33.780 086 699 999 991 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 33.780 086 699 999 991(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
33.780 086 699 999 991(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: 0.780 086 699 999 991.

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) 0.780 086 699 999 991 × 2 = 1 + 0.560 173 399 999 982;
  • 2) 0.560 173 399 999 982 × 2 = 1 + 0.120 346 799 999 964;
  • 3) 0.120 346 799 999 964 × 2 = 0 + 0.240 693 599 999 928;
  • 4) 0.240 693 599 999 928 × 2 = 0 + 0.481 387 199 999 856;
  • 5) 0.481 387 199 999 856 × 2 = 0 + 0.962 774 399 999 712;
  • 6) 0.962 774 399 999 712 × 2 = 1 + 0.925 548 799 999 424;
  • 7) 0.925 548 799 999 424 × 2 = 1 + 0.851 097 599 998 848;
  • 8) 0.851 097 599 998 848 × 2 = 1 + 0.702 195 199 997 696;
  • 9) 0.702 195 199 997 696 × 2 = 1 + 0.404 390 399 995 392;
  • 10) 0.404 390 399 995 392 × 2 = 0 + 0.808 780 799 990 784;
  • 11) 0.808 780 799 990 784 × 2 = 1 + 0.617 561 599 981 568;
  • 12) 0.617 561 599 981 568 × 2 = 1 + 0.235 123 199 963 136;
  • 13) 0.235 123 199 963 136 × 2 = 0 + 0.470 246 399 926 272;
  • 14) 0.470 246 399 926 272 × 2 = 0 + 0.940 492 799 852 544;
  • 15) 0.940 492 799 852 544 × 2 = 1 + 0.880 985 599 705 088;
  • 16) 0.880 985 599 705 088 × 2 = 1 + 0.761 971 199 410 176;
  • 17) 0.761 971 199 410 176 × 2 = 1 + 0.523 942 398 820 352;
  • 18) 0.523 942 398 820 352 × 2 = 1 + 0.047 884 797 640 704;
  • 19) 0.047 884 797 640 704 × 2 = 0 + 0.095 769 595 281 408;
  • 20) 0.095 769 595 281 408 × 2 = 0 + 0.191 539 190 562 816;
  • 21) 0.191 539 190 562 816 × 2 = 0 + 0.383 078 381 125 632;
  • 22) 0.383 078 381 125 632 × 2 = 0 + 0.766 156 762 251 264;
  • 23) 0.766 156 762 251 264 × 2 = 1 + 0.532 313 524 502 528;
  • 24) 0.532 313 524 502 528 × 2 = 1 + 0.064 627 049 005 056;
  • 25) 0.064 627 049 005 056 × 2 = 0 + 0.129 254 098 010 112;
  • 26) 0.129 254 098 010 112 × 2 = 0 + 0.258 508 196 020 224;
  • 27) 0.258 508 196 020 224 × 2 = 0 + 0.517 016 392 040 448;
  • 28) 0.517 016 392 040 448 × 2 = 1 + 0.034 032 784 080 896;
  • 29) 0.034 032 784 080 896 × 2 = 0 + 0.068 065 568 161 792;
  • 30) 0.068 065 568 161 792 × 2 = 0 + 0.136 131 136 323 584;
  • 31) 0.136 131 136 323 584 × 2 = 0 + 0.272 262 272 647 168;
  • 32) 0.272 262 272 647 168 × 2 = 0 + 0.544 524 545 294 336;
  • 33) 0.544 524 545 294 336 × 2 = 1 + 0.089 049 090 588 672;
  • 34) 0.089 049 090 588 672 × 2 = 0 + 0.178 098 181 177 344;
  • 35) 0.178 098 181 177 344 × 2 = 0 + 0.356 196 362 354 688;
  • 36) 0.356 196 362 354 688 × 2 = 0 + 0.712 392 724 709 376;
  • 37) 0.712 392 724 709 376 × 2 = 1 + 0.424 785 449 418 752;
  • 38) 0.424 785 449 418 752 × 2 = 0 + 0.849 570 898 837 504;
  • 39) 0.849 570 898 837 504 × 2 = 1 + 0.699 141 797 675 008;
  • 40) 0.699 141 797 675 008 × 2 = 1 + 0.398 283 595 350 016;
  • 41) 0.398 283 595 350 016 × 2 = 0 + 0.796 567 190 700 032;
  • 42) 0.796 567 190 700 032 × 2 = 1 + 0.593 134 381 400 064;
  • 43) 0.593 134 381 400 064 × 2 = 1 + 0.186 268 762 800 128;
  • 44) 0.186 268 762 800 128 × 2 = 0 + 0.372 537 525 600 256;
  • 45) 0.372 537 525 600 256 × 2 = 0 + 0.745 075 051 200 512;
  • 46) 0.745 075 051 200 512 × 2 = 1 + 0.490 150 102 401 024;
  • 47) 0.490 150 102 401 024 × 2 = 0 + 0.980 300 204 802 048;
  • 48) 0.980 300 204 802 048 × 2 = 1 + 0.960 600 409 604 096;
  • 49) 0.960 600 409 604 096 × 2 = 1 + 0.921 200 819 208 192;
  • 50) 0.921 200 819 208 192 × 2 = 1 + 0.842 401 638 416 384;
  • 51) 0.842 401 638 416 384 × 2 = 1 + 0.684 803 276 832 768;
  • 52) 0.684 803 276 832 768 × 2 = 1 + 0.369 606 553 665 536;
  • 53) 0.369 606 553 665 536 × 2 = 0 + 0.739 213 107 331 072;

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:


0.780 086 699 999 991(10) =


0.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0110 0101 1111 0(2)

5. Positive number before normalization:

33.780 086 699 999 991(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0110 0101 1111 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:


33.780 086 699 999 991(10) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0110 0101 1111 0(2) =


10 0001.1100 0111 1011 0011 1100 0011 0001 0000 1000 1011 0110 0101 1111 0(2) × 20 =


1.0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1011 0010 1111 10(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 1011 0010 1111 10


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 1011 0010 11 1110 =


0000 1110 0011 1101 1001 1110 0001 1000 1000 0100 0101 1011 0010


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 1011 0010


Decimal number 33.780 086 699 999 991 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 1011 0010


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