8 800.883 411 943 536 074 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 8 800.883 411 943 536 074(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
8 800.883 411 943 536 074(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. First, convert to binary (in base 2) the integer part: 8 800.
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;
  • 8 800 ÷ 2 = 4 400 + 0;
  • 4 400 ÷ 2 = 2 200 + 0;
  • 2 200 ÷ 2 = 1 100 + 0;
  • 1 100 ÷ 2 = 550 + 0;
  • 550 ÷ 2 = 275 + 0;
  • 275 ÷ 2 = 137 + 1;
  • 137 ÷ 2 = 68 + 1;
  • 68 ÷ 2 = 34 + 0;
  • 34 ÷ 2 = 17 + 0;
  • 17 ÷ 2 = 8 + 1;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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.

8 800(10) =


10 0010 0110 0000(2)


3. Convert to binary (base 2) the fractional part: 0.883 411 943 536 074.

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) 0.883 411 943 536 074 × 2 = 1 + 0.766 823 887 072 148;
  • 2) 0.766 823 887 072 148 × 2 = 1 + 0.533 647 774 144 296;
  • 3) 0.533 647 774 144 296 × 2 = 1 + 0.067 295 548 288 592;
  • 4) 0.067 295 548 288 592 × 2 = 0 + 0.134 591 096 577 184;
  • 5) 0.134 591 096 577 184 × 2 = 0 + 0.269 182 193 154 368;
  • 6) 0.269 182 193 154 368 × 2 = 0 + 0.538 364 386 308 736;
  • 7) 0.538 364 386 308 736 × 2 = 1 + 0.076 728 772 617 472;
  • 8) 0.076 728 772 617 472 × 2 = 0 + 0.153 457 545 234 944;
  • 9) 0.153 457 545 234 944 × 2 = 0 + 0.306 915 090 469 888;
  • 10) 0.306 915 090 469 888 × 2 = 0 + 0.613 830 180 939 776;
  • 11) 0.613 830 180 939 776 × 2 = 1 + 0.227 660 361 879 552;
  • 12) 0.227 660 361 879 552 × 2 = 0 + 0.455 320 723 759 104;
  • 13) 0.455 320 723 759 104 × 2 = 0 + 0.910 641 447 518 208;
  • 14) 0.910 641 447 518 208 × 2 = 1 + 0.821 282 895 036 416;
  • 15) 0.821 282 895 036 416 × 2 = 1 + 0.642 565 790 072 832;
  • 16) 0.642 565 790 072 832 × 2 = 1 + 0.285 131 580 145 664;
  • 17) 0.285 131 580 145 664 × 2 = 0 + 0.570 263 160 291 328;
  • 18) 0.570 263 160 291 328 × 2 = 1 + 0.140 526 320 582 656;
  • 19) 0.140 526 320 582 656 × 2 = 0 + 0.281 052 641 165 312;
  • 20) 0.281 052 641 165 312 × 2 = 0 + 0.562 105 282 330 624;
  • 21) 0.562 105 282 330 624 × 2 = 1 + 0.124 210 564 661 248;
  • 22) 0.124 210 564 661 248 × 2 = 0 + 0.248 421 129 322 496;
  • 23) 0.248 421 129 322 496 × 2 = 0 + 0.496 842 258 644 992;
  • 24) 0.496 842 258 644 992 × 2 = 0 + 0.993 684 517 289 984;
  • 25) 0.993 684 517 289 984 × 2 = 1 + 0.987 369 034 579 968;
  • 26) 0.987 369 034 579 968 × 2 = 1 + 0.974 738 069 159 936;
  • 27) 0.974 738 069 159 936 × 2 = 1 + 0.949 476 138 319 872;
  • 28) 0.949 476 138 319 872 × 2 = 1 + 0.898 952 276 639 744;
  • 29) 0.898 952 276 639 744 × 2 = 1 + 0.797 904 553 279 488;
  • 30) 0.797 904 553 279 488 × 2 = 1 + 0.595 809 106 558 976;
  • 31) 0.595 809 106 558 976 × 2 = 1 + 0.191 618 213 117 952;
  • 32) 0.191 618 213 117 952 × 2 = 0 + 0.383 236 426 235 904;
  • 33) 0.383 236 426 235 904 × 2 = 0 + 0.766 472 852 471 808;
  • 34) 0.766 472 852 471 808 × 2 = 1 + 0.532 945 704 943 616;
  • 35) 0.532 945 704 943 616 × 2 = 1 + 0.065 891 409 887 232;
  • 36) 0.065 891 409 887 232 × 2 = 0 + 0.131 782 819 774 464;
  • 37) 0.131 782 819 774 464 × 2 = 0 + 0.263 565 639 548 928;
  • 38) 0.263 565 639 548 928 × 2 = 0 + 0.527 131 279 097 856;
  • 39) 0.527 131 279 097 856 × 2 = 1 + 0.054 262 558 195 712;
  • 40) 0.054 262 558 195 712 × 2 = 0 + 0.108 525 116 391 424;
  • 41) 0.108 525 116 391 424 × 2 = 0 + 0.217 050 232 782 848;
  • 42) 0.217 050 232 782 848 × 2 = 0 + 0.434 100 465 565 696;
  • 43) 0.434 100 465 565 696 × 2 = 0 + 0.868 200 931 131 392;
  • 44) 0.868 200 931 131 392 × 2 = 1 + 0.736 401 862 262 784;
  • 45) 0.736 401 862 262 784 × 2 = 1 + 0.472 803 724 525 568;
  • 46) 0.472 803 724 525 568 × 2 = 0 + 0.945 607 449 051 136;
  • 47) 0.945 607 449 051 136 × 2 = 1 + 0.891 214 898 102 272;
  • 48) 0.891 214 898 102 272 × 2 = 1 + 0.782 429 796 204 544;
  • 49) 0.782 429 796 204 544 × 2 = 1 + 0.564 859 592 409 088;
  • 50) 0.564 859 592 409 088 × 2 = 1 + 0.129 719 184 818 176;
  • 51) 0.129 719 184 818 176 × 2 = 0 + 0.259 438 369 636 352;
  • 52) 0.259 438 369 636 352 × 2 = 0 + 0.518 876 739 272 704;
  • 53) 0.518 876 739 272 704 × 2 = 1 + 0.037 753 478 545 408;

