64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 987 654 321 987 654 363 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 987 654 321 987 654 363(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;
  • 987 654 321 987 654 363 ÷ 2 = 493 827 160 993 827 181 + 1;
  • 493 827 160 993 827 181 ÷ 2 = 246 913 580 496 913 590 + 1;
  • 246 913 580 496 913 590 ÷ 2 = 123 456 790 248 456 795 + 0;
  • 123 456 790 248 456 795 ÷ 2 = 61 728 395 124 228 397 + 1;
  • 61 728 395 124 228 397 ÷ 2 = 30 864 197 562 114 198 + 1;
  • 30 864 197 562 114 198 ÷ 2 = 15 432 098 781 057 099 + 0;
  • 15 432 098 781 057 099 ÷ 2 = 7 716 049 390 528 549 + 1;
  • 7 716 049 390 528 549 ÷ 2 = 3 858 024 695 264 274 + 1;
  • 3 858 024 695 264 274 ÷ 2 = 1 929 012 347 632 137 + 0;
  • 1 929 012 347 632 137 ÷ 2 = 964 506 173 816 068 + 1;
  • 964 506 173 816 068 ÷ 2 = 482 253 086 908 034 + 0;
  • 482 253 086 908 034 ÷ 2 = 241 126 543 454 017 + 0;
  • 241 126 543 454 017 ÷ 2 = 120 563 271 727 008 + 1;
  • 120 563 271 727 008 ÷ 2 = 60 281 635 863 504 + 0;
  • 60 281 635 863 504 ÷ 2 = 30 140 817 931 752 + 0;
  • 30 140 817 931 752 ÷ 2 = 15 070 408 965 876 + 0;
  • 15 070 408 965 876 ÷ 2 = 7 535 204 482 938 + 0;
  • 7 535 204 482 938 ÷ 2 = 3 767 602 241 469 + 0;
  • 3 767 602 241 469 ÷ 2 = 1 883 801 120 734 + 1;
  • 1 883 801 120 734 ÷ 2 = 941 900 560 367 + 0;
  • 941 900 560 367 ÷ 2 = 470 950 280 183 + 1;
  • 470 950 280 183 ÷ 2 = 235 475 140 091 + 1;
  • 235 475 140 091 ÷ 2 = 117 737 570 045 + 1;
  • 117 737 570 045 ÷ 2 = 58 868 785 022 + 1;
  • 58 868 785 022 ÷ 2 = 29 434 392 511 + 0;
  • 29 434 392 511 ÷ 2 = 14 717 196 255 + 1;
  • 14 717 196 255 ÷ 2 = 7 358 598 127 + 1;
  • 7 358 598 127 ÷ 2 = 3 679 299 063 + 1;
  • 3 679 299 063 ÷ 2 = 1 839 649 531 + 1;
  • 1 839 649 531 ÷ 2 = 919 824 765 + 1;
  • 919 824 765 ÷ 2 = 459 912 382 + 1;
  • 459 912 382 ÷ 2 = 229 956 191 + 0;
  • 229 956 191 ÷ 2 = 114 978 095 + 1;
  • 114 978 095 ÷ 2 = 57 489 047 + 1;
  • 57 489 047 ÷ 2 = 28 744 523 + 1;
  • 28 744 523 ÷ 2 = 14 372 261 + 1;
  • 14 372 261 ÷ 2 = 7 186 130 + 1;
  • 7 186 130 ÷ 2 = 3 593 065 + 0;
  • 3 593 065 ÷ 2 = 1 796 532 + 1;
  • 1 796 532 ÷ 2 = 898 266 + 0;
  • 898 266 ÷ 2 = 449 133 + 0;
  • 449 133 ÷ 2 = 224 566 + 1;
  • 224 566 ÷ 2 = 112 283 + 0;
  • 112 283 ÷ 2 = 56 141 + 1;
  • 56 141 ÷ 2 = 28 070 + 1;
  • 28 070 ÷ 2 = 14 035 + 0;
  • 14 035 ÷ 2 = 7 017 + 1;
  • 7 017 ÷ 2 = 3 508 + 1;
  • 3 508 ÷ 2 = 1 754 + 0;
  • 1 754 ÷ 2 = 877 + 0;
  • 877 ÷ 2 = 438 + 1;
  • 438 ÷ 2 = 219 + 0;
  • 219 ÷ 2 = 109 + 1;
  • 109 ÷ 2 = 54 + 1;
  • 54 ÷ 2 = 27 + 0;
  • 27 ÷ 2 = 13 + 1;
  • 13 ÷ 2 = 6 + 1;
  • 6 ÷ 2 = 3 + 0;
  • 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.


987 654 321 987 654 363(10) =


1101 1011 0100 1101 1010 0101 1111 0111 1110 1111 0100 0001 0010 1101 1011(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 59 positions to the left, so that only one non zero digit remains to the left of it:


987 654 321 987 654 363(10) =


1101 1011 0100 1101 1010 0101 1111 0111 1110 1111 0100 0001 0010 1101 1011(2) =


1101 1011 0100 1101 1010 0101 1111 0111 1110 1111 0100 0001 0010 1101 1011(2) × 20 =


1.1011 0110 1001 1011 0100 1011 1110 1111 1101 1110 1000 0010 0101 1011 011(2) × 259


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): 59


Mantissa (not normalized):
1.1011 0110 1001 1011 0100 1011 1110 1111 1101 1110 1000 0010 0101 1011 011


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


59 + 2(11-1) - 1 =


(59 + 1 023)(10) =


1 082(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;
  • 1 082 ÷ 2 = 541 + 0;
  • 541 ÷ 2 = 270 + 1;
  • 270 ÷ 2 = 135 + 0;
  • 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) =


1082(10) =


100 0011 1010(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. 1011 0110 1001 1011 0100 1011 1110 1111 1101 1110 1000 0010 0101 101 1011 =


1011 0110 1001 1011 0100 1011 1110 1111 1101 1110 1000 0010 0101


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 1010


Mantissa (52 bits) =
1011 0110 1001 1011 0100 1011 1110 1111 1101 1110 1000 0010 0101


The base ten decimal number 987 654 321 987 654 363 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0011 1010 - 1011 0110 1001 1011 0100 1011 1110 1111 1101 1110 1000 0010 0101

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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