-0.008 788 423 615 74 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.008 788 423 615 74(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
-0.008 788 423 615 74(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:

|-0.008 788 423 615 74| = 0.008 788 423 615 74


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

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.

0(10) =


0(2)


4. Convert to binary (base 2) the fractional part: 0.008 788 423 615 74.

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) 0.008 788 423 615 74 × 2 = 0 + 0.017 576 847 231 48;
  • 2) 0.017 576 847 231 48 × 2 = 0 + 0.035 153 694 462 96;
  • 3) 0.035 153 694 462 96 × 2 = 0 + 0.070 307 388 925 92;
  • 4) 0.070 307 388 925 92 × 2 = 0 + 0.140 614 777 851 84;
  • 5) 0.140 614 777 851 84 × 2 = 0 + 0.281 229 555 703 68;
  • 6) 0.281 229 555 703 68 × 2 = 0 + 0.562 459 111 407 36;
  • 7) 0.562 459 111 407 36 × 2 = 1 + 0.124 918 222 814 72;
  • 8) 0.124 918 222 814 72 × 2 = 0 + 0.249 836 445 629 44;
  • 9) 0.249 836 445 629 44 × 2 = 0 + 0.499 672 891 258 88;
  • 10) 0.499 672 891 258 88 × 2 = 0 + 0.999 345 782 517 76;
  • 11) 0.999 345 782 517 76 × 2 = 1 + 0.998 691 565 035 52;
  • 12) 0.998 691 565 035 52 × 2 = 1 + 0.997 383 130 071 04;
  • 13) 0.997 383 130 071 04 × 2 = 1 + 0.994 766 260 142 08;
  • 14) 0.994 766 260 142 08 × 2 = 1 + 0.989 532 520 284 16;
  • 15) 0.989 532 520 284 16 × 2 = 1 + 0.979 065 040 568 32;
  • 16) 0.979 065 040 568 32 × 2 = 1 + 0.958 130 081 136 64;
  • 17) 0.958 130 081 136 64 × 2 = 1 + 0.916 260 162 273 28;
  • 18) 0.916 260 162 273 28 × 2 = 1 + 0.832 520 324 546 56;
  • 19) 0.832 520 324 546 56 × 2 = 1 + 0.665 040 649 093 12;
  • 20) 0.665 040 649 093 12 × 2 = 1 + 0.330 081 298 186 24;
  • 21) 0.330 081 298 186 24 × 2 = 0 + 0.660 162 596 372 48;
  • 22) 0.660 162 596 372 48 × 2 = 1 + 0.320 325 192 744 96;
  • 23) 0.320 325 192 744 96 × 2 = 0 + 0.640 650 385 489 92;
  • 24) 0.640 650 385 489 92 × 2 = 1 + 0.281 300 770 979 84;
  • 25) 0.281 300 770 979 84 × 2 = 0 + 0.562 601 541 959 68;
  • 26) 0.562 601 541 959 68 × 2 = 1 + 0.125 203 083 919 36;
  • 27) 0.125 203 083 919 36 × 2 = 0 + 0.250 406 167 838 72;
  • 28) 0.250 406 167 838 72 × 2 = 0 + 0.500 812 335 677 44;
  • 29) 0.500 812 335 677 44 × 2 = 1 + 0.001 624 671 354 88;
  • 30) 0.001 624 671 354 88 × 2 = 0 + 0.003 249 342 709 76;
  • 31) 0.003 249 342 709 76 × 2 = 0 + 0.006 498 685 419 52;
  • 32) 0.006 498 685 419 52 × 2 = 0 + 0.012 997 370 839 04;
  • 33) 0.012 997 370 839 04 × 2 = 0 + 0.025 994 741 678 08;
  • 34) 0.025 994 741 678 08 × 2 = 0 + 0.051 989 483 356 16;
  • 35) 0.051 989 483 356 16 × 2 = 0 + 0.103 978 966 712 32;
  • 36) 0.103 978 966 712 32 × 2 = 0 + 0.207 957 933 424 64;
  • 37) 0.207 957 933 424 64 × 2 = 0 + 0.415 915 866 849 28;
  • 38) 0.415 915 866 849 28 × 2 = 0 + 0.831 831 733 698 56;
  • 39) 0.831 831 733 698 56 × 2 = 1 + 0.663 663 467 397 12;
  • 40) 0.663 663 467 397 12 × 2 = 1 + 0.327 326 934 794 24;
  • 41) 0.327 326 934 794 24 × 2 = 0 + 0.654 653 869 588 48;
  • 42) 0.654 653 869 588 48 × 2 = 1 + 0.309 307 739 176 96;
  • 43) 0.309 307 739 176 96 × 2 = 0 + 0.618 615 478 353 92;
  • 44) 0.618 615 478 353 92 × 2 = 1 + 0.237 230 956 707 84;
  • 45) 0.237 230 956 707 84 × 2 = 0 + 0.474 461 913 415 68;
  • 46) 0.474 461 913 415 68 × 2 = 0 + 0.948 923 826 831 36;
  • 47) 0.948 923 826 831 36 × 2 = 1 + 0.897 847 653 662 72;
  • 48) 0.897 847 653 662 72 × 2 = 1 + 0.795 695 307 325 44;
  • 49) 0.795 695 307 325 44 × 2 = 1 + 0.591 390 614 650 88;
  • 50) 0.591 390 614 650 88 × 2 = 1 + 0.182 781 229 301 76;
  • 51) 0.182 781 229 301 76 × 2 = 0 + 0.365 562 458 603 52;
  • 52) 0.365 562 458 603 52 × 2 = 0 + 0.731 124 917 207 04;
  • 53) 0.731 124 917 207 04 × 2 = 1 + 0.462 249 834 414 08;
  • 54) 0.462 249 834 414 08 × 2 = 0 + 0.924 499 668 828 16;
  • 55) 0.924 499 668 828 16 × 2 = 1 + 0.848 999 337 656 32;
  • 56) 0.848 999 337 656 32 × 2 = 1 + 0.697 998 675 312 64;
  • 57) 0.697 998 675 312 64 × 2 = 1 + 0.395 997 350 625 28;
  • 58) 0.395 997 350 625 28 × 2 = 0 + 0.791 994 701 250 56;
  • 59) 0.791 994 701 250 56 × 2 = 1 + 0.583 989 402 501 12;

