-0.008 788 423 612 72 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.008 788 423 612 72(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
-0.008 788 423 612 72(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:

|-0.008 788 423 612 72| = 0.008 788 423 612 72


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: 0.008 788 423 612 72.

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) 0.008 788 423 612 72 × 2 = 0 + 0.017 576 847 225 44;
  • 2) 0.017 576 847 225 44 × 2 = 0 + 0.035 153 694 450 88;
  • 3) 0.035 153 694 450 88 × 2 = 0 + 0.070 307 388 901 76;
  • 4) 0.070 307 388 901 76 × 2 = 0 + 0.140 614 777 803 52;
  • 5) 0.140 614 777 803 52 × 2 = 0 + 0.281 229 555 607 04;
  • 6) 0.281 229 555 607 04 × 2 = 0 + 0.562 459 111 214 08;
  • 7) 0.562 459 111 214 08 × 2 = 1 + 0.124 918 222 428 16;
  • 8) 0.124 918 222 428 16 × 2 = 0 + 0.249 836 444 856 32;
  • 9) 0.249 836 444 856 32 × 2 = 0 + 0.499 672 889 712 64;
  • 10) 0.499 672 889 712 64 × 2 = 0 + 0.999 345 779 425 28;
  • 11) 0.999 345 779 425 28 × 2 = 1 + 0.998 691 558 850 56;
  • 12) 0.998 691 558 850 56 × 2 = 1 + 0.997 383 117 701 12;
  • 13) 0.997 383 117 701 12 × 2 = 1 + 0.994 766 235 402 24;
  • 14) 0.994 766 235 402 24 × 2 = 1 + 0.989 532 470 804 48;
  • 15) 0.989 532 470 804 48 × 2 = 1 + 0.979 064 941 608 96;
  • 16) 0.979 064 941 608 96 × 2 = 1 + 0.958 129 883 217 92;
  • 17) 0.958 129 883 217 92 × 2 = 1 + 0.916 259 766 435 84;
  • 18) 0.916 259 766 435 84 × 2 = 1 + 0.832 519 532 871 68;
  • 19) 0.832 519 532 871 68 × 2 = 1 + 0.665 039 065 743 36;
  • 20) 0.665 039 065 743 36 × 2 = 1 + 0.330 078 131 486 72;
  • 21) 0.330 078 131 486 72 × 2 = 0 + 0.660 156 262 973 44;
  • 22) 0.660 156 262 973 44 × 2 = 1 + 0.320 312 525 946 88;
  • 23) 0.320 312 525 946 88 × 2 = 0 + 0.640 625 051 893 76;
  • 24) 0.640 625 051 893 76 × 2 = 1 + 0.281 250 103 787 52;
  • 25) 0.281 250 103 787 52 × 2 = 0 + 0.562 500 207 575 04;
  • 26) 0.562 500 207 575 04 × 2 = 1 + 0.125 000 415 150 08;
  • 27) 0.125 000 415 150 08 × 2 = 0 + 0.250 000 830 300 16;
  • 28) 0.250 000 830 300 16 × 2 = 0 + 0.500 001 660 600 32;
  • 29) 0.500 001 660 600 32 × 2 = 1 + 0.000 003 321 200 64;
  • 30) 0.000 003 321 200 64 × 2 = 0 + 0.000 006 642 401 28;
  • 31) 0.000 006 642 401 28 × 2 = 0 + 0.000 013 284 802 56;
  • 32) 0.000 013 284 802 56 × 2 = 0 + 0.000 026 569 605 12;
  • 33) 0.000 026 569 605 12 × 2 = 0 + 0.000 053 139 210 24;
  • 34) 0.000 053 139 210 24 × 2 = 0 + 0.000 106 278 420 48;
  • 35) 0.000 106 278 420 48 × 2 = 0 + 0.000 212 556 840 96;
  • 36) 0.000 212 556 840 96 × 2 = 0 + 0.000 425 113 681 92;
  • 37) 0.000 425 113 681 92 × 2 = 0 + 0.000 850 227 363 84;
  • 38) 0.000 850 227 363 84 × 2 = 0 + 0.001 700 454 727 68;
  • 39) 0.001 700 454 727 68 × 2 = 0 + 0.003 400 909 455 36;
  • 40) 0.003 400 909 455 36 × 2 = 0 + 0.006 801 818 910 72;
  • 41) 0.006 801 818 910 72 × 2 = 0 + 0.013 603 637 821 44;
  • 42) 0.013 603 637 821 44 × 2 = 0 + 0.027 207 275 642 88;
  • 43) 0.027 207 275 642 88 × 2 = 0 + 0.054 414 551 285 76;
  • 44) 0.054 414 551 285 76 × 2 = 0 + 0.108 829 102 571 52;
  • 45) 0.108 829 102 571 52 × 2 = 0 + 0.217 658 205 143 04;
  • 46) 0.217 658 205 143 04 × 2 = 0 + 0.435 316 410 286 08;
  • 47) 0.435 316 410 286 08 × 2 = 0 + 0.870 632 820 572 16;
  • 48) 0.870 632 820 572 16 × 2 = 1 + 0.741 265 641 144 32;
  • 49) 0.741 265 641 144 32 × 2 = 1 + 0.482 531 282 288 64;
  • 50) 0.482 531 282 288 64 × 2 = 0 + 0.965 062 564 577 28;
  • 51) 0.965 062 564 577 28 × 2 = 1 + 0.930 125 129 154 56;
  • 52) 0.930 125 129 154 56 × 2 = 1 + 0.860 250 258 309 12;
  • 53) 0.860 250 258 309 12 × 2 = 1 + 0.720 500 516 618 24;
  • 54) 0.720 500 516 618 24 × 2 = 1 + 0.441 001 033 236 48;
  • 55) 0.441 001 033 236 48 × 2 = 0 + 0.882 002 066 472 96;
  • 56) 0.882 002 066 472 96 × 2 = 1 + 0.764 004 132 945 92;
  • 57) 0.764 004 132 945 92 × 2 = 1 + 0.528 008 265 891 84;
  • 58) 0.528 008 265 891 84 × 2 = 1 + 0.056 016 531 783 68;
  • 59) 0.056 016 531 783 68 × 2 = 0 + 0.112 033 063 567 36;

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:


0.008 788 423 612 72(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0000 0000 0001 1011 1101 110(2)

6. Positive number before normalization:

0.008 788 423 612 72(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0000 0000 0001 1011 1101 110(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:


0.008 788 423 612 72(10) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0000 0000 0001 1011 1101 110(2) =


0.0000 0010 0011 1111 1111 0101 0100 1000 0000 0000 0000 0001 1011 1101 110(2) × 20 =


1.0001 1111 1111 1010 1010 0100 0000 0000 0000 0000 1101 1110 1110(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 0000 0000 1101 1110 1110


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 0000 0000 1101 1110 1110 =


0001 1111 1111 1010 1010 0100 0000 0000 0000 0000 1101 1110 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) =
011 1111 1000


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


Decimal number -0.008 788 423 612 72 converted to 64 bit double precision IEEE 754 binary floating point representation:

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