0 + 0.135 996 918 595 584;
  • 31) 0.135 996 918 595 584 × 2 = 0 + 0.271 993 837 191 168;
  • 32) 0.271 993 837 191 168 × 2 = 0 + 0.543 987 674 382 336;
  • 33) 0.543 987 674 382 336 × 2 = 1 + 0.087 975 348 764 672;
  • 34) 0.087 975 348 764 672 × 2 = 0 + 0.175 950 697 529 344;
  • 35) 0.175 950 697 529 344 × 2 = 0 + 0.351 901 395 058 688;
  • 36) 0.351 901 395 058 688 × 2 = 0 + 0.703 802 790 117 376;
  • 37) 0.703 802 790 117 376 × 2 = 1 + 0.407 605 580 234 752;
  • 38) 0.407 605 580 234 752 × 2 = 0 + 0.815 211 160 469 504;
  • 39) 0.815 211 160 469 504 × 2 = 1 + 0.630 422 320 939 008;
  • 40) 0.630 422 320 939 008 × 2 = 1 + 0.260 844 641 878 016;
  • 41) 0.260 844 641 878 016 × 2 = 0 + 0.521 689 283 756 032;
  • 42) 0.521 689 283 756 032 × 2 = 1 + 0.043 378 567 512 064;
  • 43) 0.043 378 567 512 064 × 2 = 0 + 0.086 757 135 024 128;
  • 44) 0.086 757 135 024 128 × 2 = 0 + 0.173 514 270 048 256;
  • 45) 0.173 514 270 048 256 × 2 = 0 + 0.347 028 540 096 512;
  • 46) 0.347 028 540 096 512 × 2 = 0 + 0.694 057 080 193 024;
  • 47) 0.694 057 080 193 024 × 2 = 1 + 0.388 114 160 386 048;
  • 48) 0.388 114 160 386 048 × 2 = 0 + 0.776 228 320 772 096;
  • 49) 0.776 228 320 772 096 × 2 = 1 + 0.552 456 641 544 192;
  • 50) 0.552 456 641 544 192 × 2 = 1 + 0.104 913 283 088 384;
  • 51) 0.104 913 283 088 384 × 2 = 0 + 0.209 826 566 176 768;
  • 52) 0.209 826 566 176 768 × 2 = 0 + 0.419 653 132 353 536;
  • 53) 0.419 653 132 353 536 × 2 = 0 + 0.839 306 264 707 072;

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:


0.780 086 699 999 866(10) =


0.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0100 0010 1100 0(2)

5. Positive number before normalization:

33.780 086 699 999 866(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0100 0010 1100 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:


33.780 086 699 999 866(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0100 0010 1100 0(2) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0100 0010 1100 0(2) × 20 =


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 0001 0110 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 0001 0110 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 0001 01 1000 =


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


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 0001


Decimal number 33.780 086 699 999 866 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 0001


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