2.444 089 209 850 062 616 981 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.444 089 209 850 062 616 981(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
2.444 089 209 850 062 616 981(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: 2.
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;
  • 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.

2(10) =


10(2)


3. Convert to binary (base 2) the fractional part: 0.444 089 209 850 062 616 981.

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) 0.444 089 209 850 062 616 981 × 2 = 0 + 0.888 178 419 700 125 233 962;
  • 2) 0.888 178 419 700 125 233 962 × 2 = 1 + 0.776 356 839 400 250 467 924;
  • 3) 0.776 356 839 400 250 467 924 × 2 = 1 + 0.552 713 678 800 500 935 848;
  • 4) 0.552 713 678 800 500 935 848 × 2 = 1 + 0.105 427 357 601 001 871 696;
  • 5) 0.105 427 357 601 001 871 696 × 2 = 0 + 0.210 854 715 202 003 743 392;
  • 6) 0.210 854 715 202 003 743 392 × 2 = 0 + 0.421 709 430 404 007 486 784;
  • 7) 0.421 709 430 404 007 486 784 × 2 = 0 + 0.843 418 860 808 014 973 568;
  • 8) 0.843 418 860 808 014 973 568 × 2 = 1 + 0.686 837 721 616 029 947 136;
  • 9) 0.686 837 721 616 029 947 136 × 2 = 1 + 0.373 675 443 232 059 894 272;
  • 10) 0.373 675 443 232 059 894 272 × 2 = 0 + 0.747 350 886 464 119 788 544;
  • 11) 0.747 350 886 464 119 788 544 × 2 = 1 + 0.494 701 772 928 239 577 088;
  • 12) 0.494 701 772 928 239 577 088 × 2 = 0 + 0.989 403 545 856 479 154 176;
  • 13) 0.989 403 545 856 479 154 176 × 2 = 1 + 0.978 807 091 712 958 308 352;
  • 14) 0.978 807 091 712 958 308 352 × 2 = 1 + 0.957 614 183 425 916 616 704;
  • 15) 0.957 614 183 425 916 616 704 × 2 = 1 + 0.915 228 366 851 833 233 408;
  • 16) 0.915 228 366 851 833 233 408 × 2 = 1 + 0.830 456 733 703 666 466 816;
  • 17) 0.830 456 733 703 666 466 816 × 2 = 1 + 0.660 913 467 407 332 933 632;
  • 18) 0.660 913 467 407 332 933 632 × 2 = 1 + 0.321 826 934 814 665 867 264;
  • 19) 0.321 826 934 814 665 867 264 × 2 = 0 + 0.643 653 869 629 331 734 528;
  • 20) 0.643 653 869 629 331 734 528 × 2 = 1 + 0.287 307 739 258 663 469 056;
  • 21) 0.287 307 739 258 663 469 056 × 2 = 0 + 0.574 615 478 517 326 938 112;
  • 22) 0.574 615 478 517 326 938 112 × 2 = 1 + 0.149 230 957 034 653 876 224;
  • 23) 0.149 230 957 034 653 876 224 × 2 = 0 + 0.298 461 914 069 307 752 448;
  • 24) 0.298 461 914 069 307 752 448 × 2 = 0 + 0.596 923 828 138 615 504 896;
  • 25) 0.596 923 828 138 615 504 896 × 2 = 1 + 0.193 847 656 277 231 009 792;
  • 26) 0.193 847 656 277 231 009 792 × 2 = 0 + 0.387 695 312 554 462 019 584;
  • 27) 0.387 695 312 554 462 019 584 × 2 = 0 + 0.775 390 625 108 924 039 168;
  • 28) 0.775 390 625 108 924 039 168 × 2 = 1 + 0.550 781 250 217 848 078 336;
  • 29) 0.550 781 250 217 848 078 336 × 2 = 1 + 0.101 562 500 435 696 156 672;
  • 30) 0.101 562 500 435 696 156 672 × 2 = 0 + 0.203 125 000 871 392 313 344;
  • 31) 0.203 125 000 871 392 313 344 × 2 = 0 + 0.406 250 001 742 784 626 688;
  • 32) 0.406 250 001 742 784 626 688 × 2 = 0 + 0.812 500 003 485 569 253 376;
  • 33) 0.812 500 003 485 569 253 376 × 2 = 1 + 0.625 000 006 971 138 506 752;
  • 34) 0.625 000 006 971 138 506 752 × 2 = 1 + 0.250 000 013 942 277 013 504;
  • 35) 0.250 000 013 942 277 013 504 × 2 = 0 + 0.500 000 027 884 554 027 008;
  • 36) 0.500 000 027 884 554 027 008 × 2 = 1 + 0.000 000 055 769 108 054 016;
  • 37) 0.000 000 055 769 108 054 016 × 2 = 0 + 0.000 000 111 538 216 108 032;
  • 38) 0.000 000 111 538 216 108 032 × 2 = 0 + 0.000 000 223 076 432 216 064;
  • 39) 0.000 000 223 076 432 216 064 × 2 = 0 + 0.000 000 446 152 864 432 128;
  • 40) 0.000 000 446 152 864 432 128 × 2 = 0 + 0.000 000 892 305 728 864 256;
  • 41) 0.000 000 892 305 728 864 256 × 2 = 0 + 0.000 001 784 611 457 728 512;
  • 42) 0.000 001 784 611 457 728 512 × 2 = 0 + 0.000 003 569 222 915 457 024;
  • 43) 0.000 003 569 222 915 457 024 × 2 = 0 + 0.000 007 138 445 830 914 048;
  • 44) 0.000 007 138 445 830 914 048 × 2 = 0 + 0.000 014 276 891 661 828 096;
  • 45) 0.000 014 276 891 661 828 096 × 2 = 0 + 0.000 028 553 783 323 656 192;
  • 46) 0.000 028 553 783 323 656 192 × 2 = 0 + 0.000 057 107 566 647 312 384;
  • 47) 0.000 057 107 566 647 312 384 × 2 = 0 + 0.000 114 215 133 294 624 768;
  • 48) 0.000 114 215 133 294 624 768 × 2 = 0 + 0.000 228 430 266 589 249 536;
  • 49) 0.000 228 430 266 589 249 536 × 2 = 0 + 0.000 456 860 533 178 499 072;
  • 50) 0.000 456 860 533 178 499 072 × 2 = 0 + 0.000 913 721 066 356 998 144;
  • 51) 0.000 913 721 066 356 998 144 × 2 = 0 + 0.001 827 442 132 713 996 288;
  • 52) 0.001 827 442 132 713 996 288 × 2 = 0 + 0.003 654 884 265 427 992 576;
  • 53) 0.003 654 884 265 427 992 576 × 2 = 0 + 0.007 309 768 530 855 985 152;

