6 428 594 841 965 559 778 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 6 428 594 841 965 559 778(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
6 428 594 841 965 559 778(10) to 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;
  • 6 428 594 841 965 559 778 ÷ 2 = 3 214 297 420 982 779 889 + 0;
  • 3 214 297 420 982 779 889 ÷ 2 = 1 607 148 710 491 389 944 + 1;
  • 1 607 148 710 491 389 944 ÷ 2 = 803 574 355 245 694 972 + 0;
  • 803 574 355 245 694 972 ÷ 2 = 401 787 177 622 847 486 + 0;
  • 401 787 177 622 847 486 ÷ 2 = 200 893 588 811 423 743 + 0;
  • 200 893 588 811 423 743 ÷ 2 = 100 446 794 405 711 871 + 1;
  • 100 446 794 405 711 871 ÷ 2 = 50 223 397 202 855 935 + 1;
  • 50 223 397 202 855 935 ÷ 2 = 25 111 698 601 427 967 + 1;
  • 25 111 698 601 427 967 ÷ 2 = 12 555 849 300 713 983 + 1;
  • 12 555 849 300 713 983 ÷ 2 = 6 277 924 650 356 991 + 1;
  • 6 277 924 650 356 991 ÷ 2 = 3 138 962 325 178 495 + 1;
  • 3 138 962 325 178 495 ÷ 2 = 1 569 481 162 589 247 + 1;
  • 1 569 481 162 589 247 ÷ 2 = 784 740 581 294 623 + 1;
  • 784 740 581 294 623 ÷ 2 = 392 370 290 647 311 + 1;
  • 392 370 290 647 311 ÷ 2 = 196 185 145 323 655 + 1;
  • 196 185 145 323 655 ÷ 2 = 98 092 572 661 827 + 1;
  • 98 092 572 661 827 ÷ 2 = 49 046 286 330 913 + 1;
  • 49 046 286 330 913 ÷ 2 = 24 523 143 165 456 + 1;
  • 24 523 143 165 456 ÷ 2 = 12 261 571 582 728 + 0;
  • 12 261 571 582 728 ÷ 2 = 6 130 785 791 364 + 0;
  • 6 130 785 791 364 ÷ 2 = 3 065 392 895 682 + 0;
  • 3 065 392 895 682 ÷ 2 = 1 532 696 447 841 + 0;
  • 1 532 696 447 841 ÷ 2 = 766 348 223 920 + 1;
  • 766 348 223 920 ÷ 2 = 383 174 111 960 + 0;
  • 383 174 111 960 ÷ 2 = 191 587 055 980 + 0;
  • 191 587 055 980 ÷ 2 = 95 793 527 990 + 0;
  • 95 793 527 990 ÷ 2 = 47 896 763 995 + 0;
  • 47 896 763 995 ÷ 2 = 23 948 381 997 + 1;
  • 23 948 381 997 ÷ 2 = 11 974 190 998 + 1;
  • 11 974 190 998 ÷ 2 = 5 987 095 499 + 0;
  • 5 987 095 499 ÷ 2 = 2 993 547 749 + 1;
  • 2 993 547 749 ÷ 2 = 1 496 773 874 + 1;
  • 1 496 773 874 ÷ 2 = 748 386 937 + 0;
  • 748 386 937 ÷ 2 = 374 193 468 + 1;
  • 374 193 468 ÷ 2 = 187 096 734 + 0;
  • 187 096 734 ÷ 2 = 93 548 367 + 0;
  • 93 548 367 ÷ 2 = 46 774 183 + 1;
  • 46 774 183 ÷ 2 = 23 387 091 + 1;
  • 23 387 091 ÷ 2 = 11 693 545 + 1;
  • 11 693 545 ÷ 2 = 5 846 772 + 1;
  • 5 846 772 ÷ 2 = 2 923 386 + 0;
  • 2 923 386 ÷ 2 = 1 461 693 + 0;
  • 1 461 693 ÷ 2 = 730 846 + 1;
  • 730 846 ÷ 2 = 365 423 + 0;
  • 365 423 ÷ 2 = 182 711 + 1;
  • 182 711 ÷ 2 = 91 355 + 1;
  • 91 355 ÷ 2 = 45 677 + 1;
  • 45 677 ÷ 2 = 22 838 + 1;
  • 22 838 ÷ 2 = 11 419 + 0;
  • 11 419 ÷ 2 = 5 709 + 1;
  • 5 709 ÷ 2 = 2 854 + 1;
  • 2 854 ÷ 2 = 1 427 + 0;
  • 1 427 ÷ 2 = 713 + 1;
  • 713 ÷ 2 = 356 + 1;
  • 356 ÷ 2 = 178 + 0;
  • 178 ÷ 2 = 89 + 0;
  • 89 ÷ 2 = 44 + 1;
  • 44 ÷ 2 = 22 + 0;
  • 22 ÷ 2 = 11 + 0;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 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.

6 428 594 841 965 559 778(10) =


101 1001 0011 0110 1111 0100 1111 0010 1101 1000 0100 0011 1111 1111 1110 0010(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:


6 428 594 841 965 559 778(10) =


101 1001 0011 0110 1111 0100 1111 0010 1101 1000 0100 0011 1111 1111 1110 0010(2) =


101 1001 0011 0110 1111 0100 1111 0010 1101 1000 0100 0011 1111 1111 1110 0010(2) × 20 =


1.0110 0100 1101 1011 1101 0011 1100 1011 0110 0001 0000 1111 1111 1111 1000 10(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):
1.0110 0100 1101 1011 1101 0011 1100 1011 0110 0001 0000 1111 1111 1111 1000 10


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. 0110 0100 1101 1011 1101 0011 1100 1011 0110 0001 0000 1111 1111 11 1110 0010 =


0110 0100 1101 1011 1101 0011 1100 1011 0110 0001 0000 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 1101


Mantissa (52 bits) =
0110 0100 1101 1011 1101 0011 1100 1011 0110 0001 0000 1111 1111


Decimal number 6 428 594 841 965 559 778 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0011 1101 - 0110 0100 1101 1011 1101 0011 1100 1011 0110 0001 0000 1111 1111


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