64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 1.000 000 000 000 000 222 044 604 9 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 1.000 000 000 000 000 222 044 604 9(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. 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: 0.000 000 000 000 000 222 044 604 9.

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) 0.000 000 000 000 000 222 044 604 9 × 2 = 0 + 0.000 000 000 000 000 444 089 209 8;
  • 2) 0.000 000 000 000 000 444 089 209 8 × 2 = 0 + 0.000 000 000 000 000 888 178 419 6;
  • 3) 0.000 000 000 000 000 888 178 419 6 × 2 = 0 + 0.000 000 000 000 001 776 356 839 2;
  • 4) 0.000 000 000 000 001 776 356 839 2 × 2 = 0 + 0.000 000 000 000 003 552 713 678 4;
  • 5) 0.000 000 000 000 003 552 713 678 4 × 2 = 0 + 0.000 000 000 000 007 105 427 356 8;
  • 6) 0.000 000 000 000 007 105 427 356 8 × 2 = 0 + 0.000 000 000 000 014 210 854 713 6;
  • 7) 0.000 000 000 000 014 210 854 713 6 × 2 = 0 + 0.000 000 000 000 028 421 709 427 2;
  • 8) 0.000 000 000 000 028 421 709 427 2 × 2 = 0 + 0.000 000 000 000 056 843 418 854 4;
  • 9) 0.000 000 000 000 056 843 418 854 4 × 2 = 0 + 0.000 000 000 000 113 686 837 708 8;
  • 10) 0.000 000 000 000 113 686 837 708 8 × 2 = 0 + 0.000 000 000 000 227 373 675 417 6;
  • 11) 0.000 000 000 000 227 373 675 417 6 × 2 = 0 + 0.000 000 000 000 454 747 350 835 2;
  • 12) 0.000 000 000 000 454 747 350 835 2 × 2 = 0 + 0.000 000 000 000 909 494 701 670 4;
  • 13) 0.000 000 000 000 909 494 701 670 4 × 2 = 0 + 0.000 000 000 001 818 989 403 340 8;
  • 14) 0.000 000 000 001 818 989 403 340 8 × 2 = 0 + 0.000 000 000 003 637 978 806 681 6;
  • 15) 0.000 000 000 003 637 978 806 681 6 × 2 = 0 + 0.000 000 000 007 275 957 613 363 2;
  • 16) 0.000 000 000 007 275 957 613 363 2 × 2 = 0 + 0.000 000 000 014 551 915 226 726 4;
  • 17) 0.000 000 000 014 551 915 226 726 4 × 2 = 0 + 0.000 000 000 029 103 830 453 452 8;
  • 18) 0.000 000 000 029 103 830 453 452 8 × 2 = 0 + 0.000 000 000 058 207 660 906 905 6;
  • 19) 0.000 000 000 058 207 660 906 905 6 × 2 = 0 + 0.000 000 000 116 415 321 813 811 2;
  • 20) 0.000 000 000 116 415 321 813 811 2 × 2 = 0 + 0.000 000 000 232 830 643 627 622 4;
  • 21) 0.000 000 000 232 830 643 627 622 4 × 2 = 0 + 0.000 000 000 465 661 287 255 244 8;
  • 22) 0.000 000 000 465 661 287 255 244 8 × 2 = 0 + 0.000 000 000 931 322 574 510 489 6;
  • 23) 0.000 000 000 931 322 574 510 489 6 × 2 = 0 + 0.000 000 001 862 645 149 020 979 2;
  • 24) 0.000 000 001 862 645 149 020 979 2 × 2 = 0 + 0.000 000 003 725 290 298 041 958 4;
  • 25) 0.000 000 003 725 290 298 041 958 4 × 2 = 0 + 0.000 000 007 450 580 596 083 916 8;
  • 26) 0.000 000 007 450 580 596 083 916 8 × 2 = 0 + 0.000 000 014 901 161 192 167 833 6;
  • 27) 0.000 000 014 901 161 192 167 833 6 × 2 = 0 + 0.000 000 029 802 322 384 335 667 2;
  • 28) 0.000 000 029 802 322 384 335 667 2 × 2 = 0 + 0.000 000 059 604 644 768 671 334 4;
  • 29) 0.000 000 059 604 644 768 671 334 4 × 2 = 0 + 0.000 000 119 209 289 537 342 668 8;
  • 30) 0.000 000 119 209 289 537 342 668 8 × 2 = 0 + 0.000 000 238 418 579 074 685 337 6;
  • 31) 0.000 000 238 418 579 074 685 337 6 × 2 = 0 + 0.000 000 476 837 158 149 370 675 2;
