32 913.337 166 009 587 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 32 913.337 166 009 587(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
32 913.337 166 009 587(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. First, convert to binary (in base 2) the integer part: 32 913.
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;
  • 32 913 ÷ 2 = 16 456 + 1;
  • 16 456 ÷ 2 = 8 228 + 0;
  • 8 228 ÷ 2 = 4 114 + 0;
  • 4 114 ÷ 2 = 2 057 + 0;
  • 2 057 ÷ 2 = 1 028 + 1;
  • 1 028 ÷ 2 = 514 + 0;
  • 514 ÷ 2 = 257 + 0;
  • 257 ÷ 2 = 128 + 1;
  • 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;

2. 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.

32 913(10) =


1000 0000 1001 0001(2)


3. Convert to binary (base 2) the fractional part: 0.337 166 009 587.

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) 0.337 166 009 587 × 2 = 0 + 0.674 332 019 174;
  • 2) 0.674 332 019 174 × 2 = 1 + 0.348 664 038 348;
  • 3) 0.348 664 038 348 × 2 = 0 + 0.697 328 076 696;
  • 4) 0.697 328 076 696 × 2 = 1 + 0.394 656 153 392;
  • 5) 0.394 656 153 392 × 2 = 0 + 0.789 312 306 784;
  • 6) 0.789 312 306 784 × 2 = 1 + 0.578 624 613 568;
  • 7) 0.578 624 613 568 × 2 = 1 + 0.157 249 227 136;
  • 8) 0.157 249 227 136 × 2 = 0 + 0.314 498 454 272;
  • 9) 0.314 498 454 272 × 2 = 0 + 0.628 996 908 544;
  • 10) 0.628 996 908 544 × 2 = 1 + 0.257 993 817 088;
  • 11) 0.257 993 817 088 × 2 = 0 + 0.515 987 634 176;
  • 12) 0.515 987 634 176 × 2 = 1 + 0.031 975 268 352;
  • 13) 0.031 975 268 352 × 2 = 0 + 0.063 950 536 704;
  • 14) 0.063 950 536 704 × 2 = 0 + 0.127 901 073 408;
  • 15) 0.127 901 073 408 × 2 = 0 + 0.255 802 146 816;
  • 16) 0.255 802 146 816 × 2 = 0 + 0.511 604 293 632;
  • 17) 0.511 604 293 632 × 2 = 1 + 0.023 208 587 264;
  • 18) 0.023 208 587 264 × 2 = 0 + 0.046 417 174 528;
  • 19) 0.046 417 174 528 × 2 = 0 + 0.092 834 349 056;
  • 20) 0.092 834 349 056 × 2 = 0 + 0.185 668 698 112;
  • 21) 0.185 668 698 112 × 2 = 0 + 0.371 337 396 224;
  • 22) 0.371 337 396 224 × 2 = 0 + 0.742 674 792 448;
  • 23) 0.742 674 792 448 × 2 = 1 + 0.485 349 584 896;
  • 24) 0.485 349 584 896 × 2 = 0 + 0.970 699 169 792;
  • 25) 0.970 699 169 792 × 2 = 1 + 0.941 398 339 584;
  • 26) 0.941 398 339 584 × 2 = 1 + 0.882 796 679 168;
  • 27) 0.882 796 679 168 × 2 = 1 + 0.765 593 358 336;
  • 28) 0.765 593 358 336 × 2 = 1 + 0.531 186 716 672;
  • 29) 0.531 186 716 672 × 2 = 1 + 0.062 373 433 344;
  • 30) 0.062 373 433 344 × 2 = 0 + 0.124 746 866 688;
  • 31) 0.124 746 866 688 × 2 = 0 + 0.249 493 733 376;
  • 32) 0.249 493 733 376 × 2 = 0 + 0.498 987 466 752;
  • 33) 0.498 987 466 752 × 2 = 0 + 0.997 974 933 504;
  • 34) 0.997 974 933 504 × 2 = 1 + 0.995 949 867 008;
  • 35) 0.995 949 867 008 × 2 = 1 + 0.991 899 734 016;
  • 36) 0.991 899 734 016 × 2 = 1 + 0.983 799 468 032;
  • 37) 0.983 799 468 032 × 2 = 1 + 0.967 598 936 064;
  • 38) 0.967 598 936 064 × 2 = 1 + 0.935 197 872 128;
  • 39) 0.935 197 872 128 × 2 = 1 + 0.870 395 744 256;
  • 40) 0.870 395 744 256 × 2 = 1 + 0.740 791 488 512;
  • 41) 0.740 791 488 512 × 2 = 1 + 0.481 582 977 024;
  • 42) 0.481 582 977 024 × 2 = 0 + 0.963 165 954 048;
  • 43) 0.963 165 954 048 × 2 = 1 + 0.926 331 908 096;
  • 44) 0.926 331 908 096 × 2 = 1 + 0.852 663 816 192;
  • 45) 0.852 663 816 192 × 2 = 1 + 0.705 327 632 384;
  • 46) 0.705 327 632 384 × 2 = 1 + 0.410 655 264 768;
  • 47) 0.410 655 264 768 × 2 = 0 + 0.821 310 529 536;
  • 48) 0.821 310 529 536 × 2 = 1 + 0.642 621 059 072;
  • 49) 0.642 621 059 072 × 2 = 1 + 0.285 242 118 144;
  • 50) 0.285 242 118 144 × 2 = 0 + 0.570 484 236 288;
  • 51) 0.570 484 236 288 × 2 = 1 + 0.140 968 472 576;
  • 52) 0.140 968 472 576 × 2 = 0 + 0.281 936 945 152;
  • 53) 0.281 936 945 152 × 2 = 0 + 0.563 873 890 304;

