2.000 000 029 802 321 913 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2.000 000 029 802 321 913 7(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
2.000 000 029 802 321 913 7(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: 0.000 000 029 802 321 913 7.

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) 0.000 000 029 802 321 913 7 × 2 = 0 + 0.000 000 059 604 643 827 4;
  • 2) 0.000 000 059 604 643 827 4 × 2 = 0 + 0.000 000 119 209 287 654 8;
  • 3) 0.000 000 119 209 287 654 8 × 2 = 0 + 0.000 000 238 418 575 309 6;
  • 4) 0.000 000 238 418 575 309 6 × 2 = 0 + 0.000 000 476 837 150 619 2;
  • 5) 0.000 000 476 837 150 619 2 × 2 = 0 + 0.000 000 953 674 301 238 4;
  • 6) 0.000 000 953 674 301 238 4 × 2 = 0 + 0.000 001 907 348 602 476 8;
  • 7) 0.000 001 907 348 602 476 8 × 2 = 0 + 0.000 003 814 697 204 953 6;
  • 8) 0.000 003 814 697 204 953 6 × 2 = 0 + 0.000 007 629 394 409 907 2;
  • 9) 0.000 007 629 394 409 907 2 × 2 = 0 + 0.000 015 258 788 819 814 4;
  • 10) 0.000 015 258 788 819 814 4 × 2 = 0 + 0.000 030 517 577 639 628 8;
  • 11) 0.000 030 517 577 639 628 8 × 2 = 0 + 0.000 061 035 155 279 257 6;
  • 12) 0.000 061 035 155 279 257 6 × 2 = 0 + 0.000 122 070 310 558 515 2;
  • 13) 0.000 122 070 310 558 515 2 × 2 = 0 + 0.000 244 140 621 117 030 4;
  • 14) 0.000 244 140 621 117 030 4 × 2 = 0 + 0.000 488 281 242 234 060 8;
  • 15) 0.000 488 281 242 234 060 8 × 2 = 0 + 0.000 976 562 484 468 121 6;
  • 16) 0.000 976 562 484 468 121 6 × 2 = 0 + 0.001 953 124 968 936 243 2;
  • 17) 0.001 953 124 968 936 243 2 × 2 = 0 + 0.003 906 249 937 872 486 4;
  • 18) 0.003 906 249 937 872 486 4 × 2 = 0 + 0.007 812 499 875 744 972 8;
  • 19) 0.007 812 499 875 744 972 8 × 2 = 0 + 0.015 624 999 751 489 945 6;
  • 20) 0.015 624 999 751 489 945 6 × 2 = 0 + 0.031 249 999 502 979 891 2;
  • 21) 0.031 249 999 502 979 891 2 × 2 = 0 + 0.062 499 999 005 959 782 4;
  • 22) 0.062 499 999 005 959 782 4 × 2 = 0 + 0.124 999 998 011 919 564 8;
  • 23) 0.124 999 998 011 919 564 8 × 2 = 0 + 0.249 999 996 023 839 129 6;
  • 24) 0.249 999 996 023 839 129 6 × 2 = 0 + 0.499 999 992 047 678 259 2;
  • 25) 0.499 999 992 047 678 259 2 × 2 = 0 + 0.999 999 984 095 356 518 4;
  • 26) 0.999 999 984 095 356 518 4 × 2 = 1 + 0.999 999 968 190 713 036 8;
  • 27) 0.999 999 968 190 713 036 8 × 2 = 1 + 0.999 999 936 381 426 073 6;
  • 28) 0.999 999 936 381 426 073 6 × 2 = 1 + 0.999 999 872 762 852 147 2;
  • 29) 0.999 999 872 762 852 147 2 × 2 = 1 + 0.999 999 745 525 704 294 4;
  • 30) 0.999 999 745 525 704 294 4 × 2 = 1 + 0.999 999 491 051 408 588 8;
  • 31) 0.999 999 491 051 408 588 8 × 2 = 1 + 0.999 998 982 102 817 177 6;
  • 32) 0.999 998 982 102 817 177 6 × 2 = 1 + 0.999 997 964 205 634 355 2;
  • 33) 0.999 997 964 205 634 355 2 × 2 = 1 + 0.999 995 928 411 268 710 4;
  • 34) 0.999 995 928 411 268 710 4 × 2 = 1 + 0.999 991 856 822 537 420 8;
  • 35) 0.999 991 856 822 537 420 8 × 2 = 1 + 0.999 983 713 645 074 841 6;
  • 36) 0.999 983 713 645 074 841 6 × 2 = 1 + 0.999 967 427 290 149 683 2;
  • 37) 0.999 967 427 290 149 683 2 × 2 = 1 + 0.999 934 854 580 299 366 4;
  • 38) 0.999 934 854 580 299 366 4 × 2 = 1 + 0.999 869 709 160 598 732 8;
  • 39) 0.999 869 709 160 598 732 8 × 2 = 1 + 0.999 739 418 321 197 465 6;
  • 40) 0.999 739 418 321 197 465 6 × 2 = 1 + 0.999 478 836 642 394 931 2;
  • 41) 0.999 478 836 642 394 931 2 × 2 = 1 + 0.998 957 673 284 789 862 4;
  • 42) 0.998 957 673 284 789 862 4 × 2 = 1 + 0.997 915 346 569 579 724 8;
  • 43) 0.997 915 346 569 579 724 8 × 2 = 1 + 0.995 830 693 139 159 449 6;
  • 44) 0.995 830 693 139 159 449 6 × 2 = 1 + 0.991 661 386 278 318 899 2;
  • 45) 0.991 661 386 278 318 899 2 × 2 = 1 + 0.983 322 772 556 637 798 4;
  • 46) 0.983 322 772 556 637 798 4 × 2 = 1 + 0.966 645 545 113 275 596 8;
  • 47) 0.966 645 545 113 275 596 8 × 2 = 1 + 0.933 291 090 226 551 193 6;
  • 48) 0.933 291 090 226 551 193 6 × 2 = 1 + 0.866 582 180 453 102 387 2;
  • 49) 0.866 582 180 453 102 387 2 × 2 = 1 + 0.733 164 360 906 204 774 4;
  • 50) 0.733 164 360 906 204 774 4 × 2 = 1 + 0.466 328 721 812 409 548 8;
  • 51) 0.466 328 721 812 409 548 8 × 2 = 0 + 0.932 657 443 624 819 097 6;
  • 52) 0.932 657 443 624 819 097 6 × 2 = 1 + 0.865 314 887 249 638 195 2;
  • 53) 0.865 314 887 249 638 195 2 × 2 = 1 + 0.730 629 774 499 276 390 4;

