64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 4 609 434 218 613 702 634 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 4 609 434 218 613 702 634(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;
  • 4 609 434 218 613 702 634 ÷ 2 = 2 304 717 109 306 851 317 + 0;
  • 2 304 717 109 306 851 317 ÷ 2 = 1 152 358 554 653 425 658 + 1;
  • 1 152 358 554 653 425 658 ÷ 2 = 576 179 277 326 712 829 + 0;
  • 576 179 277 326 712 829 ÷ 2 = 288 089 638 663 356 414 + 1;
  • 288 089 638 663 356 414 ÷ 2 = 144 044 819 331 678 207 + 0;
  • 144 044 819 331 678 207 ÷ 2 = 72 022 409 665 839 103 + 1;
  • 72 022 409 665 839 103 ÷ 2 = 36 011 204 832 919 551 + 1;
  • 36 011 204 832 919 551 ÷ 2 = 18 005 602 416 459 775 + 1;
  • 18 005 602 416 459 775 ÷ 2 = 9 002 801 208 229 887 + 1;
  • 9 002 801 208 229 887 ÷ 2 = 4 501 400 604 114 943 + 1;
  • 4 501 400 604 114 943 ÷ 2 = 2 250 700 302 057 471 + 1;
  • 2 250 700 302 057 471 ÷ 2 = 1 125 350 151 028 735 + 1;
  • 1 125 350 151 028 735 ÷ 2 = 562 675 075 514 367 + 1;
  • 562 675 075 514 367 ÷ 2 = 281 337 537 757 183 + 1;
  • 281 337 537 757 183 ÷ 2 = 140 668 768 878 591 + 1;
  • 140 668 768 878 591 ÷ 2 = 70 334 384 439 295 + 1;
  • 70 334 384 439 295 ÷ 2 = 35 167 192 219 647 + 1;
  • 35 167 192 219 647 ÷ 2 = 17 583 596 109 823 + 1;
  • 17 583 596 109 823 ÷ 2 = 8 791 798 054 911 + 1;
  • 8 791 798 054 911 ÷ 2 = 4 395 899 027 455 + 1;
  • 4 395 899 027 455 ÷ 2 = 2 197 949 513 727 + 1;
  • 2 197 949 513 727 ÷ 2 = 1 098 974 756 863 + 1;
  • 1 098 974 756 863 ÷ 2 = 549 487 378 431 + 1;
  • 549 487 378 431 ÷ 2 = 274 743 689 215 + 1;
  • 274 743 689 215 ÷ 2 = 137 371 844 607 + 1;
  • 137 371 844 607 ÷ 2 = 68 685 922 303 + 1;
  • 68 685 922 303 ÷ 2 = 34 342 961 151 + 1;
  • 34 342 961 151 ÷ 2 = 17 171 480 575 + 1;
  • 17 171 480 575 ÷ 2 = 8 585 740 287 + 1;
  • 8 585 740 287 ÷ 2 = 4 292 870 143 + 1;
  • 4 292 870 143 ÷ 2 = 2 146 435 071 + 1;
  • 2 146 435 071 ÷ 2 = 1 073 217 535 + 1;
  • 1 073 217 535 ÷ 2 = 536 608 767 + 1;
  • 536 608 767 ÷ 2 = 268 304 383 + 1;
  • 268 304 383 ÷ 2 = 134 152 191 + 1;
  • 134 152 191 ÷ 2 = 67 076 095 + 1;
  • 67 076 095 ÷ 2 = 33 538 047 + 1;
  • 33 538 047 ÷ 2 = 16 769 023 + 1;
  • 16 769 023 ÷ 2 = 8 384 511 + 1;
  • 8 384 511 ÷ 2 = 4 192 255 + 1;
  • 4 192 255 ÷ 2 = 2 096 127 + 1;
  • 2 096 127 ÷ 2 = 1 048 063 + 1;
  • 1 048 063 ÷ 2 = 524 031 + 1;
  • 524 031 ÷ 2 = 262 015 + 1;
  • 262 015 ÷ 2 = 131 007 + 1;
  • 131 007 ÷ 2 = 65 503 + 1;
  • 65 503 ÷ 2 = 32 751 + 1;
  • 32 751 ÷ 2 = 16 375 + 1;
  • 16 375 ÷ 2 = 8 187 + 1;
  • 8 187 ÷ 2 = 4 093 + 1;
  • 4 093 ÷ 2 = 2 046 + 1;
  • 2 046 ÷ 2 = 1 023 + 0;
  • 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.


4 609 434 218 613 702 634(10) =


11 1111 1111 0111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1110 1010(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 61 positions to the left, so that only one non zero digit remains to the left of it:


4 609 434 218 613 702 634(10) =


11 1111 1111 0111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1110 1010(2) =


11 1111 1111 0111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1110 1010(2) × 20 =


1.1111 1111 1011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 0101 0(2) × 261


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): 61


Mantissa (not normalized):
1.1111 1111 1011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 0101 0


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


61 + 2(11-1) - 1 =


(61 + 1 023)(10) =


1 084(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;
  • 1 084 ÷ 2 = 542 + 0;
  • 542 ÷ 2 = 271 + 0;
  • 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) =


1084(10) =


100 0011 1100(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 1011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111 1 1110 1010 =


1111 1111 1011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111


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 1100


Mantissa (52 bits) =
1111 1111 1011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111


The base ten decimal number 4 609 434 218 613 702 634 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0011 1100 - 1111 1111 1011 1111 1111 1111 1111 1111 1111 1111 1111 1111 1111

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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