64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 4 833 058 800 576 644 579 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 4 833 058 800 576 644 579(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;
  • 4 833 058 800 576 644 579 ÷ 2 = 2 416 529 400 288 322 289 + 1;
  • 2 416 529 400 288 322 289 ÷ 2 = 1 208 264 700 144 161 144 + 1;
  • 1 208 264 700 144 161 144 ÷ 2 = 604 132 350 072 080 572 + 0;
  • 604 132 350 072 080 572 ÷ 2 = 302 066 175 036 040 286 + 0;
  • 302 066 175 036 040 286 ÷ 2 = 151 033 087 518 020 143 + 0;
  • 151 033 087 518 020 143 ÷ 2 = 75 516 543 759 010 071 + 1;
  • 75 516 543 759 010 071 ÷ 2 = 37 758 271 879 505 035 + 1;
  • 37 758 271 879 505 035 ÷ 2 = 18 879 135 939 752 517 + 1;
  • 18 879 135 939 752 517 ÷ 2 = 9 439 567 969 876 258 + 1;
  • 9 439 567 969 876 258 ÷ 2 = 4 719 783 984 938 129 + 0;
  • 4 719 783 984 938 129 ÷ 2 = 2 359 891 992 469 064 + 1;
  • 2 359 891 992 469 064 ÷ 2 = 1 179 945 996 234 532 + 0;
  • 1 179 945 996 234 532 ÷ 2 = 589 972 998 117 266 + 0;
  • 589 972 998 117 266 ÷ 2 = 294 986 499 058 633 + 0;
  • 294 986 499 058 633 ÷ 2 = 147 493 249 529 316 + 1;
  • 147 493 249 529 316 ÷ 2 = 73 746 624 764 658 + 0;
  • 73 746 624 764 658 ÷ 2 = 36 873 312 382 329 + 0;
  • 36 873 312 382 329 ÷ 2 = 18 436 656 191 164 + 1;
  • 18 436 656 191 164 ÷ 2 = 9 218 328 095 582 + 0;
  • 9 218 328 095 582 ÷ 2 = 4 609 164 047 791 + 0;
  • 4 609 164 047 791 ÷ 2 = 2 304 582 023 895 + 1;
  • 2 304 582 023 895 ÷ 2 = 1 152 291 011 947 + 1;
  • 1 152 291 011 947 ÷ 2 = 576 145 505 973 + 1;
  • 576 145 505 973 ÷ 2 = 288 072 752 986 + 1;
  • 288 072 752 986 ÷ 2 = 144 036 376 493 + 0;
  • 144 036 376 493 ÷ 2 = 72 018 188 246 + 1;
  • 72 018 188 246 ÷ 2 = 36 009 094 123 + 0;
  • 36 009 094 123 ÷ 2 = 18 004 547 061 + 1;
  • 18 004 547 061 ÷ 2 = 9 002 273 530 + 1;
  • 9 002 273 530 ÷ 2 = 4 501 136 765 + 0;
  • 4 501 136 765 ÷ 2 = 2 250 568 382 + 1;
  • 2 250 568 382 ÷ 2 = 1 125 284 191 + 0;
  • 1 125 284 191 ÷ 2 = 562 642 095 + 1;
  • 562 642 095 ÷ 2 = 281 321 047 + 1;
  • 281 321 047 ÷ 2 = 140 660 523 + 1;
  • 140 660 523 ÷ 2 = 70 330 261 + 1;
  • 70 330 261 ÷ 2 = 35 165 130 + 1;
  • 35 165 130 ÷ 2 = 17 582 565 + 0;
  • 17 582 565 ÷ 2 = 8 791 282 + 1;
  • 8 791 282 ÷ 2 = 4 395 641 + 0;
  • 4 395 641 ÷ 2 = 2 197 820 + 1;
  • 2 197 820 ÷ 2 = 1 098 910 + 0;
  • 1 098 910 ÷ 2 = 549 455 + 0;
  • 549 455 ÷ 2 = 274 727 + 1;
  • 274 727 ÷ 2 = 137 363 + 1;
  • 137 363 ÷ 2 = 68 681 + 1;
  • 68 681 ÷ 2 = 34 340 + 1;
  • 34 340 ÷ 2 = 17 170 + 0;
  • 17 170 ÷ 2 = 8 585 + 0;
  • 8 585 ÷ 2 = 4 292 + 1;
  • 4 292 ÷ 2 = 2 146 + 0;
  • 2 146 ÷ 2 = 1 073 + 0;
  • 1 073 ÷ 2 = 536 + 1;
  • 536 ÷ 2 = 268 + 0;
  • 268 ÷ 2 = 134 + 0;
  • 134 ÷ 2 = 67 + 0;
  • 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;

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

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


4 833 058 800 576 644 579(10) =


100 0011 0001 0010 0111 1001 0101 1111 0101 1010 1111 0010 0100 0101 1110 0011(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 62 positions to the left, so that only one non zero digit remains to the left of it:


4 833 058 800 576 644 579(10) =


100 0011 0001 0010 0111 1001 0101 1111 0101 1010 1111 0010 0100 0101 1110 0011(2) =


100 0011 0001 0010 0111 1001 0101 1111 0101 1010 1111 0010 0100 0101 1110 0011(2) × 20 =


1.0000 1100 0100 1001 1110 0101 0111 1101 0110 1011 1100 1001 0001 0111 1000 11(2) × 262


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): 62


Mantissa (not normalized):
1.0000 1100 0100 1001 1110 0101 0111 1101 0110 1011 1100 1001 0001 0111 1000 11


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


62 + 2(11-1) - 1 =


(62 + 1 023)(10) =


1 085(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;
  • 1 085 ÷ 2 = 542 + 1;
  • 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) =


1085(10) =


100 0011 1101(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. 0000 1100 0100 1001 1110 0101 0111 1101 0110 1011 1100 1001 0001 01 1110 0011 =


0000 1100 0100 1001 1110 0101 0111 1101 0110 1011 1100 1001 0001


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 1101


Mantissa (52 bits) =
0000 1100 0100 1001 1110 0101 0111 1101 0110 1011 1100 1001 0001


The base ten decimal number 4 833 058 800 576 644 579 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0011 1101 - 0000 1100 0100 1001 1110 0101 0111 1101 0110 1011 1100 1001 0001

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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