241 317.426 001 548 752 7 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 241 317.426 001 548 752 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
241 317.426 001 548 752 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: 241 317.
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;
  • 241 317 ÷ 2 = 120 658 + 1;
  • 120 658 ÷ 2 = 60 329 + 0;
  • 60 329 ÷ 2 = 30 164 + 1;
  • 30 164 ÷ 2 = 15 082 + 0;
  • 15 082 ÷ 2 = 7 541 + 0;
  • 7 541 ÷ 2 = 3 770 + 1;
  • 3 770 ÷ 2 = 1 885 + 0;
  • 1 885 ÷ 2 = 942 + 1;
  • 942 ÷ 2 = 471 + 0;
  • 471 ÷ 2 = 235 + 1;
  • 235 ÷ 2 = 117 + 1;
  • 117 ÷ 2 = 58 + 1;
  • 58 ÷ 2 = 29 + 0;
  • 29 ÷ 2 = 14 + 1;
  • 14 ÷ 2 = 7 + 0;
  • 7 ÷ 2 = 3 + 1;
  • 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.

241 317(10) =


11 1010 1110 1010 0101(2)


3. Convert to binary (base 2) the fractional part: 0.426 001 548 752 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) 0.426 001 548 752 7 × 2 = 0 + 0.852 003 097 505 4;
  • 2) 0.852 003 097 505 4 × 2 = 1 + 0.704 006 195 010 8;
  • 3) 0.704 006 195 010 8 × 2 = 1 + 0.408 012 390 021 6;
  • 4) 0.408 012 390 021 6 × 2 = 0 + 0.816 024 780 043 2;
  • 5) 0.816 024 780 043 2 × 2 = 1 + 0.632 049 560 086 4;
  • 6) 0.632 049 560 086 4 × 2 = 1 + 0.264 099 120 172 8;
  • 7) 0.264 099 120 172 8 × 2 = 0 + 0.528 198 240 345 6;
  • 8) 0.528 198 240 345 6 × 2 = 1 + 0.056 396 480 691 2;
  • 9) 0.056 396 480 691 2 × 2 = 0 + 0.112 792 961 382 4;
  • 10) 0.112 792 961 382 4 × 2 = 0 + 0.225 585 922 764 8;
  • 11) 0.225 585 922 764 8 × 2 = 0 + 0.451 171 845 529 6;
  • 12) 0.451 171 845 529 6 × 2 = 0 + 0.902 343 691 059 2;
  • 13) 0.902 343 691 059 2 × 2 = 1 + 0.804 687 382 118 4;
  • 14) 0.804 687 382 118 4 × 2 = 1 + 0.609 374 764 236 8;
  • 15) 0.609 374 764 236 8 × 2 = 1 + 0.218 749 528 473 6;
  • 16) 0.218 749 528 473 6 × 2 = 0 + 0.437 499 056 947 2;
  • 17) 0.437 499 056 947 2 × 2 = 0 + 0.874 998 113 894 4;
  • 18) 0.874 998 113 894 4 × 2 = 1 + 0.749 996 227 788 8;
  • 19) 0.749 996 227 788 8 × 2 = 1 + 0.499 992 455 577 6;
  • 20) 0.499 992 455 577 6 × 2 = 0 + 0.999 984 911 155 2;
  • 21) 0.999 984 911 155 2 × 2 = 1 + 0.999 969 822 310 4;
  • 22) 0.999 969 822 310 4 × 2 = 1 + 0.999 939 644 620 8;
  • 23) 0.999 939 644 620 8 × 2 = 1 + 0.999 879 289 241 6;
  • 24) 0.999 879 289 241 6 × 2 = 1 + 0.999 758 578 483 2;
  • 25) 0.999 758 578 483 2 × 2 = 1 + 0.999 517 156 966 4;
  • 26) 0.999 517 156 966 4 × 2 = 1 + 0.999 034 313 932 8;
  • 27) 0.999 034 313 932 8 × 2 = 1 + 0.998 068 627 865 6;
  • 28) 0.998 068 627 865 6 × 2 = 1 + 0.996 137 255 731 2;
  • 29) 0.996 137 255 731 2 × 2 = 1 + 0.992 274 511 462 4;
  • 30) 0.992 274 511 462 4 × 2 = 1 + 0.984 549 022 924 8;
  • 31) 0.984 549 022 924 8 × 2 = 1 + 0.969 098 045 849 6;
  • 32) 0.969 098 045 849 6 × 2 = 1 + 0.938 196 091 699 2;
  • 33) 0.938 196 091 699 2 × 2 = 1 + 0.876 392 183 398 4;
  • 34) 0.876 392 183 398 4 × 2 = 1 + 0.752 784 366 796 8;
  • 35) 0.752 784 366 796 8 × 2 = 1 + 0.505 568 733 593 6;
  • 36) 0.505 568 733 593 6 × 2 = 1 + 0.011 137 467 187 2;
  • 37) 0.011 137 467 187 2 × 2 = 0 + 0.022 274 934 374 4;
  • 38) 0.022 274 934 374 4 × 2 = 0 + 0.044 549 868 748 8;
  • 39) 0.044 549 868 748 8 × 2 = 0 + 0.089 099 737 497 6;
  • 40) 0.089 099 737 497 6 × 2 = 0 + 0.178 199 474 995 2;
  • 41) 0.178 199 474 995 2 × 2 = 0 + 0.356 398 949 990 4;
  • 42) 0.356 398 949 990 4 × 2 = 0 + 0.712 797 899 980 8;
  • 43) 0.712 797 899 980 8 × 2 = 1 + 0.425 595 799 961 6;
  • 44) 0.425 595 799 961 6 × 2 = 0 + 0.851 191 599 923 2;
  • 45) 0.851 191 599 923 2 × 2 = 1 + 0.702 383 199 846 4;
  • 46) 0.702 383 199 846 4 × 2 = 1 + 0.404 766 399 692 8;
  • 47) 0.404 766 399 692 8 × 2 = 0 + 0.809 532 799 385 6;
  • 48) 0.809 532 799 385 6 × 2 = 1 + 0.619 065 598 771 2;
  • 49) 0.619 065 598 771 2 × 2 = 1 + 0.238 131 197 542 4;
  • 50) 0.238 131 197 542 4 × 2 = 0 + 0.476 262 395 084 8;
  • 51) 0.476 262 395 084 8 × 2 = 0 + 0.952 524 790 169 6;
  • 52) 0.952 524 790 169 6 × 2 = 1 + 0.905 049 580 339 2;
  • 53) 0.905 049 580 339 2 × 2 = 1 + 0.810 099 160 678 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:


