8 590 983 296.015 626 672 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 8 590 983 296.015 626 672(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
8 590 983 296.015 626 672(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: 8 590 983 296.
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;
  • 8 590 983 296 ÷ 2 = 4 295 491 648 + 0;
  • 4 295 491 648 ÷ 2 = 2 147 745 824 + 0;
  • 2 147 745 824 ÷ 2 = 1 073 872 912 + 0;
  • 1 073 872 912 ÷ 2 = 536 936 456 + 0;
  • 536 936 456 ÷ 2 = 268 468 228 + 0;
  • 268 468 228 ÷ 2 = 134 234 114 + 0;
  • 134 234 114 ÷ 2 = 67 117 057 + 0;
  • 67 117 057 ÷ 2 = 33 558 528 + 1;
  • 33 558 528 ÷ 2 = 16 779 264 + 0;
  • 16 779 264 ÷ 2 = 8 389 632 + 0;
  • 8 389 632 ÷ 2 = 4 194 816 + 0;
  • 4 194 816 ÷ 2 = 2 097 408 + 0;
  • 2 097 408 ÷ 2 = 1 048 704 + 0;
  • 1 048 704 ÷ 2 = 524 352 + 0;
  • 524 352 ÷ 2 = 262 176 + 0;
  • 262 176 ÷ 2 = 131 088 + 0;
  • 131 088 ÷ 2 = 65 544 + 0;
  • 65 544 ÷ 2 = 32 772 + 0;
  • 32 772 ÷ 2 = 16 386 + 0;
  • 16 386 ÷ 2 = 8 193 + 0;
  • 8 193 ÷ 2 = 4 096 + 1;
  • 4 096 ÷ 2 = 2 048 + 0;
  • 2 048 ÷ 2 = 1 024 + 0;
  • 1 024 ÷ 2 = 512 + 0;
  • 512 ÷ 2 = 256 + 0;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 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;

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.

8 590 983 296(10) =


10 0000 0000 0001 0000 0000 0000 1000 0000(2)