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:


0.444 089 209 850 062 616 981(10) =


0.0111 0001 1010 1111 1101 0100 1001 1000 1101 0000 0000 0000 0000 0(2)

5. Positive number before normalization:

2.444 089 209 850 062 616 981(10) =


10.0111 0001 1010 1111 1101 0100 1001 1000 1101 0000 0000 0000 0000 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 1 positions to the left, so that only one non zero digit remains to the left of it:


2.444 089 209 850 062 616 981(10) =


10.0111 0001 1010 1111 1101 0100 1001 1000 1101 0000 0000 0000 0000 0(2) =


10.0111 0001 1010 1111 1101 0100 1001 1000 1101 0000 0000 0000 0000 0(2) × 20 =


1.0011 1000 1101 0111 1110 1010 0100 1100 0110 1000 0000 0000 0000 00(2) × 21


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): 1


Mantissa (not normalized):
1.0011 1000 1101 0111 1110 1010 0100 1100 0110 1000 0000 0000 0000 00


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


1 + 2(11-1) - 1 =


(1 + 1 023)(10) =


1 024(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;
  • 1 024 ÷ 2 = 512 + 0;
  • 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;

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) =


1024(10) =


100 0000 0000(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. 0011 1000 1101 0111 1110 1010 0100 1100 0110 1000 0000 0000 0000 00 =


0011 1000 1101 0111 1110 1010 0100 1100 0110 1000 0000 0000 0000


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 0000


Mantissa (52 bits) =
0011 1000 1101 0111 1110 1010 0100 1100 0110 1000 0000 0000 0000


Decimal number 2.444 089 209 850 062 616 981 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0011 1000 1101 0111 1110 1010 0100 1100 0110 1000 0000 0000 0000


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