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 - the converted number we get in the end will be just a very good approximation of the initial one).


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:


0.883 411 943 536 074(10) =


0.1110 0010 0010 0111 0100 1000 1111 1110 0110 0010 0001 1011 1100 1(2)

5. Positive number before normalization:

8 800.883 411 943 536 074(10) =


10 0010 0110 0000.1110 0010 0010 0111 0100 1000 1111 1110 0110 0010 0001 1011 1100 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 13 positions to the left, so that only one non zero digit remains to the left of it:


8 800.883 411 943 536 074(10) =


10 0010 0110 0000.1110 0010 0010 0111 0100 1000 1111 1110 0110 0010 0001 1011 1100 1(2) =


10 0010 0110 0000.1110 0010 0010 0111 0100 1000 1111 1110 0110 0010 0001 1011 1100 1(2) × 20 =


1.0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0001 0000 1101 1110 01(2) × 213


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): 13


Mantissa (not normalized):
1.0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0001 0000 1101 1110 01


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


13 + 2(11-1) - 1 =


(13 + 1 023)(10) =


1 036(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;
  • 1 036 ÷ 2 = 518 + 0;
  • 518 ÷ 2 = 259 + 0;
  • 259 ÷ 2 = 129 + 1;
  • 129 ÷ 2 = 64 + 1;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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) =


1036(10) =


100 0000 1100(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. 0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0001 00 0011 0111 1001 =


0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0001


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) =
100 0000 1100


Mantissa (52 bits) =
0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0001


Decimal number 8 800.883 411 943 536 074 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 1100 - 0001 0011 0000 0111 0001 0001 0011 1010 0100 0111 1111 0011 0001

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