-0.033 343 988 072 56 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.033 343 988 072 56(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
-0.033 343 988 072 56(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:

|-0.033 343 988 072 56| = 0.033 343 988 072 56


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: 0.033 343 988 072 56.

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) 0.033 343 988 072 56 × 2 = 0 + 0.066 687 976 145 12;
  • 2) 0.066 687 976 145 12 × 2 = 0 + 0.133 375 952 290 24;
  • 3) 0.133 375 952 290 24 × 2 = 0 + 0.266 751 904 580 48;
  • 4) 0.266 751 904 580 48 × 2 = 0 + 0.533 503 809 160 96;
  • 5) 0.533 503 809 160 96 × 2 = 1 + 0.067 007 618 321 92;
  • 6) 0.067 007 618 321 92 × 2 = 0 + 0.134 015 236 643 84;
  • 7) 0.134 015 236 643 84 × 2 = 0 + 0.268 030 473 287 68;
  • 8) 0.268 030 473 287 68 × 2 = 0 + 0.536 060 946 575 36;
  • 9) 0.536 060 946 575 36 × 2 = 1 + 0.072 121 893 150 72;
  • 10) 0.072 121 893 150 72 × 2 = 0 + 0.144 243 786 301 44;
  • 11) 0.144 243 786 301 44 × 2 = 0 + 0.288 487 572 602 88;
  • 12) 0.288 487 572 602 88 × 2 = 0 + 0.576 975 145 205 76;
  • 13) 0.576 975 145 205 76 × 2 = 1 + 0.153 950 290 411 52;
  • 14) 0.153 950 290 411 52 × 2 = 0 + 0.307 900 580 823 04;
  • 15) 0.307 900 580 823 04 × 2 = 0 + 0.615 801 161 646 08;
  • 16) 0.615 801 161 646 08 × 2 = 1 + 0.231 602 323 292 16;
  • 17) 0.231 602 323 292 16 × 2 = 0 + 0.463 204 646 584 32;
  • 18) 0.463 204 646 584 32 × 2 = 0 + 0.926 409 293 168 64;
  • 19) 0.926 409 293 168 64 × 2 = 1 + 0.852 818 586 337 28;
  • 20) 0.852 818 586 337 28 × 2 = 1 + 0.705 637 172 674 56;
  • 21) 0.705 637 172 674 56 × 2 = 1 + 0.411 274 345 349 12;
  • 22) 0.411 274 345 349 12 × 2 = 0 + 0.822 548 690 698 24;
  • 23) 0.822 548 690 698 24 × 2 = 1 + 0.645 097 381 396 48;
  • 24) 0.645 097 381 396 48 × 2 = 1 + 0.290 194 762 792 96;
  • 25) 0.290 194 762 792 96 × 2 = 0 + 0.580 389 525 585 92;
  • 26) 0.580 389 525 585 92 × 2 = 1 + 0.160 779 051 171 84;
  • 27) 0.160 779 051 171 84 × 2 = 0 + 0.321 558 102 343 68;
  • 28) 0.321 558 102 343 68 × 2 = 0 + 0.643 116 204 687 36;
  • 29) 0.643 116 204 687 36 × 2 = 1 + 0.286 232 409 374 72;
  • 30) 0.286 232 409 374 72 × 2 = 0 + 0.572 464 818 749 44;
  • 31) 0.572 464 818 749 44 × 2 = 1 + 0.144 929 637 498 88;
  • 32) 0.144 929 637 498 88 × 2 = 0 + 0.289 859 274 997 76;
  • 33) 0.289 859 274 997 76 × 2 = 0 + 0.579 718 549 995 52;
  • 34) 0.579 718 549 995 52 × 2 = 1 + 0.159 437 099 991 04;
  • 35) 0.159 437 099 991 04 × 2 = 0 + 0.318 874 199 982 08;
  • 36) 0.318 874 199 982 08 × 2 = 0 + 0.637 748 399 964 16;
  • 37) 0.637 748 399 964 16 × 2 = 1 + 0.275 496 799 928 32;
  • 38) 0.275 496 799 928 32 × 2 = 0 + 0.550 993 599 856 64;
  • 39) 0.550 993 599 856 64 × 2 = 1 + 0.101 987 199 713 28;
  • 40) 0.101 987 199 713 28 × 2 = 0 + 0.203 974 399 426 56;
  • 41) 0.203 974 399 426 56 × 2 = 0 + 0.407 948 798 853 12;
  • 42) 0.407 948 798 853 12 × 2 = 0 + 0.815 897 597 706 24;
  • 43) 0.815 897 597 706 24 × 2 = 1 + 0.631 795 195 412 48;
  • 44) 0.631 795 195 412 48 × 2 = 1 + 0.263 590 390 824 96;
  • 45) 0.263 590 390 824 96 × 2 = 0 + 0.527 180 781 649 92;
  • 46) 0.527 180 781 649 92 × 2 = 1 + 0.054 361 563 299 84;
  • 47) 0.054 361 563 299 84 × 2 = 0 + 0.108 723 126 599 68;
  • 48) 0.108 723 126 599 68 × 2 = 0 + 0.217 446 253 199 36;
  • 49) 0.217 446 253 199 36 × 2 = 0 + 0.434 892 506 398 72;
  • 50) 0.434 892 506 398 72 × 2 = 0 + 0.869 785 012 797 44;
  • 51) 0.869 785 012 797 44 × 2 = 1 + 0.739 570 025 594 88;
  • 52) 0.739 570 025 594 88 × 2 = 1 + 0.479 140 051 189 76;
  • 53) 0.479 140 051 189 76 × 2 = 0 + 0.958 280 102 379 52;
  • 54) 0.958 280 102 379 52 × 2 = 1 + 0.916 560 204 759 04;
  • 55) 0.916 560 204 759 04 × 2 = 1 + 0.833 120 409 518 08;
  • 56) 0.833 120 409 518 08 × 2 = 1 + 0.666 240 819 036 16;
  • 57) 0.666 240 819 036 16 × 2 = 1 + 0.332 481 638 072 32;

