1.370 000 000 000 000 106 812 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.370 000 000 000 000 106 812(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
1.370 000 000 000 000 106 812(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: 0.370 000 000 000 000 106 812.

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) 0.370 000 000 000 000 106 812 × 2 = 0 + 0.740 000 000 000 000 213 624;
  • 2) 0.740 000 000 000 000 213 624 × 2 = 1 + 0.480 000 000 000 000 427 248;
  • 3) 0.480 000 000 000 000 427 248 × 2 = 0 + 0.960 000 000 000 000 854 496;
  • 4) 0.960 000 000 000 000 854 496 × 2 = 1 + 0.920 000 000 000 001 708 992;
  • 5) 0.920 000 000 000 001 708 992 × 2 = 1 + 0.840 000 000 000 003 417 984;
  • 6) 0.840 000 000 000 003 417 984 × 2 = 1 + 0.680 000 000 000 006 835 968;
  • 7) 0.680 000 000 000 006 835 968 × 2 = 1 + 0.360 000 000 000 013 671 936;
  • 8) 0.360 000 000 000 013 671 936 × 2 = 0 + 0.720 000 000 000 027 343 872;
  • 9) 0.720 000 000 000 027 343 872 × 2 = 1 + 0.440 000 000 000 054 687 744;
  • 10) 0.440 000 000 000 054 687 744 × 2 = 0 + 0.880 000 000 000 109 375 488;
  • 11) 0.880 000 000 000 109 375 488 × 2 = 1 + 0.760 000 000 000 218 750 976;
  • 12) 0.760 000 000 000 218 750 976 × 2 = 1 + 0.520 000 000 000 437 501 952;
  • 13) 0.520 000 000 000 437 501 952 × 2 = 1 + 0.040 000 000 000 875 003 904;
  • 14) 0.040 000 000 000 875 003 904 × 2 = 0 + 0.080 000 000 001 750 007 808;
  • 15) 0.080 000 000 001 750 007 808 × 2 = 0 + 0.160 000 000 003 500 015 616;
  • 16) 0.160 000 000 003 500 015 616 × 2 = 0 + 0.320 000 000 007 000 031 232;
  • 17) 0.320 000 000 007 000 031 232 × 2 = 0 + 0.640 000 000 014 000 062 464;
  • 18) 0.640 000 000 014 000 062 464 × 2 = 1 + 0.280 000 000 028 000 124 928;
  • 19) 0.280 000 000 028 000 124 928 × 2 = 0 + 0.560 000 000 056 000 249 856;
  • 20) 0.560 000 000 056 000 249 856 × 2 = 1 + 0.120 000 000 112 000 499 712;
  • 21) 0.120 000 000 112 000 499 712 × 2 = 0 + 0.240 000 000 224 000 999 424;
  • 22) 0.240 000 000 224 000 999 424 × 2 = 0 + 0.480 000 000 448 001 998 848;
  • 23) 0.480 000 000 448 001 998 848 × 2 = 0 + 0.960 000 000 896 003 997 696;
  • 24) 0.960 000 000 896 003 997 696 × 2 = 1 + 0.920 000 001 792 007 995 392;
  • 25) 0.920 000 001 792 007 995 392 × 2 = 1 + 0.840 000 003 584 015 990 784;
  • 26) 0.840 000 003 584 015 990 784 × 2 = 1 + 0.680 000 007 168 031 981 568;
  • 27) 0.680 000 007 168 031 981 568 × 2 = 1 + 0.360 000 014 336 063 963 136;
  • 28) 0.360 000 014 336 063 963 136 × 2 = 0 + 0.720 000 028 672 127 926 272;
  • 29) 0.720 000 028 672 127 926 272 × 2 = 1 + 0.440 000 057 344 255 852 544;
  • 30) 0.440 000 057 344 255 852 544 × 2 = 0 + 0.880 000 114 688 511 705 088;
  • 31) 0.880 000 114 688 511 705 088 × 2 = 1 + 0.760 000 229 377 023 410 176;
  • 32) 0.760 000 229 377 023 410 176 × 2 = 1 + 0.520 000 458 754 046 820 352;
  • 33) 0.520 000 458 754 046 820 352 × 2 = 1 + 0.040 000 917 508 093 640 704;
  • 34) 0.040 000 917 508 093 640 704 × 2 = 0 + 0.080 001 835 016 187 281 408;
  • 35) 0.080 001 835 016 187 281 408 × 2 = 0 + 0.160 003 670 032 374 562 816;
  • 36) 0.160 003 670 032 374 562 816 × 2 = 0 + 0.320 007 340 064 749 125 632;
  • 37) 0.320 007 340 064 749 125 632 × 2 = 0 + 0.640 014 680 129 498 251 264;
  • 38) 0.640 014 680 129 498 251 264 × 2 = 1 + 0.280 029 360 258 996 502 528;
  • 39) 0.280 029 360 258 996 502 528 × 2 = 0 + 0.560 058 720 517 993 005 056;
  • 40) 0.560 058 720 517 993 005 056 × 2 = 1 + 0.120 117 441 035 986 010 112;
  • 41) 0.120 117 441 035 986 010 112 × 2 = 0 + 0.240 234 882 071 972 020 224;
  • 42) 0.240 234 882 071 972 020 224 × 2 = 0 + 0.480 469 764 143 944 040 448;
  • 43) 0.480 469 764 143 944 040 448 × 2 = 0 + 0.960 939 528 287 888 080 896;
  • 44) 0.960 939 528 287 888 080 896 × 2 = 1 + 0.921 879 056 575 776 161 792;
  • 45) 0.921 879 056 575 776 161 792 × 2 = 1 + 0.843 758 113 151 552 323 584;
  • 46) 0.843 758 113 151 552 323 584 × 2 = 1 + 0.687 516 226 303 104 647 168;
  • 47) 0.687 516 226 303 104 647 168 × 2 = 1 + 0.375 032 452 606 209 294 336;
  • 48) 0.375 032 452 606 209 294 336 × 2 = 0 + 0.750 064 905 212 418 588 672;
  • 49) 0.750 064 905 212 418 588 672 × 2 = 1 + 0.500 129 810 424 837 177 344;
  • 50) 0.500 129 810 424 837 177 344 × 2 = 1 + 0.000 259 620 849 674 354 688;
  • 51) 0.000 259 620 849 674 354 688 × 2 = 0 + 0.000 519 241 699 348 709 376;
  • 52) 0.000 519 241 699 348 709 376 × 2 = 0 + 0.001 038 483 398 697 418 752;
  • 53) 0.001 038 483 398 697 418 752 × 2 = 0 + 0.002 076 966 797 394 837 504;

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:


0.370 000 000 000 000 106 812(10) =


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

5. Positive number before normalization:

1.370 000 000 000 000 106 812(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:


1.370 000 000 000 000 106 812(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 1.370 000 000 000 000 106 812 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