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:


0.000 000 029 802 321 913 7(10) =


0.0000 0000 0000 0000 0000 0000 0111 1111 1111 1111 1111 1111 1101 1(2)

5. Positive number before normalization:

2.000 000 029 802 321 913 7(10) =


10.0000 0000 0000 0000 0000 0000 0111 1111 1111 1111 1111 1111 1101 1(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:


2.000 000 029 802 321 913 7(10) =


10.0000 0000 0000 0000 0000 0000 0111 1111 1111 1111 1111 1111 1101 1(2) =


10.0000 0000 0000 0000 0000 0000 0111 1111 1111 1111 1111 1111 1101 1(2) × 20 =


1.0000 0000 0000 0000 0000 0000 0011 1111 1111 1111 1111 1111 1110 11(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):
1.0000 0000 0000 0000 0000 0000 0011 1111 1111 1111 1111 1111 1110 11


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. 0000 0000 0000 0000 0000 0000 0011 1111 1111 1111 1111 1111 1110 11 =


0000 0000 0000 0000 0000 0000 0011 1111 1111 1111 1111 1111 1110


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) =
0000 0000 0000 0000 0000 0000 0011 1111 1111 1111 1111 1111 1110


Decimal number 2.000 000 029 802 321 913 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 0000 0000 0000 0000 0000 0000 0011 1111 1111 1111 1111 1111 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