3.141 592 653 689 789 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 3.141 592 653 689 789 2(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
3.141 592 653 689 789 2(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: 3.
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;
  • 3 ÷ 2 = 1 + 1;
  • 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.

3(10) =


11(2)


3. Convert to binary (base 2) the fractional part: 0.141 592 653 689 789 2.

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) 0.141 592 653 689 789 2 × 2 = 0 + 0.283 185 307 379 578 4;
  • 2) 0.283 185 307 379 578 4 × 2 = 0 + 0.566 370 614 759 156 8;
  • 3) 0.566 370 614 759 156 8 × 2 = 1 + 0.132 741 229 518 313 6;
  • 4) 0.132 741 229 518 313 6 × 2 = 0 + 0.265 482 459 036 627 2;
  • 5) 0.265 482 459 036 627 2 × 2 = 0 + 0.530 964 918 073 254 4;
  • 6) 0.530 964 918 073 254 4 × 2 = 1 + 0.061 929 836 146 508 8;
  • 7) 0.061 929 836 146 508 8 × 2 = 0 + 0.123 859 672 293 017 6;
  • 8) 0.123 859 672 293 017 6 × 2 = 0 + 0.247 719 344 586 035 2;
  • 9) 0.247 719 344 586 035 2 × 2 = 0 + 0.495 438 689 172 070 4;
  • 10) 0.495 438 689 172 070 4 × 2 = 0 + 0.990 877 378 344 140 8;
  • 11) 0.990 877 378 344 140 8 × 2 = 1 + 0.981 754 756 688 281 6;
  • 12) 0.981 754 756 688 281 6 × 2 = 1 + 0.963 509 513 376 563 2;
  • 13) 0.963 509 513 376 563 2 × 2 = 1 + 0.927 019 026 753 126 4;
  • 14) 0.927 019 026 753 126 4 × 2 = 1 + 0.854 038 053 506 252 8;
  • 15) 0.854 038 053 506 252 8 × 2 = 1 + 0.708 076 107 012 505 6;
  • 16) 0.708 076 107 012 505 6 × 2 = 1 + 0.416 152 214 025 011 2;
  • 17) 0.416 152 214 025 011 2 × 2 = 0 + 0.832 304 428 050 022 4;
  • 18) 0.832 304 428 050 022 4 × 2 = 1 + 0.664 608 856 100 044 8;
  • 19) 0.664 608 856 100 044 8 × 2 = 1 + 0.329 217 712 200 089 6;
  • 20) 0.329 217 712 200 089 6 × 2 = 0 + 0.658 435 424 400 179 2;
  • 21) 0.658 435 424 400 179 2 × 2 = 1 + 0.316 870 848 800 358 4;
  • 22) 0.316 870 848 800 358 4 × 2 = 0 + 0.633 741 697 600 716 8;
  • 23) 0.633 741 697 600 716 8 × 2 = 1 + 0.267 483 395 201 433 6;
  • 24) 0.267 483 395 201 433 6 × 2 = 0 + 0.534 966 790 402 867 2;
  • 25) 0.534 966 790 402 867 2 × 2 = 1 + 0.069 933 580 805 734 4;
  • 26) 0.069 933 580 805 734 4 × 2 = 0 + 0.139 867 161 611 468 8;
  • 27) 0.139 867 161 611 468 8 × 2 = 0 + 0.279 734 323 222 937 6;
  • 28) 0.279 734 323 222 937 6 × 2 = 0 + 0.559 468 646 445 875 2;
  • 29) 0.559 468 646 445 875 2 × 2 = 1 + 0.118 937 292 891 750 4;
  • 30) 0.118 937 292 891 750 4 × 2 = 0 + 0.237 874 585 783 500 8;
  • 31) 0.237 874 585 783 500 8 × 2 = 0 + 0.475 749 171 567 001 6;
  • 32) 0.475 749 171 567 001 6 × 2 = 0 + 0.951 498 343 134 003 2;
  • 33) 0.951 498 343 134 003 2 × 2 = 1 + 0.902 996 686 268 006 4;
  • 34) 0.902 996 686 268 006 4 × 2 = 1 + 0.805 993 372 536 012 8;
  • 35) 0.805 993 372 536 012 8 × 2 = 1 + 0.611 986 745 072 025 6;
  • 36) 0.611 986 745 072 025 6 × 2 = 1 + 0.223 973 490 144 051 2;
  • 37) 0.223 973 490 144 051 2 × 2 = 0 + 0.447 946 980 288 102 4;
  • 38) 0.447 946 980 288 102 4 × 2 = 0 + 0.895 893 960 576 204 8;
  • 39) 0.895 893 960 576 204 8 × 2 = 1 + 0.791 787 921 152 409 6;
  • 40) 0.791 787 921 152 409 6 × 2 = 1 + 0.583 575 842 304 819 2;
  • 41) 0.583 575 842 304 819 2 × 2 = 1 + 0.167 151 684 609 638 4;
  • 42) 0.167 151 684 609 638 4 × 2 = 0 + 0.334 303 369 219 276 8;
  • 43) 0.334 303 369 219 276 8 × 2 = 0 + 0.668 606 738 438 553 6;
  • 44) 0.668 606 738 438 553 6 × 2 = 1 + 0.337 213 476 877 107 2;
  • 45) 0.337 213 476 877 107 2 × 2 = 0 + 0.674 426 953 754 214 4;
  • 46) 0.674 426 953 754 214 4 × 2 = 1 + 0.348 853 907 508 428 8;
  • 47) 0.348 853 907 508 428 8 × 2 = 0 + 0.697 707 815 016 857 6;
  • 48) 0.697 707 815 016 857 6 × 2 = 1 + 0.395 415 630 033 715 2;
  • 49) 0.395 415 630 033 715 2 × 2 = 0 + 0.790 831 260 067 430 4;
  • 50) 0.790 831 260 067 430 4 × 2 = 1 + 0.581 662 520 134 860 8;
  • 51) 0.581 662 520 134 860 8 × 2 = 1 + 0.163 325 040 269 721 6;
  • 52) 0.163 325 040 269 721 6 × 2 = 0 + 0.326 650 080 539 443 2;
  • 53) 0.326 650 080 539 443 2 × 2 = 0 + 0.653 300 161 078 886 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:


0.141 592 653 689 789 2(10) =


0.0010 0100 0011 1111 0110 1010 1000 1000 1111 0011 1001 0101 0110 0(2)

5. Positive number before normalization:

3.141 592 653 689 789 2(10) =


11.0010 0100 0011 1111 0110 1010 1000 1000 1111 0011 1001 0101 0110 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:


3.141 592 653 689 789 2(10) =


11.0010 0100 0011 1111 0110 1010 1000 1000 1111 0011 1001 0101 0110 0(2) =


11.0010 0100 0011 1111 0110 1010 1000 1000 1111 0011 1001 0101 0110 0(2) × 20 =


1.1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1010 1011 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):
1.1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1010 1011 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. 1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1010 1011 00 =


1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1010 1011


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) =
1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1010 1011


Decimal number 3.141 592 653 689 789 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0000 - 1001 0010 0001 1111 1011 0101 0100 0100 0111 1001 1100 1010 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