33.780 086 699 999 823 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 823(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
33.780 086 699 999 823(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: 0.780 086 699 999 823.

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) 0.780 086 699 999 823 × 2 = 1 + 0.560 173 399 999 646;
  • 2) 0.560 173 399 999 646 × 2 = 1 + 0.120 346 799 999 292;
  • 3) 0.120 346 799 999 292 × 2 = 0 + 0.240 693 599 998 584;
  • 4) 0.240 693 599 998 584 × 2 = 0 + 0.481 387 199 997 168;
  • 5) 0.481 387 199 997 168 × 2 = 0 + 0.962 774 399 994 336;
  • 6) 0.962 774 399 994 336 × 2 = 1 + 0.925 548 799 988 672;
  • 7) 0.925 548 799 988 672 × 2 = 1 + 0.851 097 599 977 344;
  • 8) 0.851 097 599 977 344 × 2 = 1 + 0.702 195 199 954 688;
  • 9) 0.702 195 199 954 688 × 2 = 1 + 0.404 390 399 909 376;
  • 10) 0.404 390 399 909 376 × 2 = 0 + 0.808 780 799 818 752;
  • 11) 0.808 780 799 818 752 × 2 = 1 + 0.617 561 599 637 504;
  • 12) 0.617 561 599 637 504 × 2 = 1 + 0.235 123 199 275 008;
  • 13) 0.235 123 199 275 008 × 2 = 0 + 0.470 246 398 550 016;
  • 14) 0.470 246 398 550 016 × 2 = 0 + 0.940 492 797 100 032;
  • 15) 0.940 492 797 100 032 × 2 = 1 + 0.880 985 594 200 064;
  • 16) 0.880 985 594 200 064 × 2 = 1 + 0.761 971 188 400 128;
  • 17) 0.761 971 188 400 128 × 2 = 1 + 0.523 942 376 800 256;
  • 18) 0.523 942 376 800 256 × 2 = 1 + 0.047 884 753 600 512;
  • 19) 0.047 884 753 600 512 × 2 = 0 + 0.095 769 507 201 024;
  • 20) 0.095 769 507 201 024 × 2 = 0 + 0.191 539 014 402 048;
  • 21) 0.191 539 014 402 048 × 2 = 0 + 0.383 078 028 804 096;
  • 22) 0.383 078 028 804 096 × 2 = 0 + 0.766 156 057 608 192;
  • 23) 0.766 156 057 608 192 × 2 = 1 + 0.532 312 115 216 384;
  • 24) 0.532 312 115 216 384 × 2 = 1 + 0.064 624 230 432 768;
  • 25) 0.064 624 230 432 768 × 2 = 0 + 0.129 248 460 865 536;
  • 26) 0.129 248 460 865 536 × 2 = 0 + 0.258 496 921 731 072;
  • 27) 0.258 496 921 731 072 × 2 = 0 + 0.516 993 843 462 144;
  • 28) 0.516 993 843 462 144 × 2 = 1 + 0.033 987 686 924 288;
  • 29) 0.033 987 686 924 288 × 2 = 0 + 0.067 975 373 848 576;
  • 30) 0.067 975 373 848 576 × 2 = 0 + 0.135 950 747 697 152;
  • 31) 0.135 950 747 697 152 × 2 = 0 + 0.271 901 495 394 304;
  • 32) 0.271 901 495 394 304 × 2 = 0 + 0.543 802 990 788 608;
  • 33) 0.543 802 990 788 608 × 2 = 1 + 0.087 605 981 577 216;
  • 34) 0.087 605 981 577 216 × 2 = 0 + 0.175 211 963 154 432;
  • 35) 0.175 211 963 154 432 × 2 = 0 + 0.350 423 926 308 864;
  • 36) 0.350 423 926 308 864 × 2 = 0 + 0.700 847 852 617 728;
  • 37) 0.700 847 852 617 728 × 2 = 1 + 0.401 695 705 235 456;
  • 38) 0.401 695 705 235 456 × 2 = 0 + 0.803 391 410 470 912;
  • 39) 0.803 391 410 470 912 × 2 = 1 + 0.606 782 820 941 824;
  • 40) 0.606 782 820 941 824 × 2 = 1 + 0.213 565 641 883 648;
  • 41) 0.213 565 641 883 648 × 2 = 0 + 0.427 131 283 767 296;
  • 42) 0.427 131 283 767 296 × 2 = 0 + 0.854 262 567 534 592;
  • 43) 0.854 262 567 534 592 × 2 = 1 + 0.708 525 135 069 184;
  • 44) 0.708 525 135 069 184 × 2 = 1 + 0.417 050 270 138 368;
  • 45) 0.417 050 270 138 368 × 2 = 0 + 0.834 100 540 276 736;
  • 46) 0.834 100 540 276 736 × 2 = 1 + 0.668 201 080 553 472;
  • 47) 0.668 201 080 553 472 × 2 = 1 + 0.336 402 161 106 944;
  • 48) 0.336 402 161 106 944 × 2 = 0 + 0.672 804 322 213 888;
  • 49) 0.672 804 322 213 888 × 2 = 1 + 0.345 608 644 427 776;
  • 50) 0.345 608 644 427 776 × 2 = 0 + 0.691 217 288 855 552;
  • 51) 0.691 217 288 855 552 × 2 = 1 + 0.382 434 577 711 104;
  • 52) 0.382 434 577 711 104 × 2 = 0 + 0.764 869 155 422 208;
  • 53) 0.764 869 155 422 208 × 2 = 1 + 0.529 738 310 844 416;

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:


0.780 086 699 999 823(10) =


0.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0110 1010 1(2)

5. Positive number before normalization:

33.780 086 699 999 823(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0110 1010 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:


33.780 086 699 999 823(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0110 1010 1(2) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0011 0110 1010 1(2) × 20 =


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 1011 0101 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 1001 1011 0101 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 1001 1011 01 0101 =


0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1001 1011


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 1011


Decimal number 33.780 086 699 999 823 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 1011


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