-7.769 489 691 002 12 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -7.769 489 691 002 12(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
-7.769 489 691 002 12(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. Start with the positive version of the number:

|-7.769 489 691 002 12| = 7.769 489 691 002 12


2. First, convert to binary (in base 2) the integer part: 7.
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;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

3. 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.

7(10) =


111(2)


4. Convert to binary (base 2) the fractional part: 0.769 489 691 002 12.

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) 0.769 489 691 002 12 × 2 = 1 + 0.538 979 382 004 24;
  • 2) 0.538 979 382 004 24 × 2 = 1 + 0.077 958 764 008 48;
  • 3) 0.077 958 764 008 48 × 2 = 0 + 0.155 917 528 016 96;
  • 4) 0.155 917 528 016 96 × 2 = 0 + 0.311 835 056 033 92;
  • 5) 0.311 835 056 033 92 × 2 = 0 + 0.623 670 112 067 84;
  • 6) 0.623 670 112 067 84 × 2 = 1 + 0.247 340 224 135 68;
  • 7) 0.247 340 224 135 68 × 2 = 0 + 0.494 680 448 271 36;
  • 8) 0.494 680 448 271 36 × 2 = 0 + 0.989 360 896 542 72;
  • 9) 0.989 360 896 542 72 × 2 = 1 + 0.978 721 793 085 44;
  • 10) 0.978 721 793 085 44 × 2 = 1 + 0.957 443 586 170 88;
  • 11) 0.957 443 586 170 88 × 2 = 1 + 0.914 887 172 341 76;
  • 12) 0.914 887 172 341 76 × 2 = 1 + 0.829 774 344 683 52;
  • 13) 0.829 774 344 683 52 × 2 = 1 + 0.659 548 689 367 04;
  • 14) 0.659 548 689 367 04 × 2 = 1 + 0.319 097 378 734 08;
  • 15) 0.319 097 378 734 08 × 2 = 0 + 0.638 194 757 468 16;
  • 16) 0.638 194 757 468 16 × 2 = 1 + 0.276 389 514 936 32;
  • 17) 0.276 389 514 936 32 × 2 = 0 + 0.552 779 029 872 64;
  • 18) 0.552 779 029 872 64 × 2 = 1 + 0.105 558 059 745 28;
  • 19) 0.105 558 059 745 28 × 2 = 0 + 0.211 116 119 490 56;
  • 20) 0.211 116 119 490 56 × 2 = 0 + 0.422 232 238 981 12;
  • 21) 0.422 232 238 981 12 × 2 = 0 + 0.844 464 477 962 24;
  • 22) 0.844 464 477 962 24 × 2 = 1 + 0.688 928 955 924 48;
  • 23) 0.688 928 955 924 48 × 2 = 1 + 0.377 857 911 848 96;
  • 24) 0.377 857 911 848 96 × 2 = 0 + 0.755 715 823 697 92;
  • 25) 0.755 715 823 697 92 × 2 = 1 + 0.511 431 647 395 84;
  • 26) 0.511 431 647 395 84 × 2 = 1 + 0.022 863 294 791 68;
  • 27) 0.022 863 294 791 68 × 2 = 0 + 0.045 726 589 583 36;
  • 28) 0.045 726 589 583 36 × 2 = 0 + 0.091 453 179 166 72;
  • 29) 0.091 453 179 166 72 × 2 = 0 + 0.182 906 358 333 44;
  • 30) 0.182 906 358 333 44 × 2 = 0 + 0.365 812 716 666 88;
  • 31) 0.365 812 716 666 88 × 2 = 0 + 0.731 625 433 333 76;
  • 32) 0.731 625 433 333 76 × 2 = 1 + 0.463 250 866 667 52;
  • 33) 0.463 250 866 667 52 × 2 = 0 + 0.926 501 733 335 04;
  • 34) 0.926 501 733 335 04 × 2 = 1 + 0.853 003 466 670 08;
  • 35) 0.853 003 466 670 08 × 2 = 1 + 0.706 006 933 340 16;
  • 36) 0.706 006 933 340 16 × 2 = 1 + 0.412 013 866 680 32;
  • 37) 0.412 013 866 680 32 × 2 = 0 + 0.824 027 733 360 64;
  • 38) 0.824 027 733 360 64 × 2 = 1 + 0.648 055 466 721 28;
  • 39) 0.648 055 466 721 28 × 2 = 1 + 0.296 110 933 442 56;
  • 40) 0.296 110 933 442 56 × 2 = 0 + 0.592 221 866 885 12;
  • 41) 0.592 221 866 885 12 × 2 = 1 + 0.184 443 733 770 24;
  • 42) 0.184 443 733 770 24 × 2 = 0 + 0.368 887 467 540 48;
  • 43) 0.368 887 467 540 48 × 2 = 0 + 0.737 774 935 080 96;
  • 44) 0.737 774 935 080 96 × 2 = 1 + 0.475 549 870 161 92;
  • 45) 0.475 549 870 161 92 × 2 = 0 + 0.951 099 740 323 84;
  • 46) 0.951 099 740 323 84 × 2 = 1 + 0.902 199 480 647 68;
  • 47) 0.902 199 480 647 68 × 2 = 1 + 0.804 398 961 295 36;
  • 48) 0.804 398 961 295 36 × 2 = 1 + 0.608 797 922 590 72;
  • 49) 0.608 797 922 590 72 × 2 = 1 + 0.217 595 845 181 44;
  • 50) 0.217 595 845 181 44 × 2 = 0 + 0.435 191 690 362 88;
  • 51) 0.435 191 690 362 88 × 2 = 0 + 0.870 383 380 725 76;
  • 52) 0.870 383 380 725 76 × 2 = 1 + 0.740 766 761 451 52;
  • 53) 0.740 766 761 451 52 × 2 = 1 + 0.481 533 522 903 04;

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).


5. 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:


0.769 489 691 002 12(10) =


0.1100 0100 1111 1101 0100 0110 1100 0001 0111 0110 1001 0111 1001 1(2)

6. Positive number before normalization:

7.769 489 691 002 12(10) =


111.1100 0100 1111 1101 0100 0110 1100 0001 0111 0110 1001 0111 1001 1(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 2 positions to the left, so that only one non zero digit remains to the left of it:


7.769 489 691 002 12(10) =


111.1100 0100 1111 1101 0100 0110 1100 0001 0111 0110 1001 0111 1001 1(2) =


111.1100 0100 1111 1101 0100 0110 1100 0001 0111 0110 1001 0111 1001 1(2) × 20 =


1.1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1010 0101 1110 011(2) × 22


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): 2


Mantissa (not normalized):
1.1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1010 0101 1110 011


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


2 + 2(11-1) - 1 =


(2 + 1 023)(10) =


1 025(10)


10. 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;
  • 1 025 ÷ 2 = 512 + 1;
  • 512 ÷ 2 = 256 + 0;
  • 256 ÷ 2 = 128 + 0;
  • 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;

11. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1025(10) =


100 0000 0001(2)


12. 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. 1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1010 0101 1110 011 =


1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1010 0101 1110


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
100 0000 0001


Mantissa (52 bits) =
1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1010 0101 1110


Decimal number -7.769 489 691 002 12 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0001 - 1111 0001 0011 1111 0101 0001 1011 0000 0101 1101 1010 0101 1110

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