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).


4. 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:


0.337 166 009 587(10) =


0.0101 0110 0101 0000 1000 0010 1111 1000 0111 1111 1011 1101 1010 0(2)

5. Positive number before normalization:

32 913.337 166 009 587(10) =


1000 0000 1001 0001.0101 0110 0101 0000 1000 0010 1111 1000 0111 1111 1011 1101 1010 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 15 positions to the left, so that only one non zero digit remains to the left of it:


32 913.337 166 009 587(10) =


1000 0000 1001 0001.0101 0110 0101 0000 1000 0010 1111 1000 0111 1111 1011 1101 1010 0(2) =


1000 0000 1001 0001.0101 0110 0101 0000 1000 0010 1111 1000 0111 1111 1011 1101 1010 0(2) × 20 =


1.0000 0001 0010 0010 1010 1100 1010 0001 0000 0101 1111 0000 1111 1111 0111 1011 0100(2) × 215


7. 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 0 (a positive number)


Exponent (unadjusted): 15


Mantissa (not normalized):
1.0000 0001 0010 0010 1010 1100 1010 0001 0000 0101 1111 0000 1111 1111 0111 1011 0100


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


15 + 2(11-1) - 1 =


(15 + 1 023)(10) =


1 038(10)


9. 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;
  • 1 038 ÷ 2 = 519 + 0;
  • 519 ÷ 2 = 259 + 1;
  • 259 ÷ 2 = 129 + 1;
  • 129 ÷ 2 = 64 + 1;
  • 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;

10. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1038(10) =


100 0000 1110(2)


11. 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. 0000 0001 0010 0010 1010 1100 1010 0001 0000 0101 1111 0000 1111 1111 0111 1011 0100 =


0000 0001 0010 0010 1010 1100 1010 0001 0000 0101 1111 0000 1111


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
100 0000 1110


Mantissa (52 bits) =
0000 0001 0010 0010 1010 1100 1010 0001 0000 0101 1111 0000 1111


Decimal number 32 913.337 166 009 587 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1110 - 0000 0001 0010 0010 1010 1100 1010 0001 0000 0101 1111 0000 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