777.789 999 999 999 602 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 777.789 999 999 999 602(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
777.789 999 999 999 602(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: 777.
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;
  • 777 ÷ 2 = 388 + 1;
  • 388 ÷ 2 = 194 + 0;
  • 194 ÷ 2 = 97 + 0;
  • 97 ÷ 2 = 48 + 1;
  • 48 ÷ 2 = 24 + 0;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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.

777(10) =


11 0000 1001(2)


3. Convert to binary (base 2) the fractional part: 0.789 999 999 999 602.

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) 0.789 999 999 999 602 × 2 = 1 + 0.579 999 999 999 204;
  • 2) 0.579 999 999 999 204 × 2 = 1 + 0.159 999 999 998 408;
  • 3) 0.159 999 999 998 408 × 2 = 0 + 0.319 999 999 996 816;
  • 4) 0.319 999 999 996 816 × 2 = 0 + 0.639 999 999 993 632;
  • 5) 0.639 999 999 993 632 × 2 = 1 + 0.279 999 999 987 264;
  • 6) 0.279 999 999 987 264 × 2 = 0 + 0.559 999 999 974 528;
  • 7) 0.559 999 999 974 528 × 2 = 1 + 0.119 999 999 949 056;
  • 8) 0.119 999 999 949 056 × 2 = 0 + 0.239 999 999 898 112;
  • 9) 0.239 999 999 898 112 × 2 = 0 + 0.479 999 999 796 224;
  • 10) 0.479 999 999 796 224 × 2 = 0 + 0.959 999 999 592 448;
  • 11) 0.959 999 999 592 448 × 2 = 1 + 0.919 999 999 184 896;
  • 12) 0.919 999 999 184 896 × 2 = 1 + 0.839 999 998 369 792;
  • 13) 0.839 999 998 369 792 × 2 = 1 + 0.679 999 996 739 584;
  • 14) 0.679 999 996 739 584 × 2 = 1 + 0.359 999 993 479 168;
  • 15) 0.359 999 993 479 168 × 2 = 0 + 0.719 999 986 958 336;
  • 16) 0.719 999 986 958 336 × 2 = 1 + 0.439 999 973 916 672;
  • 17) 0.439 999 973 916 672 × 2 = 0 + 0.879 999 947 833 344;
  • 18) 0.879 999 947 833 344 × 2 = 1 + 0.759 999 895 666 688;
  • 19) 0.759 999 895 666 688 × 2 = 1 + 0.519 999 791 333 376;
  • 20) 0.519 999 791 333 376 × 2 = 1 + 0.039 999 582 666 752;
  • 21) 0.039 999 582 666 752 × 2 = 0 + 0.079 999 165 333 504;
  • 22) 0.079 999 165 333 504 × 2 = 0 + 0.159 998 330 667 008;
  • 23) 0.159 998 330 667 008 × 2 = 0 + 0.319 996 661 334 016;
  • 24) 0.319 996 661 334 016 × 2 = 0 + 0.639 993 322 668 032;
  • 25) 0.639 993 322 668 032 × 2 = 1 + 0.279 986 645 336 064;
  • 26) 0.279 986 645 336 064 × 2 = 0 + 0.559 973 290 672 128;
  • 27) 0.559 973 290 672 128 × 2 = 1 + 0.119 946 581 344 256;
  • 28) 0.119 946 581 344 256 × 2 = 0 + 0.239 893 162 688 512;
  • 29) 0.239 893 162 688 512 × 2 = 0 + 0.479 786 325 377 024;
  • 30) 0.479 786 325 377 024 × 2 = 0 + 0.959 572 650 754 048;
  • 31) 0.959 572 650 754 048 × 2 = 1 + 0.919 145 301 508 096;
  • 32) 0.919 145 301 508 096 × 2 = 1 + 0.838 290 603 016 192;
  • 33) 0.838 290 603 016 192 × 2 = 1 + 0.676 581 206 032 384;
  • 34) 0.676 581 206 032 384 × 2 = 1 + 0.353 162 412 064 768;
  • 35) 0.353 162 412 064 768 × 2 = 0 + 0.706 324 824 129 536;
  • 36) 0.706 324 824 129 536 × 2 = 1 + 0.412 649 648 259 072;
  • 37) 0.412 649 648 259 072 × 2 = 0 + 0.825 299 296 518 144;
  • 38) 0.825 299 296 518 144 × 2 = 1 + 0.650 598 593 036 288;
  • 39) 0.650 598 593 036 288 × 2 = 1 + 0.301 197 186 072 576;
  • 40) 0.301 197 186 072 576 × 2 = 0 + 0.602 394 372 145 152;
  • 41) 0.602 394 372 145 152 × 2 = 1 + 0.204 788 744 290 304;
  • 42) 0.204 788 744 290 304 × 2 = 0 + 0.409 577 488 580 608;
  • 43) 0.409 577 488 580 608 × 2 = 0 + 0.819 154 977 161 216;
  • 44) 0.819 154 977 161 216 × 2 = 1 + 0.638 309 954 322 432;
  • 45) 0.638 309 954 322 432 × 2 = 1 + 0.276 619 908 644 864;
  • 46) 0.276 619 908 644 864 × 2 = 0 + 0.553 239 817 289 728;
  • 47) 0.553 239 817 289 728 × 2 = 1 + 0.106 479 634 579 456;
  • 48) 0.106 479 634 579 456 × 2 = 0 + 0.212 959 269 158 912;
  • 49) 0.212 959 269 158 912 × 2 = 0 + 0.425 918 538 317 824;
  • 50) 0.425 918 538 317 824 × 2 = 0 + 0.851 837 076 635 648;
  • 51) 0.851 837 076 635 648 × 2 = 1 + 0.703 674 153 271 296;
  • 52) 0.703 674 153 271 296 × 2 = 1 + 0.407 348 306 542 592;
  • 53) 0.407 348 306 542 592 × 2 = 0 + 0.814 696 613 085 184;

