1.370 000 000 000 000 106 96 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.370 000 000 000 000 106 96(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
1.370 000 000 000 000 106 96(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: 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: 0.370 000 000 000 000 106 96.

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) 0.370 000 000 000 000 106 96 × 2 = 0 + 0.740 000 000 000 000 213 92;
  • 2) 0.740 000 000 000 000 213 92 × 2 = 1 + 0.480 000 000 000 000 427 84;
  • 3) 0.480 000 000 000 000 427 84 × 2 = 0 + 0.960 000 000 000 000 855 68;
  • 4) 0.960 000 000 000 000 855 68 × 2 = 1 + 0.920 000 000 000 001 711 36;
  • 5) 0.920 000 000 000 001 711 36 × 2 = 1 + 0.840 000 000 000 003 422 72;
  • 6) 0.840 000 000 000 003 422 72 × 2 = 1 + 0.680 000 000 000 006 845 44;
  • 7) 0.680 000 000 000 006 845 44 × 2 = 1 + 0.360 000 000 000 013 690 88;
  • 8) 0.360 000 000 000 013 690 88 × 2 = 0 + 0.720 000 000 000 027 381 76;
  • 9) 0.720 000 000 000 027 381 76 × 2 = 1 + 0.440 000 000 000 054 763 52;
  • 10) 0.440 000 000 000 054 763 52 × 2 = 0 + 0.880 000 000 000 109 527 04;
  • 11) 0.880 000 000 000 109 527 04 × 2 = 1 + 0.760 000 000 000 219 054 08;
  • 12) 0.760 000 000 000 219 054 08 × 2 = 1 + 0.520 000 000 000 438 108 16;
  • 13) 0.520 000 000 000 438 108 16 × 2 = 1 + 0.040 000 000 000 876 216 32;
  • 14) 0.040 000 000 000 876 216 32 × 2 = 0 + 0.080 000 000 001 752 432 64;
  • 15) 0.080 000 000 001 752 432 64 × 2 = 0 + 0.160 000 000 003 504 865 28;
  • 16) 0.160 000 000 003 504 865 28 × 2 = 0 + 0.320 000 000 007 009 730 56;
  • 17) 0.320 000 000 007 009 730 56 × 2 = 0 + 0.640 000 000 014 019 461 12;
  • 18) 0.640 000 000 014 019 461 12 × 2 = 1 + 0.280 000 000 028 038 922 24;
  • 19) 0.280 000 000 028 038 922 24 × 2 = 0 + 0.560 000 000 056 077 844 48;
  • 20) 0.560 000 000 056 077 844 48 × 2 = 1 + 0.120 000 000 112 155 688 96;
  • 21) 0.120 000 000 112 155 688 96 × 2 = 0 + 0.240 000 000 224 311 377 92;
  • 22) 0.240 000 000 224 311 377 92 × 2 = 0 + 0.480 000 000 448 622 755 84;
  • 23) 0.480 000 000 448 622 755 84 × 2 = 0 + 0.960 000 000 897 245 511 68;
  • 24) 0.960 000 000 897 245 511 68 × 2 = 1 + 0.920 000 001 794 491 023 36;
  • 25) 0.920 000 001 794 491 023 36 × 2 = 1 + 0.840 000 003 588 982 046 72;
  • 26) 0.840 000 003 588 982 046 72 × 2 = 1 + 0.680 000 007 177 964 093 44;
  • 27) 0.680 000 007 177 964 093 44 × 2 = 1 + 0.360 000 014 355 928 186 88;
  • 28) 0.360 000 014 355 928 186 88 × 2 = 0 + 0.720 000 028 711 856 373 76;
  • 29) 0.720 000 028 711 856 373 76 × 2 = 1 + 0.440 000 057 423 712 747 52;
  • 30) 0.440 000 057 423 712 747 52 × 2 = 0 + 0.880 000 114 847 425 495 04;
  • 31) 0.880 000 114 847 425 495 04 × 2 = 1 + 0.760 000 229 694 850 990 08;
  • 32) 0.760 000 229 694 850 990 08 × 2 = 1 + 0.520 000 459 389 701 980 16;
  • 33) 0.520 000 459 389 701 980 16 × 2 = 1 + 0.040 000 918 779 403 960 32;
  • 34) 0.040 000 918 779 403 960 32 × 2 = 0 + 0.080 001 837 558 807 920 64;
  • 35) 0.080 001 837 558 807 920 64 × 2 = 0 + 0.160 003 675 117 615 841 28;
  • 36) 0.160 003 675 117 615 841 28 × 2 = 0 + 0.320 007 350 235 231 682 56;
  • 37) 0.320 007 350 235 231 682 56 × 2 = 0 + 0.640 014 700 470 463 365 12;
  • 38) 0.640 014 700 470 463 365 12 × 2 = 1 + 0.280 029 400 940 926 730 24;
  • 39) 0.280 029 400 940 926 730 24 × 2 = 0 + 0.560 058 801 881 853 460 48;
  • 40) 0.560 058 801 881 853 460 48 × 2 = 1 + 0.120 117 603 763 706 920 96;
  • 41) 0.120 117 603 763 706 920 96 × 2 = 0 + 0.240 235 207 527 413 841 92;
  • 42) 0.240 235 207 527 413 841 92 × 2 = 0 + 0.480 470 415 054 827 683 84;
  • 43) 0.480 470 415 054 827 683 84 × 2 = 0 + 0.960 940 830 109 655 367 68;
  • 44) 0.960 940 830 109 655 367 68 × 2 = 1 + 0.921 881 660 219 310 735 36;
  • 45) 0.921 881 660 219 310 735 36 × 2 = 1 + 0.843 763 320 438 621 470 72;
  • 46) 0.843 763 320 438 621 470 72 × 2 = 1 + 0.687 526 640 877 242 941 44;
  • 47) 0.687 526 640 877 242 941 44 × 2 = 1 + 0.375 053 281 754 485 882 88;
  • 48) 0.375 053 281 754 485 882 88 × 2 = 0 + 0.750 106 563 508 971 765 76;
  • 49) 0.750 106 563 508 971 765 76 × 2 = 1 + 0.500 213 127 017 943 531 52;
  • 50) 0.500 213 127 017 943 531 52 × 2 = 1 + 0.000 426 254 035 887 063 04;
  • 51) 0.000 426 254 035 887 063 04 × 2 = 0 + 0.000 852 508 071 774 126 08;
  • 52) 0.000 852 508 071 774 126 08 × 2 = 0 + 0.001 705 016 143 548 252 16;
  • 53) 0.001 705 016 143 548 252 16 × 2 = 0 + 0.003 410 032 287 096 504 32;

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:


0.370 000 000 000 000 106 96(10) =


0.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0(2)

5. Positive number before normalization:

1.370 000 000 000 000 106 96(10) =


1.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0(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:


1.370 000 000 000 000 106 96(10) =


1.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0(2) =


1.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0(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):
1.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0


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. 0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0 =


0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100


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) =
0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100


Decimal number 1.370 000 000 000 000 106 96 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1111 - 0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100


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