-6.259 853 613 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -6.259 853 613(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
-6.259 853 613(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:

|-6.259 853 613| = 6.259 853 613


2. First, convert to binary (in base 2) the integer part: 6.
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;
  • 6 ÷ 2 = 3 + 0;
  • 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.

6(10) =


110(2)


4. Convert to binary (base 2) the fractional part: 0.259 853 613.

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) 0.259 853 613 × 2 = 0 + 0.519 707 226;
  • 2) 0.519 707 226 × 2 = 1 + 0.039 414 452;
  • 3) 0.039 414 452 × 2 = 0 + 0.078 828 904;
  • 4) 0.078 828 904 × 2 = 0 + 0.157 657 808;
  • 5) 0.157 657 808 × 2 = 0 + 0.315 315 616;
  • 6) 0.315 315 616 × 2 = 0 + 0.630 631 232;
  • 7) 0.630 631 232 × 2 = 1 + 0.261 262 464;
  • 8) 0.261 262 464 × 2 = 0 + 0.522 524 928;
  • 9) 0.522 524 928 × 2 = 1 + 0.045 049 856;
  • 10) 0.045 049 856 × 2 = 0 + 0.090 099 712;
  • 11) 0.090 099 712 × 2 = 0 + 0.180 199 424;
  • 12) 0.180 199 424 × 2 = 0 + 0.360 398 848;
  • 13) 0.360 398 848 × 2 = 0 + 0.720 797 696;
  • 14) 0.720 797 696 × 2 = 1 + 0.441 595 392;
  • 15) 0.441 595 392 × 2 = 0 + 0.883 190 784;
  • 16) 0.883 190 784 × 2 = 1 + 0.766 381 568;
  • 17) 0.766 381 568 × 2 = 1 + 0.532 763 136;
  • 18) 0.532 763 136 × 2 = 1 + 0.065 526 272;
  • 19) 0.065 526 272 × 2 = 0 + 0.131 052 544;
  • 20) 0.131 052 544 × 2 = 0 + 0.262 105 088;
  • 21) 0.262 105 088 × 2 = 0 + 0.524 210 176;
  • 22) 0.524 210 176 × 2 = 1 + 0.048 420 352;
  • 23) 0.048 420 352 × 2 = 0 + 0.096 840 704;
  • 24) 0.096 840 704 × 2 = 0 + 0.193 681 408;
  • 25) 0.193 681 408 × 2 = 0 + 0.387 362 816;
  • 26) 0.387 362 816 × 2 = 0 + 0.774 725 632;
  • 27) 0.774 725 632 × 2 = 1 + 0.549 451 264;
  • 28) 0.549 451 264 × 2 = 1 + 0.098 902 528;
  • 29) 0.098 902 528 × 2 = 0 + 0.197 805 056;
  • 30) 0.197 805 056 × 2 = 0 + 0.395 610 112;
  • 31) 0.395 610 112 × 2 = 0 + 0.791 220 224;
  • 32) 0.791 220 224 × 2 = 1 + 0.582 440 448;
  • 33) 0.582 440 448 × 2 = 1 + 0.164 880 896;
  • 34) 0.164 880 896 × 2 = 0 + 0.329 761 792;
  • 35) 0.329 761 792 × 2 = 0 + 0.659 523 584;
  • 36) 0.659 523 584 × 2 = 1 + 0.319 047 168;
  • 37) 0.319 047 168 × 2 = 0 + 0.638 094 336;
  • 38) 0.638 094 336 × 2 = 1 + 0.276 188 672;
  • 39) 0.276 188 672 × 2 = 0 + 0.552 377 344;
  • 40) 0.552 377 344 × 2 = 1 + 0.104 754 688;
  • 41) 0.104 754 688 × 2 = 0 + 0.209 509 376;
  • 42) 0.209 509 376 × 2 = 0 + 0.419 018 752;
  • 43) 0.419 018 752 × 2 = 0 + 0.838 037 504;
  • 44) 0.838 037 504 × 2 = 1 + 0.676 075 008;
  • 45) 0.676 075 008 × 2 = 1 + 0.352 150 016;
  • 46) 0.352 150 016 × 2 = 0 + 0.704 300 032;
  • 47) 0.704 300 032 × 2 = 1 + 0.408 600 064;
  • 48) 0.408 600 064 × 2 = 0 + 0.817 200 128;
  • 49) 0.817 200 128 × 2 = 1 + 0.634 400 256;
  • 50) 0.634 400 256 × 2 = 1 + 0.268 800 512;
  • 51) 0.268 800 512 × 2 = 0 + 0.537 601 024;
  • 52) 0.537 601 024 × 2 = 1 + 0.075 202 048;
  • 53) 0.075 202 048 × 2 = 0 + 0.150 404 096;

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:


0.259 853 613(10) =


0.0100 0010 1000 0101 1100 0100 0011 0001 1001 0101 0001 1010 1101 0(2)

6. Positive number before normalization:

6.259 853 613(10) =


110.0100 0010 1000 0101 1100 0100 0011 0001 1001 0101 0001 1010 1101 0(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:


6.259 853 613(10) =


110.0100 0010 1000 0101 1100 0100 0011 0001 1001 0101 0001 1010 1101 0(2) =


110.0100 0010 1000 0101 1100 0100 0011 0001 1001 0101 0001 1010 1101 0(2) × 20 =


1.1001 0000 1010 0001 0111 0001 0000 1100 0110 0101 0100 0110 1011 010(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):
1.1001 0000 1010 0001 0111 0001 0000 1100 0110 0101 0100 0110 1011 010


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. 1001 0000 1010 0001 0111 0001 0000 1100 0110 0101 0100 0110 1011 010 =


1001 0000 1010 0001 0111 0001 0000 1100 0110 0101 0100 0110 1011


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) =
1001 0000 1010 0001 0111 0001 0000 1100 0110 0101 0100 0110 1011


Decimal number -6.259 853 613 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0000 0001 - 1001 0000 1010 0001 0111 0001 0000 1100 0110 0101 0100 0110 1011


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