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:


0.789 999 999 999 602(10) =


0.1100 1010 0011 1101 0111 0000 1010 0011 1101 0110 1001 1010 0011 0(2)

5. Positive number before normalization:

777.789 999 999 999 602(10) =


11 0000 1001.1100 1010 0011 1101 0111 0000 1010 0011 1101 0110 1001 1010 0011 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 9 positions to the left, so that only one non zero digit remains to the left of it:


777.789 999 999 999 602(10) =


11 0000 1001.1100 1010 0011 1101 0111 0000 1010 0011 1101 0110 1001 1010 0011 0(2) =


11 0000 1001.1100 1010 0011 1101 0111 0000 1010 0011 1101 0110 1001 1010 0011 0(2) × 20 =


1.1000 0100 1110 0101 0001 1110 1011 1000 0101 0001 1110 1011 0100 1101 0001 10(2) × 29


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): 9


Mantissa (not normalized):
1.1000 0100 1110 0101 0001 1110 1011 1000 0101 0001 1110 1011 0100 1101 0001 10


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


9 + 2(11-1) - 1 =


(9 + 1 023)(10) =


1 032(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;
  • 1 032 ÷ 2 = 516 + 0;
  • 516 ÷ 2 = 258 + 0;
  • 258 ÷ 2 = 129 + 0;
  • 129 ÷ 2 = 64 + 1;
  • 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) =


1032(10) =


100 0000 1000(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. 1000 0100 1110 0101 0001 1110 1011 1000 0101 0001 1110 1011 0100 11 0100 0110 =


1000 0100 1110 0101 0001 1110 1011 1000 0101 0001 1110 1011 0100


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 1000


Mantissa (52 bits) =
1000 0100 1110 0101 0001 1110 1011 1000 0101 0001 1110 1011 0100


Decimal number 777.789 999 999 999 602 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1000 - 1000 0100 1110 0101 0001 1110 1011 1000 0101 0001 1110 1011 0100


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