64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 18 444 169 349 236 478 865 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 18 444 169 349 236 478 865(10) converted and written in 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

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;
  • 18 444 169 349 236 478 865 ÷ 2 = 9 222 084 674 618 239 432 + 1;
  • 9 222 084 674 618 239 432 ÷ 2 = 4 611 042 337 309 119 716 + 0;
  • 4 611 042 337 309 119 716 ÷ 2 = 2 305 521 168 654 559 858 + 0;
  • 2 305 521 168 654 559 858 ÷ 2 = 1 152 760 584 327 279 929 + 0;
  • 1 152 760 584 327 279 929 ÷ 2 = 576 380 292 163 639 964 + 1;
  • 576 380 292 163 639 964 ÷ 2 = 288 190 146 081 819 982 + 0;
  • 288 190 146 081 819 982 ÷ 2 = 144 095 073 040 909 991 + 0;
  • 144 095 073 040 909 991 ÷ 2 = 72 047 536 520 454 995 + 1;
  • 72 047 536 520 454 995 ÷ 2 = 36 023 768 260 227 497 + 1;
  • 36 023 768 260 227 497 ÷ 2 = 18 011 884 130 113 748 + 1;
  • 18 011 884 130 113 748 ÷ 2 = 9 005 942 065 056 874 + 0;
  • 9 005 942 065 056 874 ÷ 2 = 4 502 971 032 528 437 + 0;
  • 4 502 971 032 528 437 ÷ 2 = 2 251 485 516 264 218 + 1;
  • 2 251 485 516 264 218 ÷ 2 = 1 125 742 758 132 109 + 0;
  • 1 125 742 758 132 109 ÷ 2 = 562 871 379 066 054 + 1;
  • 562 871 379 066 054 ÷ 2 = 281 435 689 533 027 + 0;
  • 281 435 689 533 027 ÷ 2 = 140 717 844 766 513 + 1;
  • 140 717 844 766 513 ÷ 2 = 70 358 922 383 256 + 1;
  • 70 358 922 383 256 ÷ 2 = 35 179 461 191 628 + 0;
  • 35 179 461 191 628 ÷ 2 = 17 589 730 595 814 + 0;
  • 17 589 730 595 814 ÷ 2 = 8 794 865 297 907 + 0;
  • 8 794 865 297 907 ÷ 2 = 4 397 432 648 953 + 1;
  • 4 397 432 648 953 ÷ 2 = 2 198 716 324 476 + 1;
  • 2 198 716 324 476 ÷ 2 = 1 099 358 162 238 + 0;
  • 1 099 358 162 238 ÷ 2 = 549 679 081 119 + 0;
  • 549 679 081 119 ÷ 2 = 274 839 540 559 + 1;
  • 274 839 540 559 ÷ 2 = 137 419 770 279 + 1;
  • 137 419 770 279 ÷ 2 = 68 709 885 139 + 1;
  • 68 709 885 139 ÷ 2 = 34 354 942 569 + 1;
  • 34 354 942 569 ÷ 2 = 17 177 471 284 + 1;
  • 17 177 471 284 ÷ 2 = 8 588 735 642 + 0;
  • 8 588 735 642 ÷ 2 = 4 294 367 821 + 0;
  • 4 294 367 821 ÷ 2 = 2 147 183 910 + 1;
  • 2 147 183 910 ÷ 2 = 1 073 591 955 + 0;
  • 1 073 591 955 ÷ 2 = 536 795 977 + 1;
  • 536 795 977 ÷ 2 = 268 397 988 + 1;
  • 268 397 988 ÷ 2 = 134 198 994 + 0;
  • 134 198 994 ÷ 2 = 67 099 497 + 0;
  • 67 099 497 ÷ 2 = 33 549 748 + 1;
  • 33 549 748 ÷ 2 = 16 774 874 + 0;
  • 16 774 874 ÷ 2 = 8 387 437 + 0;
  • 8 387 437 ÷ 2 = 4 193 718 + 1;
  • 4 193 718 ÷ 2 = 2 096 859 + 0;
  • 2 096 859 ÷ 2 = 1 048 429 + 1;
  • 1 048 429 ÷ 2 = 524 214 + 1;
  • 524 214 ÷ 2 = 262 107 + 0;
  • 262 107 ÷ 2 = 131 053 + 1;
  • 131 053 ÷ 2 = 65 526 + 1;
  • 65 526 ÷ 2 = 32 763 + 0;
  • 32 763 ÷ 2 = 16 381 + 1;
  • 16 381 ÷ 2 = 8 190 + 1;
  • 8 190 ÷ 2 = 4 095 + 0;
  • 4 095 ÷ 2 = 2 047 + 1;
  • 2 047 ÷ 2 = 1 023 + 1;
  • 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;

2. Construct the base 2 representation of the positive number.

Take all the remainders starting from the bottom of the list constructed above.


18 444 169 349 236 478 865(10) =


1111 1111 1111 0110 1101 1010 0100 1101 0011 1110 0110 0011 0101 0011 1001 0001(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 63 positions to the left, so that only one non zero digit remains to the left of it:


18 444 169 349 236 478 865(10) =


1111 1111 1111 0110 1101 1010 0100 1101 0011 1110 0110 0011 0101 0011 1001 0001(2) =


1111 1111 1111 0110 1101 1010 0100 1101 0011 1110 0110 0011 0101 0011 1001 0001(2) × 20 =


1.1111 1111 1110 1101 1011 0100 1001 1010 0111 1100 1100 0110 1010 0111 0010 001(2) × 263


4. 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): 63


Mantissa (not normalized):
1.1111 1111 1110 1101 1011 0100 1001 1010 0111 1100 1100 0110 1010 0111 0010 001


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


63 + 2(11-1) - 1 =


(63 + 1 023)(10) =


1 086(10)


6. 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;
  • 1 086 ÷ 2 = 543 + 0;
  • 543 ÷ 2 = 271 + 1;
  • 271 ÷ 2 = 135 + 1;
  • 135 ÷ 2 = 67 + 1;
  • 67 ÷ 2 = 33 + 1;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

7. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1086(10) =


100 0011 1110(2)


8. 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. 1111 1111 1110 1101 1011 0100 1001 1010 0111 1100 1100 0110 1010 011 1001 0001 =


1111 1111 1110 1101 1011 0100 1001 1010 0111 1100 1100 0110 1010


9. 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 0011 1110


Mantissa (52 bits) =
1111 1111 1110 1101 1011 0100 1001 1010 0111 1100 1100 0110 1010


The base ten decimal number 18 444 169 349 236 478 865 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0011 1110 - 1111 1111 1110 1101 1011 0100 1001 1010 0111 1100 1100 0110 1010

The latest decimal numbers converted from base ten to 64 bit double precision IEEE 754 floating point binary standard representation

Number 50 530 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:32 UTC (GMT)
Number 16 939 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:31 UTC (GMT)
Number 31.63 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:31 UTC (GMT)
Number -3.712 125 056 104 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:31 UTC (GMT)
Number 112 285 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:31 UTC (GMT)
Number 0.123 456 788 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:31 UTC (GMT)
Number 200 116 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:31 UTC (GMT)
Number 0.111 7 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:31 UTC (GMT)
Number 17 392 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:31 UTC (GMT)
Number 7 333 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard Apr 30 08:31 UTC (GMT)
All base ten decimal numbers converted to 64 bit double precision IEEE 754 binary floating point

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