1.117 587 089 538 691 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.117 587 089 538 691(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
1.117 587 089 538 691(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: 0.117 587 089 538 691.

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) 0.117 587 089 538 691 × 2 = 0 + 0.235 174 179 077 382;
  • 2) 0.235 174 179 077 382 × 2 = 0 + 0.470 348 358 154 764;
  • 3) 0.470 348 358 154 764 × 2 = 0 + 0.940 696 716 309 528;
  • 4) 0.940 696 716 309 528 × 2 = 1 + 0.881 393 432 619 056;
  • 5) 0.881 393 432 619 056 × 2 = 1 + 0.762 786 865 238 112;
  • 6) 0.762 786 865 238 112 × 2 = 1 + 0.525 573 730 476 224;
  • 7) 0.525 573 730 476 224 × 2 = 1 + 0.051 147 460 952 448;
  • 8) 0.051 147 460 952 448 × 2 = 0 + 0.102 294 921 904 896;
  • 9) 0.102 294 921 904 896 × 2 = 0 + 0.204 589 843 809 792;
  • 10) 0.204 589 843 809 792 × 2 = 0 + 0.409 179 687 619 584;
  • 11) 0.409 179 687 619 584 × 2 = 0 + 0.818 359 375 239 168;
  • 12) 0.818 359 375 239 168 × 2 = 1 + 0.636 718 750 478 336;
  • 13) 0.636 718 750 478 336 × 2 = 1 + 0.273 437 500 956 672;
  • 14) 0.273 437 500 956 672 × 2 = 0 + 0.546 875 001 913 344;
  • 15) 0.546 875 001 913 344 × 2 = 1 + 0.093 750 003 826 688;
  • 16) 0.093 750 003 826 688 × 2 = 0 + 0.187 500 007 653 376;
  • 17) 0.187 500 007 653 376 × 2 = 0 + 0.375 000 015 306 752;
  • 18) 0.375 000 015 306 752 × 2 = 0 + 0.750 000 030 613 504;
  • 19) 0.750 000 030 613 504 × 2 = 1 + 0.500 000 061 227 008;
  • 20) 0.500 000 061 227 008 × 2 = 1 + 0.000 000 122 454 016;
  • 21) 0.000 000 122 454 016 × 2 = 0 + 0.000 000 244 908 032;
  • 22) 0.000 000 244 908 032 × 2 = 0 + 0.000 000 489 816 064;
  • 23) 0.000 000 489 816 064 × 2 = 0 + 0.000 000 979 632 128;
  • 24) 0.000 000 979 632 128 × 2 = 0 + 0.000 001 959 264 256;
  • 25) 0.000 001 959 264 256 × 2 = 0 + 0.000 003 918 528 512;
  • 26) 0.000 003 918 528 512 × 2 = 0 + 0.000 007 837 057 024;
  • 27) 0.000 007 837 057 024 × 2 = 0 + 0.000 015 674 114 048;
  • 28) 0.000 015 674 114 048 × 2 = 0 + 0.000 031 348 228 096;
  • 29) 0.000 031 348 228 096 × 2 = 0 + 0.000 062 696 456 192;
  • 30) 0.000 062 696 456 192 × 2 = 0 + 0.000 125 392 912 384;
  • 31) 0.000 125 392 912 384 × 2 = 0 + 0.000 250 785 824 768;
  • 32) 0.000 250 785 824 768 × 2 = 0 + 0.000 501 571 649 536;
  • 33) 0.000 501 571 649 536 × 2 = 0 + 0.001 003 143 299 072;
  • 34) 0.001 003 143 299 072 × 2 = 0 + 0.002 006 286 598 144;
  • 35) 0.002 006 286 598 144 × 2 = 0 + 0.004 012 573 196 288;
  • 36) 0.004 012 573 196 288 × 2 = 0 + 0.008 025 146 392 576;
  • 37) 0.008 025 146 392 576 × 2 = 0 + 0.016 050 292 785 152;
  • 38) 0.016 050 292 785 152 × 2 = 0 + 0.032 100 585 570 304;
  • 39) 0.032 100 585 570 304 × 2 = 0 + 0.064 201 171 140 608;
  • 40) 0.064 201 171 140 608 × 2 = 0 + 0.128 402 342 281 216;
  • 41) 0.128 402 342 281 216 × 2 = 0 + 0.256 804 684 562 432;
  • 42) 0.256 804 684 562 432 × 2 = 0 + 0.513 609 369 124 864;
  • 43) 0.513 609 369 124 864 × 2 = 1 + 0.027 218 738 249 728;
  • 44) 0.027 218 738 249 728 × 2 = 0 + 0.054 437 476 499 456;
  • 45) 0.054 437 476 499 456 × 2 = 0 + 0.108 874 952 998 912;
  • 46) 0.108 874 952 998 912 × 2 = 0 + 0.217 749 905 997 824;
  • 47) 0.217 749 905 997 824 × 2 = 0 + 0.435 499 811 995 648;
  • 48) 0.435 499 811 995 648 × 2 = 0 + 0.870 999 623 991 296;
  • 49) 0.870 999 623 991 296 × 2 = 1 + 0.741 999 247 982 592;
  • 50) 0.741 999 247 982 592 × 2 = 1 + 0.483 998 495 965 184;
  • 51) 0.483 998 495 965 184 × 2 = 0 + 0.967 996 991 930 368;
  • 52) 0.967 996 991 930 368 × 2 = 1 + 0.935 993 983 860 736;
  • 53) 0.935 993 983 860 736 × 2 = 1 + 0.871 987 967 721 472;

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:


0.117 587 089 538 691(10) =


0.0001 1110 0001 1010 0011 0000 0000 0000 0000 0000 0010 0000 1101 1(2)

5. Positive number before normalization:

1.117 587 089 538 691(10) =


1.0001 1110 0001 1010 0011 0000 0000 0000 0000 0000 0010 0000 1101 1(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:


1.117 587 089 538 691(10) =


1.0001 1110 0001 1010 0011 0000 0000 0000 0000 0000 0010 0000 1101 1(2) =


1.0001 1110 0001 1010 0011 0000 0000 0000 0000 0000 0010 0000 1101 1(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):
1.0001 1110 0001 1010 0011 0000 0000 0000 0000 0000 0010 0000 1101 1


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. 0001 1110 0001 1010 0011 0000 0000 0000 0000 0000 0010 0000 1101 1 =


0001 1110 0001 1010 0011 0000 0000 0000 0000 0000 0010 0000 1101


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) =
0001 1110 0001 1010 0011 0000 0000 0000 0000 0000 0010 0000 1101


Decimal number 1.117 587 089 538 691 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1111 - 0001 1110 0001 1010 0011 0000 0000 0000 0000 0000 0010 0000 1101


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