33.780 086 699 999 918 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 918(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
33.780 086 699 999 918(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: 0.780 086 699 999 918.

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) 0.780 086 699 999 918 × 2 = 1 + 0.560 173 399 999 836;
  • 2) 0.560 173 399 999 836 × 2 = 1 + 0.120 346 799 999 672;
  • 3) 0.120 346 799 999 672 × 2 = 0 + 0.240 693 599 999 344;
  • 4) 0.240 693 599 999 344 × 2 = 0 + 0.481 387 199 998 688;
  • 5) 0.481 387 199 998 688 × 2 = 0 + 0.962 774 399 997 376;
  • 6) 0.962 774 399 997 376 × 2 = 1 + 0.925 548 799 994 752;
  • 7) 0.925 548 799 994 752 × 2 = 1 + 0.851 097 599 989 504;
  • 8) 0.851 097 599 989 504 × 2 = 1 + 0.702 195 199 979 008;
  • 9) 0.702 195 199 979 008 × 2 = 1 + 0.404 390 399 958 016;
  • 10) 0.404 390 399 958 016 × 2 = 0 + 0.808 780 799 916 032;
  • 11) 0.808 780 799 916 032 × 2 = 1 + 0.617 561 599 832 064;
  • 12) 0.617 561 599 832 064 × 2 = 1 + 0.235 123 199 664 128;
  • 13) 0.235 123 199 664 128 × 2 = 0 + 0.470 246 399 328 256;
  • 14) 0.470 246 399 328 256 × 2 = 0 + 0.940 492 798 656 512;
  • 15) 0.940 492 798 656 512 × 2 = 1 + 0.880 985 597 313 024;
  • 16) 0.880 985 597 313 024 × 2 = 1 + 0.761 971 194 626 048;
  • 17) 0.761 971 194 626 048 × 2 = 1 + 0.523 942 389 252 096;
  • 18) 0.523 942 389 252 096 × 2 = 1 + 0.047 884 778 504 192;
  • 19) 0.047 884 778 504 192 × 2 = 0 + 0.095 769 557 008 384;
  • 20) 0.095 769 557 008 384 × 2 = 0 + 0.191 539 114 016 768;
  • 21) 0.191 539 114 016 768 × 2 = 0 + 0.383 078 228 033 536;
  • 22) 0.383 078 228 033 536 × 2 = 0 + 0.766 156 456 067 072;
  • 23) 0.766 156 456 067 072 × 2 = 1 + 0.532 312 912 134 144;
  • 24) 0.532 312 912 134 144 × 2 = 1 + 0.064 625 824 268 288;
  • 25) 0.064 625 824 268 288 × 2 = 0 + 0.129 251 648 536 576;
  • 26) 0.129 251 648 536 576 × 2 = 0 + 0.258 503 297 073 152;
  • 27) 0.258 503 297 073 152 × 2 = 0 + 0.517 006 594 146 304;
  • 28) 0.517 006 594 146 304 × 2 = 1 + 0.034 013 188 292 608;
  • 29) 0.034 013 188 292 608 × 2 = 0 + 0.068 026 376 585 216;
  • 30) 0.068 026 376 585 216 × 2 = 0 + 0.136 052 753 170 432;
  • 31) 0.136 052 753 170 432 × 2 = 0 + 0.272 105 506 340 864;
  • 32) 0.272 105 506 340 864 × 2 = 0 + 0.544 211 012 681 728;
  • 33) 0.544 211 012 681 728 × 2 = 1 + 0.088 422 025 363 456;
  • 34) 0.088 422 025 363 456 × 2 = 0 + 0.176 844 050 726 912;
  • 35) 0.176 844 050 726 912 × 2 = 0 + 0.353 688 101 453 824;
  • 36) 0.353 688 101 453 824 × 2 = 0 + 0.707 376 202 907 648;
  • 37) 0.707 376 202 907 648 × 2 = 1 + 0.414 752 405 815 296;
  • 38) 0.414 752 405 815 296 × 2 = 0 + 0.829 504 811 630 592;
  • 39) 0.829 504 811 630 592 × 2 = 1 + 0.659 009 623 261 184;
  • 40) 0.659 009 623 261 184 × 2 = 1 + 0.318 019 246 522 368;
  • 41) 0.318 019 246 522 368 × 2 = 0 + 0.636 038 493 044 736;
  • 42) 0.636 038 493 044 736 × 2 = 1 + 0.272 076 986 089 472;
  • 43) 0.272 076 986 089 472 × 2 = 0 + 0.544 153 972 178 944;
  • 44) 0.544 153 972 178 944 × 2 = 1 + 0.088 307 944 357 888;
  • 45) 0.088 307 944 357 888 × 2 = 0 + 0.176 615 888 715 776;
  • 46) 0.176 615 888 715 776 × 2 = 0 + 0.353 231 777 431 552;
  • 47) 0.353 231 777 431 552 × 2 = 0 + 0.706 463 554 863 104;
  • 48) 0.706 463 554 863 104 × 2 = 1 + 0.412 927 109 726 208;
  • 49) 0.412 927 109 726 208 × 2 = 0 + 0.825 854 219 452 416;
  • 50) 0.825 854 219 452 416 × 2 = 1 + 0.651 708 438 904 832;
  • 51) 0.651 708 438 904 832 × 2 = 1 + 0.303 416 877 809 664;
  • 52) 0.303 416 877 809 664 × 2 = 0 + 0.606 833 755 619 328;
  • 53) 0.606 833 755 619 328 × 2 = 1 + 0.213 667 511 238 656;

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:


0.780 086 699 999 918(10) =


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

5. Positive number before normalization:

33.780 086 699 999 918(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0101 0001 0110 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:


33.780 086 699 999 918(10) =


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


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


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1010 1000 1011 01(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 1011 01


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 10 1101 =


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 33.780 086 699 999 918 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