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:


0.033 343 988 072 56(10) =


0.0000 1000 1000 1001 0011 1011 0100 1010 0100 1010 0011 0100 0011 0111 1(2)

6. Positive number before normalization:

0.033 343 988 072 56(10) =


0.0000 1000 1000 1001 0011 1011 0100 1010 0100 1010 0011 0100 0011 0111 1(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 5 positions to the right, so that only one non zero digit remains to the left of it:


0.033 343 988 072 56(10) =


0.0000 1000 1000 1001 0011 1011 0100 1010 0100 1010 0011 0100 0011 0111 1(2) =


0.0000 1000 1000 1001 0011 1011 0100 1010 0100 1010 0011 0100 0011 0111 1(2) × 20 =


1.0001 0001 0010 0111 0110 1001 0100 1001 0100 0110 1000 0110 1111(2) × 2-5


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): -5


Mantissa (not normalized):
1.0001 0001 0010 0111 0110 1001 0100 1001 0100 0110 1000 0110 1111


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


-5 + 2(11-1) - 1 =


(-5 + 1 023)(10) =


1 018(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;
  • 1 018 ÷ 2 = 509 + 0;
  • 509 ÷ 2 = 254 + 1;
  • 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) =


1018(10) =


011 1111 1010(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 0001 0010 0111 0110 1001 0100 1001 0100 0110 1000 0110 1111 =


0001 0001 0010 0111 0110 1001 0100 1001 0100 0110 1000 0110 1111


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 1010


Mantissa (52 bits) =
0001 0001 0010 0111 0110 1001 0100 1001 0100 0110 1000 0110 1111


Decimal number -0.033 343 988 072 56 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 1010 - 0001 0001 0010 0111 0110 1001 0100 1001 0100 0110 1000 0110 1111

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