1.370 000 000 000 000 106 903 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.370 000 000 000 000 106 903(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
1.370 000 000 000 000 106 903(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: 0.370 000 000 000 000 106 903.

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) 0.370 000 000 000 000 106 903 × 2 = 0 + 0.740 000 000 000 000 213 806;
  • 2) 0.740 000 000 000 000 213 806 × 2 = 1 + 0.480 000 000 000 000 427 612;
  • 3) 0.480 000 000 000 000 427 612 × 2 = 0 + 0.960 000 000 000 000 855 224;
  • 4) 0.960 000 000 000 000 855 224 × 2 = 1 + 0.920 000 000 000 001 710 448;
  • 5) 0.920 000 000 000 001 710 448 × 2 = 1 + 0.840 000 000 000 003 420 896;
  • 6) 0.840 000 000 000 003 420 896 × 2 = 1 + 0.680 000 000 000 006 841 792;
  • 7) 0.680 000 000 000 006 841 792 × 2 = 1 + 0.360 000 000 000 013 683 584;
  • 8) 0.360 000 000 000 013 683 584 × 2 = 0 + 0.720 000 000 000 027 367 168;
  • 9) 0.720 000 000 000 027 367 168 × 2 = 1 + 0.440 000 000 000 054 734 336;
  • 10) 0.440 000 000 000 054 734 336 × 2 = 0 + 0.880 000 000 000 109 468 672;
  • 11) 0.880 000 000 000 109 468 672 × 2 = 1 + 0.760 000 000 000 218 937 344;
  • 12) 0.760 000 000 000 218 937 344 × 2 = 1 + 0.520 000 000 000 437 874 688;
  • 13) 0.520 000 000 000 437 874 688 × 2 = 1 + 0.040 000 000 000 875 749 376;
  • 14) 0.040 000 000 000 875 749 376 × 2 = 0 + 0.080 000 000 001 751 498 752;
  • 15) 0.080 000 000 001 751 498 752 × 2 = 0 + 0.160 000 000 003 502 997 504;
  • 16) 0.160 000 000 003 502 997 504 × 2 = 0 + 0.320 000 000 007 005 995 008;
  • 17) 0.320 000 000 007 005 995 008 × 2 = 0 + 0.640 000 000 014 011 990 016;
  • 18) 0.640 000 000 014 011 990 016 × 2 = 1 + 0.280 000 000 028 023 980 032;
  • 19) 0.280 000 000 028 023 980 032 × 2 = 0 + 0.560 000 000 056 047 960 064;
  • 20) 0.560 000 000 056 047 960 064 × 2 = 1 + 0.120 000 000 112 095 920 128;
  • 21) 0.120 000 000 112 095 920 128 × 2 = 0 + 0.240 000 000 224 191 840 256;
  • 22) 0.240 000 000 224 191 840 256 × 2 = 0 + 0.480 000 000 448 383 680 512;
  • 23) 0.480 000 000 448 383 680 512 × 2 = 0 + 0.960 000 000 896 767 361 024;
  • 24) 0.960 000 000 896 767 361 024 × 2 = 1 + 0.920 000 001 793 534 722 048;
  • 25) 0.920 000 001 793 534 722 048 × 2 = 1 + 0.840 000 003 587 069 444 096;
  • 26) 0.840 000 003 587 069 444 096 × 2 = 1 + 0.680 000 007 174 138 888 192;
  • 27) 0.680 000 007 174 138 888 192 × 2 = 1 + 0.360 000 014 348 277 776 384;
  • 28) 0.360 000 014 348 277 776 384 × 2 = 0 + 0.720 000 028 696 555 552 768;
  • 29) 0.720 000 028 696 555 552 768 × 2 = 1 + 0.440 000 057 393 111 105 536;
  • 30) 0.440 000 057 393 111 105 536 × 2 = 0 + 0.880 000 114 786 222 211 072;
  • 31) 0.880 000 114 786 222 211 072 × 2 = 1 + 0.760 000 229 572 444 422 144;
  • 32) 0.760 000 229 572 444 422 144 × 2 = 1 + 0.520 000 459 144 888 844 288;
  • 33) 0.520 000 459 144 888 844 288 × 2 = 1 + 0.040 000 918 289 777 688 576;
  • 34) 0.040 000 918 289 777 688 576 × 2 = 0 + 0.080 001 836 579 555 377 152;
  • 35) 0.080 001 836 579 555 377 152 × 2 = 0 + 0.160 003 673 159 110 754 304;
  • 36) 0.160 003 673 159 110 754 304 × 2 = 0 + 0.320 007 346 318 221 508 608;
  • 37) 0.320 007 346 318 221 508 608 × 2 = 0 + 0.640 014 692 636 443 017 216;
  • 38) 0.640 014 692 636 443 017 216 × 2 = 1 + 0.280 029 385 272 886 034 432;
  • 39) 0.280 029 385 272 886 034 432 × 2 = 0 + 0.560 058 770 545 772 068 864;
  • 40) 0.560 058 770 545 772 068 864 × 2 = 1 + 0.120 117 541 091 544 137 728;
  • 41) 0.120 117 541 091 544 137 728 × 2 = 0 + 0.240 235 082 183 088 275 456;
  • 42) 0.240 235 082 183 088 275 456 × 2 = 0 + 0.480 470 164 366 176 550 912;
  • 43) 0.480 470 164 366 176 550 912 × 2 = 0 + 0.960 940 328 732 353 101 824;
  • 44) 0.960 940 328 732 353 101 824 × 2 = 1 + 0.921 880 657 464 706 203 648;
  • 45) 0.921 880 657 464 706 203 648 × 2 = 1 + 0.843 761 314 929 412 407 296;
  • 46) 0.843 761 314 929 412 407 296 × 2 = 1 + 0.687 522 629 858 824 814 592;
  • 47) 0.687 522 629 858 824 814 592 × 2 = 1 + 0.375 045 259 717 649 629 184;
  • 48) 0.375 045 259 717 649 629 184 × 2 = 0 + 0.750 090 519 435 299 258 368;
  • 49) 0.750 090 519 435 299 258 368 × 2 = 1 + 0.500 181 038 870 598 516 736;
  • 50) 0.500 181 038 870 598 516 736 × 2 = 1 + 0.000 362 077 741 197 033 472;
  • 51) 0.000 362 077 741 197 033 472 × 2 = 0 + 0.000 724 155 482 394 066 944;
  • 52) 0.000 724 155 482 394 066 944 × 2 = 0 + 0.001 448 310 964 788 133 888;
  • 53) 0.001 448 310 964 788 133 888 × 2 = 0 + 0.002 896 621 929 576 267 776;

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:


0.370 000 000 000 000 106 903(10) =


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

5. Positive number before normalization:

1.370 000 000 000 000 106 903(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:


1.370 000 000 000 000 106 903(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 1.370 000 000 000 000 106 903 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