-0.008 788 423 614 12 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.008 788 423 614 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
-0.008 788 423 614 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:

|-0.008 788 423 614 12| = 0.008 788 423 614 12


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: 0.008 788 423 614 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) 0.008 788 423 614 12 × 2 = 0 + 0.017 576 847 228 24;
  • 2) 0.017 576 847 228 24 × 2 = 0 + 0.035 153 694 456 48;
  • 3) 0.035 153 694 456 48 × 2 = 0 + 0.070 307 388 912 96;
  • 4) 0.070 307 388 912 96 × 2 = 0 + 0.140 614 777 825 92;
  • 5) 0.140 614 777 825 92 × 2 = 0 + 0.281 229 555 651 84;
  • 6) 0.281 229 555 651 84 × 2 = 0 + 0.562 459 111 303 68;
  • 7) 0.562 459 111 303 68 × 2 = 1 + 0.124 918 222 607 36;
  • 8) 0.124 918 222 607 36 × 2 = 0 + 0.249 836 445 214 72;
  • 9) 0.249 836 445 214 72 × 2 = 0 + 0.499 672 890 429 44;
  • 10) 0.499 672 890 429 44 × 2 = 0 + 0.999 345 780 858 88;
  • 11) 0.999 345 780 858 88 × 2 = 1 + 0.998 691 561 717 76;
  • 12) 0.998 691 561 717 76 × 2 = 1 + 0.997 383 123 435 52;
  • 13) 0.997 383 123 435 52 × 2 = 1 + 0.994 766 246 871 04;
  • 14) 0.994 766 246 871 04 × 2 = 1 + 0.989 532 493 742 08;
  • 15) 0.989 532 493 742 08 × 2 = 1 + 0.979 064 987 484 16;
  • 16) 0.979 064 987 484 16 × 2 = 1 + 0.958 129 974 968 32;
  • 17) 0.958 129 974 968 32 × 2 = 1 + 0.916 259 949 936 64;
  • 18) 0.916 259 949 936 64 × 2 = 1 + 0.832 519 899 873 28;
  • 19) 0.832 519 899 873 28 × 2 = 1 + 0.665 039 799 746 56;
  • 20) 0.665 039 799 746 56 × 2 = 1 + 0.330 079 599 493 12;
  • 21) 0.330 079 599 493 12 × 2 = 0 + 0.660 159 198 986 24;
  • 22) 0.660 159 198 986 24 × 2 = 1 + 0.320 318 397 972 48;
  • 23) 0.320 318 397 972 48 × 2 = 0 + 0.640 636 795 944 96;
  • 24) 0.640 636 795 944 96 × 2 = 1 + 0.281 273 591 889 92;
  • 25) 0.281 273 591 889 92 × 2 = 0 + 0.562 547 183 779 84;
  • 26) 0.562 547 183 779 84 × 2 = 1 + 0.125 094 367 559 68;
  • 27) 0.125 094 367 559 68 × 2 = 0 + 0.250 188 735 119 36;
  • 28) 0.250 188 735 119 36 × 2 = 0 + 0.500 377 470 238 72;
  • 29) 0.500 377 470 238 72 × 2 = 1 + 0.000 754 940 477 44;
  • 30) 0.000 754 940 477 44 × 2 = 0 + 0.001 509 880 954 88;
  • 31) 0.001 509 880 954 88 × 2 = 0 + 0.003 019 761 909 76;
  • 32) 0.003 019 761 909 76 × 2 = 0 + 0.006 039 523 819 52;
  • 33) 0.006 039 523 819 52 × 2 = 0 + 0.012 079 047 639 04;
  • 34) 0.012 079 047 639 04 × 2 = 0 + 0.024 158 095 278 08;
  • 35) 0.024 158 095 278 08 × 2 = 0 + 0.048 316 190 556 16;
  • 36) 0.048 316 190 556 16 × 2 = 0 + 0.096 632 381 112 32;
  • 37) 0.096 632 381 112 32 × 2 = 0 + 0.193 264 762 224 64;
  • 38) 0.193 264 762 224 64 × 2 = 0 + 0.386 529 524 449 28;
  • 39) 0.386 529 524 449 28 × 2 = 0 + 0.773 059 048 898 56;
  • 40) 0.773 059 048 898 56 × 2 = 1 + 0.546 118 097 797 12;
  • 41) 0.546 118 097 797 12 × 2 = 1 + 0.092 236 195 594 24;
  • 42) 0.092 236 195 594 24 × 2 = 0 + 0.184 472 391 188 48;
  • 43) 0.184 472 391 188 48 × 2 = 0 + 0.368 944 782 376 96;
  • 44) 0.368 944 782 376 96 × 2 = 0 + 0.737 889 564 753 92;
  • 45) 0.737 889 564 753 92 × 2 = 1 + 0.475 779 129 507 84;
  • 46) 0.475 779 129 507 84 × 2 = 0 + 0.951 558 259 015 68;
  • 47) 0.951 558 259 015 68 × 2 = 1 + 0.903 116 518 031 36;
  • 48) 0.903 116 518 031 36 × 2 = 1 + 0.806 233 036 062 72;
  • 49) 0.806 233 036 062 72 × 2 = 1 + 0.612 466 072 125 44;
  • 50) 0.612 466 072 125 44 × 2 = 1 + 0.224 932 144 250 88;
  • 51) 0.224 932 144 250 88 × 2 = 0 + 0.449 864 288 501 76;
  • 52) 0.449 864 288 501 76 × 2 = 0 + 0.899 728 577 003 52;
  • 53) 0.899 728 577 003 52 × 2 = 1 + 0.799 457 154 007 04;
  • 54) 0.799 457 154 007 04 × 2 = 1 + 0.598 914 308 014 08;
  • 55) 0.598 914 308 014 08 × 2 = 1 + 0.197 828 616 028 16;
  • 56) 0.197 828 616 028 16 × 2 = 0 + 0.395 657 232 056 32;
  • 57) 0.395 657 232 056 32 × 2 = 0 + 0.791 314 464 112 64;
  • 58) 0.791 314 464 112 64 × 2 = 1 + 0.582 628 928 225 28;
  • 59) 0.582 628 928 225 28 × 2 = 1 + 0.165 257 856 450 56;

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:


0.008 788 423 614 12(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0001 1000 1011 1100 1110 011(2)

6. Positive number before normalization:

0.008 788 423 614 12(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0001 1000 1011 1100 1110 011(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:


0.008 788 423 614 12(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0001 1000 1011 1100 1110 011(2) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0001 1000 1011 1100 1110 011(2) × 20 =


1.0001 1111 1111 1010 1010 0100 0000 0000 1100 0101 1110 0111 0011(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 0000 1100 0101 1110 0111 0011


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 0000 1100 0101 1110 0111 0011 =


0001 1111 1111 1010 1010 0100 0000 0000 1100 0101 1110 0111 0011


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 0000 1100 0101 1110 0111 0011


Decimal number -0.008 788 423 614 12 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1000 - 0001 1111 1111 1010 1010 0100 0000 0000 1100 0101 1110 0111 0011


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