  • 32) 0.000 000 476 837 158 149 370 675 2 × 2 = 0 + 0.000 000 953 674 316 298 741 350 4;
  • 33) 0.000 000 953 674 316 298 741 350 4 × 2 = 0 + 0.000 001 907 348 632 597 482 700 8;
  • 34) 0.000 001 907 348 632 597 482 700 8 × 2 = 0 + 0.000 003 814 697 265 194 965 401 6;
  • 35) 0.000 003 814 697 265 194 965 401 6 × 2 = 0 + 0.000 007 629 394 530 389 930 803 2;
  • 36) 0.000 007 629 394 530 389 930 803 2 × 2 = 0 + 0.000 015 258 789 060 779 861 606 4;
  • 37) 0.000 015 258 789 060 779 861 606 4 × 2 = 0 + 0.000 030 517 578 121 559 723 212 8;
  • 38) 0.000 030 517 578 121 559 723 212 8 × 2 = 0 + 0.000 061 035 156 243 119 446 425 6;
  • 39) 0.000 061 035 156 243 119 446 425 6 × 2 = 0 + 0.000 122 070 312 486 238 892 851 2;
  • 40) 0.000 122 070 312 486 238 892 851 2 × 2 = 0 + 0.000 244 140 624 972 477 785 702 4;
  • 41) 0.000 244 140 624 972 477 785 702 4 × 2 = 0 + 0.000 488 281 249 944 955 571 404 8;
  • 42) 0.000 488 281 249 944 955 571 404 8 × 2 = 0 + 0.000 976 562 499 889 911 142 809 6;
  • 43) 0.000 976 562 499 889 911 142 809 6 × 2 = 0 + 0.001 953 124 999 779 822 285 619 2;
  • 44) 0.001 953 124 999 779 822 285 619 2 × 2 = 0 + 0.003 906 249 999 559 644 571 238 4;
  • 45) 0.003 906 249 999 559 644 571 238 4 × 2 = 0 + 0.007 812 499 999 119 289 142 476 8;
  • 46) 0.007 812 499 999 119 289 142 476 8 × 2 = 0 + 0.015 624 999 998 238 578 284 953 6;
  • 47) 0.015 624 999 998 238 578 284 953 6 × 2 = 0 + 0.031 249 999 996 477 156 569 907 2;
  • 48) 0.031 249 999 996 477 156 569 907 2 × 2 = 0 + 0.062 499 999 992 954 313 139 814 4;
  • 49) 0.062 499 999 992 954 313 139 814 4 × 2 = 0 + 0.124 999 999 985 908 626 279 628 8;
  • 50) 0.124 999 999 985 908 626 279 628 8 × 2 = 0 + 0.249 999 999 971 817 252 559 257 6;
  • 51) 0.249 999 999 971 817 252 559 257 6 × 2 = 0 + 0.499 999 999 943 634 505 118 515 2;
  • 52) 0.499 999 999 943 634 505 118 515 2 × 2 = 0 + 0.999 999 999 887 269 010 237 030 4;
  • 53) 0.999 999 999 887 269 010 237 030 4 × 2 = 1 + 0.999 999 999 774 538 020 474 060 8;

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...)


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:


0.000 000 000 000 000 222 044 604 9(10) =


0.0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1(2)


5. Positive number before normalization:

1.000 000 000 000 000 222 044 604 9(10) =


1.0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1(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:


1.000 000 000 000 000 222 044 604 9(10) =


1.0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1(2) =


1.0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1(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 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1


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 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 1 =


0000 0000 0000 0000 0000 0000 0000 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 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000


The base ten decimal number 1.000 000 000 000 000 222 044 604 9 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 011 1111 1111 - 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000 0000

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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