3. Convert to binary (base 2) the fractional part: 0.015 626 672.

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) 0.015 626 672 × 2 = 0 + 0.031 253 344;
  • 2) 0.031 253 344 × 2 = 0 + 0.062 506 688;
  • 3) 0.062 506 688 × 2 = 0 + 0.125 013 376;
  • 4) 0.125 013 376 × 2 = 0 + 0.250 026 752;
  • 5) 0.250 026 752 × 2 = 0 + 0.500 053 504;
  • 6) 0.500 053 504 × 2 = 1 + 0.000 107 008;
  • 7) 0.000 107 008 × 2 = 0 + 0.000 214 016;
  • 8) 0.000 214 016 × 2 = 0 + 0.000 428 032;
  • 9) 0.000 428 032 × 2 = 0 + 0.000 856 064;
  • 10) 0.000 856 064 × 2 = 0 + 0.001 712 128;
  • 11) 0.001 712 128 × 2 = 0 + 0.003 424 256;
  • 12) 0.003 424 256 × 2 = 0 + 0.006 848 512;
  • 13) 0.006 848 512 × 2 = 0 + 0.013 697 024;
  • 14) 0.013 697 024 × 2 = 0 + 0.027 394 048;
  • 15) 0.027 394 048 × 2 = 0 + 0.054 788 096;
  • 16) 0.054 788 096 × 2 = 0 + 0.109 576 192;
  • 17) 0.109 576 192 × 2 = 0 + 0.219 152 384;
  • 18) 0.219 152 384 × 2 = 0 + 0.438 304 768;
  • 19) 0.438 304 768 × 2 = 0 + 0.876 609 536;
  • 20) 0.876 609 536 × 2 = 1 + 0.753 219 072;
  • 21) 0.753 219 072 × 2 = 1 + 0.506 438 144;
  • 22) 0.506 438 144 × 2 = 1 + 0.012 876 288;
  • 23) 0.012 876 288 × 2 = 0 + 0.025 752 576;
  • 24) 0.025 752 576 × 2 = 0 + 0.051 505 152;
  • 25) 0.051 505 152 × 2 = 0 + 0.103 010 304;
  • 26) 0.103 010 304 × 2 = 0 + 0.206 020 608;
  • 27) 0.206 020 608 × 2 = 0 + 0.412 041 216;
  • 28) 0.412 041 216 × 2 = 0 + 0.824 082 432;
  • 29) 0.824 082 432 × 2 = 1 + 0.648 164 864;
  • 30) 0.648 164 864 × 2 = 1 + 0.296 329 728;
  • 31) 0.296 329 728 × 2 = 0 + 0.592 659 456;
  • 32) 0.592 659 456 × 2 = 1 + 0.185 318 912;
  • 33) 0.185 318 912 × 2 = 0 + 0.370 637 824;
  • 34) 0.370 637 824 × 2 = 0 + 0.741 275 648;
  • 35) 0.741 275 648 × 2 = 1 + 0.482 551 296;
  • 36) 0.482 551 296 × 2 = 0 + 0.965 102 592;
  • 37) 0.965 102 592 × 2 = 1 + 0.930 205 184;
  • 38) 0.930 205 184 × 2 = 1 + 0.860 410 368;
  • 39) 0.860 410 368 × 2 = 1 + 0.720 820 736;
  • 40) 0.720 820 736 × 2 = 1 + 0.441 641 472;
  • 41) 0.441 641 472 × 2 = 0 + 0.883 282 944;
  • 42) 0.883 282 944 × 2 = 1 + 0.766 565 888;
  • 43) 0.766 565 888 × 2 = 1 + 0.533 131 776;
  • 44) 0.533 131 776 × 2 = 1 + 0.066 263 552;
  • 45) 0.066 263 552 × 2 = 0 + 0.132 527 104;
  • 46) 0.132 527 104 × 2 = 0 + 0.265 054 208;
  • 47) 0.265 054 208 × 2 = 0 + 0.530 108 416;
  • 48) 0.530 108 416 × 2 = 1 + 0.060 216 832;
  • 49) 0.060 216 832 × 2 = 0 + 0.120 433 664;
  • 50) 0.120 433 664 × 2 = 0 + 0.240 867 328;
  • 51) 0.240 867 328 × 2 = 0 + 0.481 734 656;
  • 52) 0.481 734 656 × 2 = 0 + 0.963 469 312;
  • 53) 0.963 469 312 × 2 = 1 + 0.926 938 624;

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:


0.015 626 672(10) =


0.0000 0100 0000 0000 0001 1100 0000 1101 0010 1111 0111 0001 0000 1(2)

5. Positive number before normalization:

8 590 983 296.015 626 672(10) =


10 0000 0000 0001 0000 0000 0000 1000 0000.0000 0100 0000 0000 0001 1100 0000 1101 0010 1111 0111 0001 0000 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 33 positions to the left, so that only one non zero digit remains to the left of it:


8 590 983 296.015 626 672(10) =


10 0000 0000 0001 0000 0000 0000 1000 0000.0000 0100 0000 0000 0001 1100 0000 1101 0010 1111 0111 0001 0000 1(2) =


10 0000 0000 0001 0000 0000 0000 1000 0000.0000 0100 0000 0000 0001 1100 0000 1101 0010 1111 0111 0001 0000 1(2) × 20 =


1.0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000 1110 0000 0110 1001 0111 1011 1000 1000 01(2) × 233


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): 33


Mantissa (not normalized):
1.0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000 1110 0000 0110 1001 0111 1011 1000 1000 01


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


33 + 2(11-1) - 1 =


(33 + 1 023)(10) =


1 056(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;
  • 1 056 ÷ 2 = 528 + 0;
  • 528 ÷ 2 = 264 + 0;
  • 264 ÷ 2 = 132 + 0;
  • 132 ÷ 2 = 66 + 0;
  • 66 ÷ 2 = 33 + 0;
  • 33 ÷ 2 = 16 + 1;
  • 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) =


1056(10) =


100 0010 0000(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. 0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000 11 1000 0001 1010 0101 1110 1110 0010 0001 =


0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000


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 0010 0000


Mantissa (52 bits) =
0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000


Decimal number 8 590 983 296.015 626 672 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0010 0000 - 0000 0000 0000 1000 0000 0000 0100 0000 0000 0010 0000 0000 0000


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