0.426 001 548 752 7(10) =


0.0110 1101 0000 1110 0110 1111 1111 1111 1111 0000 0010 1101 1001 1(2)

5. Positive number before normalization:

241 317.426 001 548 752 7(10) =


11 1010 1110 1010 0101.0110 1101 0000 1110 0110 1111 1111 1111 1111 0000 0010 1101 1001 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 17 positions to the left, so that only one non zero digit remains to the left of it:


241 317.426 001 548 752 7(10) =


11 1010 1110 1010 0101.0110 1101 0000 1110 0110 1111 1111 1111 1111 0000 0010 1101 1001 1(2) =


11 1010 1110 1010 0101.0110 1101 0000 1110 0110 1111 1111 1111 1111 0000 0010 1101 1001 1(2) × 20 =


1.1101 0111 0101 0010 1011 0110 1000 0111 0011 0111 1111 1111 1111 1000 0001 0110 1100 11(2) × 217


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): 17


Mantissa (not normalized):
1.1101 0111 0101 0010 1011 0110 1000 0111 0011 0111 1111 1111 1111 1000 0001 0110 1100 11


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


17 + 2(11-1) - 1 =


(17 + 1 023)(10) =


1 040(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;
  • 1 040 ÷ 2 = 520 + 0;
  • 520 ÷ 2 = 260 + 0;
  • 260 ÷ 2 = 130 + 0;
  • 130 ÷ 2 = 65 + 0;
  • 65 ÷ 2 = 32 + 1;
  • 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) =


1040(10) =


100 0001 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. 1101 0111 0101 0010 1011 0110 1000 0111 0011 0111 1111 1111 1111 10 0000 0101 1011 0011 =


1101 0111 0101 0010 1011 0110 1000 0111 0011 0111 1111 1111 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 0001 0000


Mantissa (52 bits) =
1101 0111 0101 0010 1011 0110 1000 0111 0011 0111 1111 1111 1111


Decimal number 241 317.426 001 548 752 7 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0001 0000 - 1101 0111 0101 0010 1011 0110 1000 0111 0011 0111 1111 1111 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