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:


0.008 788 423 615 74(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0011 0101 0011 1100 1011 101(2)

6. Positive number before normalization:

0.008 788 423 615 74(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0011 0101 0011 1100 1011 101(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 7 positions to the right, so that only one non zero digit remains to the left of it:


0.008 788 423 615 74(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0011 0101 0011 1100 1011 101(2) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0011 0101 0011 1100 1011 101(2) × 20 =


1.0001 1111 1111 1010 1010 0100 0000 0001 1010 1001 1110 0101 1101(2) × 2-7


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): -7


Mantissa (not normalized):
1.0001 1111 1111 1010 1010 0100 0000 0001 1010 1001 1110 0101 1101


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-7 + 2(11-1) - 1 =


(-7 + 1 023)(10) =


1 016(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;
  • 1 016 ÷ 2 = 508 + 0;
  • 508 ÷ 2 = 254 + 0;
  • 254 ÷ 2 = 127 + 0;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1016(10) =


011 1111 1000(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, only if necessary (not the case here).


Mantissa (normalized) =


1. 0001 1111 1111 1010 1010 0100 0000 0001 1010 1001 1110 0101 1101 =


0001 1111 1111 1010 1010 0100 0000 0001 1010 1001 1110 0101 1101


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) =
011 1111 1000


Mantissa (52 bits) =
0001 1111 1111 1010 1010 0100 0000 0001 1010 1001 1110 0101 1101


Decimal number -0.008 788 423 615 74 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1000 - 0001 1111 1111 1010 1010 0100 0000 0001 1010 1001 1110 0101 1101


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