1.015 625 193 715 095 520 2 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.015 625 193 715 095 520 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
1.015 625 193 715 095 520 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: 1.
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;
  • 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.

1(10) =


1(2)


3. Convert to binary (base 2) the fractional part: 0.015 625 193 715 095 520 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) 0.015 625 193 715 095 520 2 × 2 = 0 + 0.031 250 387 430 191 040 4;
  • 2) 0.031 250 387 430 191 040 4 × 2 = 0 + 0.062 500 774 860 382 080 8;
  • 3) 0.062 500 774 860 382 080 8 × 2 = 0 + 0.125 001 549 720 764 161 6;
  • 4) 0.125 001 549 720 764 161 6 × 2 = 0 + 0.250 003 099 441 528 323 2;
  • 5) 0.250 003 099 441 528 323 2 × 2 = 0 + 0.500 006 198 883 056 646 4;
  • 6) 0.500 006 198 883 056 646 4 × 2 = 1 + 0.000 012 397 766 113 292 8;
  • 7) 0.000 012 397 766 113 292 8 × 2 = 0 + 0.000 024 795 532 226 585 6;
  • 8) 0.000 024 795 532 226 585 6 × 2 = 0 + 0.000 049 591 064 453 171 2;
  • 9) 0.000 049 591 064 453 171 2 × 2 = 0 + 0.000 099 182 128 906 342 4;
  • 10) 0.000 099 182 128 906 342 4 × 2 = 0 + 0.000 198 364 257 812 684 8;
  • 11) 0.000 198 364 257 812 684 8 × 2 = 0 + 0.000 396 728 515 625 369 6;
  • 12) 0.000 396 728 515 625 369 6 × 2 = 0 + 0.000 793 457 031 250 739 2;
  • 13) 0.000 793 457 031 250 739 2 × 2 = 0 + 0.001 586 914 062 501 478 4;
  • 14) 0.001 586 914 062 501 478 4 × 2 = 0 + 0.003 173 828 125 002 956 8;
  • 15) 0.003 173 828 125 002 956 8 × 2 = 0 + 0.006 347 656 250 005 913 6;
  • 16) 0.006 347 656 250 005 913 6 × 2 = 0 + 0.012 695 312 500 011 827 2;
  • 17) 0.012 695 312 500 011 827 2 × 2 = 0 + 0.025 390 625 000 023 654 4;
  • 18) 0.025 390 625 000 023 654 4 × 2 = 0 + 0.050 781 250 000 047 308 8;
  • 19) 0.050 781 250 000 047 308 8 × 2 = 0 + 0.101 562 500 000 094 617 6;
  • 20) 0.101 562 500 000 094 617 6 × 2 = 0 + 0.203 125 000 000 189 235 2;
  • 21) 0.203 125 000 000 189 235 2 × 2 = 0 + 0.406 250 000 000 378 470 4;
  • 22) 0.406 250 000 000 378 470 4 × 2 = 0 + 0.812 500 000 000 756 940 8;
  • 23) 0.812 500 000 000 756 940 8 × 2 = 1 + 0.625 000 000 001 513 881 6;
  • 24) 0.625 000 000 001 513 881 6 × 2 = 1 + 0.250 000 000 003 027 763 2;
  • 25) 0.250 000 000 003 027 763 2 × 2 = 0 + 0.500 000 000 006 055 526 4;
  • 26) 0.500 000 000 006 055 526 4 × 2 = 1 + 0.000 000 000 012 111 052 8;
  • 27) 0.000 000 000 012 111 052 8 × 2 = 0 + 0.000 000 000 024 222 105 6;
  • 28) 0.000 000 000 024 222 105 6 × 2 = 0 + 0.000 000 000 048 444 211 2;
  • 29) 0.000 000 000 048 444 211 2 × 2 = 0 + 0.000 000 000 096 888 422 4;
  • 30) 0.000 000 000 096 888 422 4 × 2 = 0 + 0.000 000 000 193 776 844 8;
  • 31) 0.000 000 000 193 776 844 8 × 2 = 0 + 0.000 000 000 387 553 689 6;
  • 32) 0.000 000 000 387 553 689 6 × 2 = 0 + 0.000 000 000 775 107 379 2;
  • 33) 0.000 000 000 775 107 379 2 × 2 = 0 + 0.000 000 001 550 214 758 4;
  • 34) 0.000 000 001 550 214 758 4 × 2 = 0 + 0.000 000 003 100 429 516 8;
  • 35) 0.000 000 003 100 429 516 8 × 2 = 0 + 0.000 000 006 200 859 033 6;
  • 36) 0.000 000 006 200 859 033 6 × 2 = 0 + 0.000 000 012 401 718 067 2;
  • 37) 0.000 000 012 401 718 067 2 × 2 = 0 + 0.000 000 024 803 436 134 4;
  • 38) 0.000 000 024 803 436 134 4 × 2 = 0 + 0.000 000 049 606 872 268 8;
  • 39) 0.000 000 049 606 872 268 8 × 2 = 0 + 0.000 000 099 213 744 537 6;
  • 40) 0.000 000 099 213 744 537 6 × 2 = 0 + 0.000 000 198 427 489 075 2;
  • 41) 0.000 000 198 427 489 075 2 × 2 = 0 + 0.000 000 396 854 978 150 4;
  • 42) 0.000 000 396 854 978 150 4 × 2 = 0 + 0.000 000 793 709 956 300 8;
  • 43) 0.000 000 793 709 956 300 8 × 2 = 0 + 0.000 001 587 419 912 601 6;
  • 44) 0.000 001 587 419 912 601 6 × 2 = 0 + 0.000 003 174 839 825 203 2;
  • 45) 0.000 003 174 839 825 203 2 × 2 = 0 + 0.000 006 349 679 650 406 4;
  • 46) 0.000 006 349 679 650 406 4 × 2 = 0 + 0.000 012 699 359 300 812 8;
  • 47) 0.000 012 699 359 300 812 8 × 2 = 0 + 0.000 025 398 718 601 625 6;
  • 48) 0.000 025 398 718 601 625 6 × 2 = 0 + 0.000 050 797 437 203 251 2;
  • 49) 0.000 050 797 437 203 251 2 × 2 = 0 + 0.000 101 594 874 406 502 4;
  • 50) 0.000 101 594 874 406 502 4 × 2 = 0 + 0.000 203 189 748 813 004 8;
  • 51) 0.000 203 189 748 813 004 8 × 2 = 0 + 0.000 406 379 497 626 009 6;
  • 52) 0.000 406 379 497 626 009 6 × 2 = 0 + 0.000 812 758 995 252 019 2;
  • 53) 0.000 812 758 995 252 019 2 × 2 = 0 + 0.001 625 517 990 504 038 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:


0.015 625 193 715 095 520 2(10) =


0.0000 0100 0000 0000 0000 0011 0100 0000 0000 0000 0000 0000 0000 0(2)

5. Positive number before normalization:

1.015 625 193 715 095 520 2(10) =


1.0000 0100 0000 0000 0000 0011 0100 0000 0000 0000 0000 0000 0000 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 0 positions to the left, so that only one non zero digit remains to the left of it:


1.015 625 193 715 095 520 2(10) =


1.0000 0100 0000 0000 0000 0011 0100 0000 0000 0000 0000 0000 0000 0(2) =


1.0000 0100 0000 0000 0000 0011 0100 0000 0000 0000 0000 0000 0000 0(2) × 20


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): 0


Mantissa (not normalized):
1.0000 0100 0000 0000 0000 0011 0100 0000 0000 0000 0000 0000 0000 0


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


0 + 2(11-1) - 1 =


(0 + 1 023)(10) =


1 023(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;
  • 1 023 ÷ 2 = 511 + 1;
  • 511 ÷ 2 = 255 + 1;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


1023(10) =


011 1111 1111(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 0100 0000 0000 0000 0011 0100 0000 0000 0000 0000 0000 0000 0 =


0000 0100 0000 0000 0000 0011 0100 0000 0000 0000 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) =
011 1111 1111


Mantissa (52 bits) =
0000 0100 0000 0000 0000 0011 0100 0000 0000 0000 0000 0000 0000


Decimal number 1.015 625 193 715 095 520 2 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1111 - 0000 0100 0000 0000 0000 0011 0100 0000 0000 0000 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