33.780 086 699 999 806 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 806(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
33.780 086 699 999 806(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: 0.780 086 699 999 806.

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) 0.780 086 699 999 806 × 2 = 1 + 0.560 173 399 999 612;
  • 2) 0.560 173 399 999 612 × 2 = 1 + 0.120 346 799 999 224;
  • 3) 0.120 346 799 999 224 × 2 = 0 + 0.240 693 599 998 448;
  • 4) 0.240 693 599 998 448 × 2 = 0 + 0.481 387 199 996 896;
  • 5) 0.481 387 199 996 896 × 2 = 0 + 0.962 774 399 993 792;
  • 6) 0.962 774 399 993 792 × 2 = 1 + 0.925 548 799 987 584;
  • 7) 0.925 548 799 987 584 × 2 = 1 + 0.851 097 599 975 168;
  • 8) 0.851 097 599 975 168 × 2 = 1 + 0.702 195 199 950 336;
  • 9) 0.702 195 199 950 336 × 2 = 1 + 0.404 390 399 900 672;
  • 10) 0.404 390 399 900 672 × 2 = 0 + 0.808 780 799 801 344;
  • 11) 0.808 780 799 801 344 × 2 = 1 + 0.617 561 599 602 688;
  • 12) 0.617 561 599 602 688 × 2 = 1 + 0.235 123 199 205 376;
  • 13) 0.235 123 199 205 376 × 2 = 0 + 0.470 246 398 410 752;
  • 14) 0.470 246 398 410 752 × 2 = 0 + 0.940 492 796 821 504;
  • 15) 0.940 492 796 821 504 × 2 = 1 + 0.880 985 593 643 008;
  • 16) 0.880 985 593 643 008 × 2 = 1 + 0.761 971 187 286 016;
  • 17) 0.761 971 187 286 016 × 2 = 1 + 0.523 942 374 572 032;
  • 18) 0.523 942 374 572 032 × 2 = 1 + 0.047 884 749 144 064;
  • 19) 0.047 884 749 144 064 × 2 = 0 + 0.095 769 498 288 128;
  • 20) 0.095 769 498 288 128 × 2 = 0 + 0.191 538 996 576 256;
  • 21) 0.191 538 996 576 256 × 2 = 0 + 0.383 077 993 152 512;
  • 22) 0.383 077 993 152 512 × 2 = 0 + 0.766 155 986 305 024;
  • 23) 0.766 155 986 305 024 × 2 = 1 + 0.532 311 972 610 048;
  • 24) 0.532 311 972 610 048 × 2 = 1 + 0.064 623 945 220 096;
  • 25) 0.064 623 945 220 096 × 2 = 0 + 0.129 247 890 440 192;
  • 26) 0.129 247 890 440 192 × 2 = 0 + 0.258 495 780 880 384;
  • 27) 0.258 495 780 880 384 × 2 = 0 + 0.516 991 561 760 768;
  • 28) 0.516 991 561 760 768 × 2 = 1 + 0.033 983 123 521 536;
  • 29) 0.033 983 123 521 536 × 2 = 0 + 0.067 966 247 043 072;
  • 30) 0.067 966 247 043 072 × 2 = 0 + 0.135 932 494 086 144;
  • 31) 0.135 932 494 086 144 × 2 = 0 + 0.271 864 988 172 288;
  • 32) 0.271 864 988 172 288 × 2 = 0 + 0.543 729 976 344 576;
  • 33) 0.543 729 976 344 576 × 2 = 1 + 0.087 459 952 689 152;
  • 34) 0.087 459 952 689 152 × 2 = 0 + 0.174 919 905 378 304;
  • 35) 0.174 919 905 378 304 × 2 = 0 + 0.349 839 810 756 608;
  • 36) 0.349 839 810 756 608 × 2 = 0 + 0.699 679 621 513 216;
  • 37) 0.699 679 621 513 216 × 2 = 1 + 0.399 359 243 026 432;
  • 38) 0.399 359 243 026 432 × 2 = 0 + 0.798 718 486 052 864;
  • 39) 0.798 718 486 052 864 × 2 = 1 + 0.597 436 972 105 728;
  • 40) 0.597 436 972 105 728 × 2 = 1 + 0.194 873 944 211 456;
  • 41) 0.194 873 944 211 456 × 2 = 0 + 0.389 747 888 422 912;
  • 42) 0.389 747 888 422 912 × 2 = 0 + 0.779 495 776 845 824;
  • 43) 0.779 495 776 845 824 × 2 = 1 + 0.558 991 553 691 648;
  • 44) 0.558 991 553 691 648 × 2 = 1 + 0.117 983 107 383 296;
  • 45) 0.117 983 107 383 296 × 2 = 0 + 0.235 966 214 766 592;
  • 46) 0.235 966 214 766 592 × 2 = 0 + 0.471 932 429 533 184;
  • 47) 0.471 932 429 533 184 × 2 = 0 + 0.943 864 859 066 368;
  • 48) 0.943 864 859 066 368 × 2 = 1 + 0.887 729 718 132 736;
  • 49) 0.887 729 718 132 736 × 2 = 1 + 0.775 459 436 265 472;
  • 50) 0.775 459 436 265 472 × 2 = 1 + 0.550 918 872 530 944;
  • 51) 0.550 918 872 530 944 × 2 = 1 + 0.101 837 745 061 888;
  • 52) 0.101 837 745 061 888 × 2 = 0 + 0.203 675 490 123 776;
  • 53) 0.203 675 490 123 776 × 2 = 0 + 0.407 350 980 247 552;

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:


0.780 086 699 999 806(10) =


0.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0001 1110 0(2)

5. Positive number before normalization:

33.780 086 699 999 806(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0001 1110 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:


33.780 086 699 999 806(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0001 1110 0(2) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0001 1110 0(2) × 20 =


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 1000 1111 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 1001 1000 1111 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 1001 1000 11 1100 =


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


Decimal number 33.780 086 699 999 806 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 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