16 142 028 064 602 201 376 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 16 142 028 064 602 201 376(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
16 142 028 064 602 201 376(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. 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;
  • 16 142 028 064 602 201 376 ÷ 2 = 8 071 014 032 301 100 688 + 0;
  • 8 071 014 032 301 100 688 ÷ 2 = 4 035 507 016 150 550 344 + 0;
  • 4 035 507 016 150 550 344 ÷ 2 = 2 017 753 508 075 275 172 + 0;
  • 2 017 753 508 075 275 172 ÷ 2 = 1 008 876 754 037 637 586 + 0;
  • 1 008 876 754 037 637 586 ÷ 2 = 504 438 377 018 818 793 + 0;
  • 504 438 377 018 818 793 ÷ 2 = 252 219 188 509 409 396 + 1;
  • 252 219 188 509 409 396 ÷ 2 = 126 109 594 254 704 698 + 0;
  • 126 109 594 254 704 698 ÷ 2 = 63 054 797 127 352 349 + 0;
  • 63 054 797 127 352 349 ÷ 2 = 31 527 398 563 676 174 + 1;
  • 31 527 398 563 676 174 ÷ 2 = 15 763 699 281 838 087 + 0;
  • 15 763 699 281 838 087 ÷ 2 = 7 881 849 640 919 043 + 1;
  • 7 881 849 640 919 043 ÷ 2 = 3 940 924 820 459 521 + 1;
  • 3 940 924 820 459 521 ÷ 2 = 1 970 462 410 229 760 + 1;
  • 1 970 462 410 229 760 ÷ 2 = 985 231 205 114 880 + 0;
  • 985 231 205 114 880 ÷ 2 = 492 615 602 557 440 + 0;
  • 492 615 602 557 440 ÷ 2 = 246 307 801 278 720 + 0;
  • 246 307 801 278 720 ÷ 2 = 123 153 900 639 360 + 0;
  • 123 153 900 639 360 ÷ 2 = 61 576 950 319 680 + 0;
  • 61 576 950 319 680 ÷ 2 = 30 788 475 159 840 + 0;
  • 30 788 475 159 840 ÷ 2 = 15 394 237 579 920 + 0;
  • 15 394 237 579 920 ÷ 2 = 7 697 118 789 960 + 0;
  • 7 697 118 789 960 ÷ 2 = 3 848 559 394 980 + 0;
  • 3 848 559 394 980 ÷ 2 = 1 924 279 697 490 + 0;
  • 1 924 279 697 490 ÷ 2 = 962 139 848 745 + 0;
  • 962 139 848 745 ÷ 2 = 481 069 924 372 + 1;
  • 481 069 924 372 ÷ 2 = 240 534 962 186 + 0;
  • 240 534 962 186 ÷ 2 = 120 267 481 093 + 0;
  • 120 267 481 093 ÷ 2 = 60 133 740 546 + 1;
  • 60 133 740 546 ÷ 2 = 30 066 870 273 + 0;
  • 30 066 870 273 ÷ 2 = 15 033 435 136 + 1;
  • 15 033 435 136 ÷ 2 = 7 516 717 568 + 0;
  • 7 516 717 568 ÷ 2 = 3 758 358 784 + 0;
  • 3 758 358 784 ÷ 2 = 1 879 179 392 + 0;
  • 1 879 179 392 ÷ 2 = 939 589 696 + 0;
  • 939 589 696 ÷ 2 = 469 794 848 + 0;
  • 469 794 848 ÷ 2 = 234 897 424 + 0;
  • 234 897 424 ÷ 2 = 117 448 712 + 0;
  • 117 448 712 ÷ 2 = 58 724 356 + 0;
  • 58 724 356 ÷ 2 = 29 362 178 + 0;
  • 29 362 178 ÷ 2 = 14 681 089 + 0;
  • 14 681 089 ÷ 2 = 7 340 544 + 1;
  • 7 340 544 ÷ 2 = 3 670 272 + 0;
  • 3 670 272 ÷ 2 = 1 835 136 + 0;
  • 1 835 136 ÷ 2 = 917 568 + 0;
  • 917 568 ÷ 2 = 458 784 + 0;
  • 458 784 ÷ 2 = 229 392 + 0;
  • 229 392 ÷ 2 = 114 696 + 0;
  • 114 696 ÷ 2 = 57 348 + 0;
  • 57 348 ÷ 2 = 28 674 + 0;
  • 28 674 ÷ 2 = 14 337 + 0;
  • 14 337 ÷ 2 = 7 168 + 1;
  • 7 168 ÷ 2 = 3 584 + 0;
  • 3 584 ÷ 2 = 1 792 + 0;
  • 1 792 ÷ 2 = 896 + 0;
  • 896 ÷ 2 = 448 + 0;
  • 448 ÷ 2 = 224 + 0;
  • 224 ÷ 2 = 112 + 0;
  • 112 ÷ 2 = 56 + 0;
  • 56 ÷ 2 = 28 + 0;
  • 28 ÷ 2 = 14 + 0;
  • 14 ÷ 2 = 7 + 0;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the positive number.

Take all the remainders starting from the bottom of the list constructed above.

16 142 028 064 602 201 376(10) =


1110 0000 0000 0100 0000 0001 0000 0000 0010 1001 0000 0000 0001 1101 0010 0000(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 63 positions to the left, so that only one non zero digit remains to the left of it:


16 142 028 064 602 201 376(10) =


1110 0000 0000 0100 0000 0001 0000 0000 0010 1001 0000 0000 0001 1101 0010 0000(2) =


1110 0000 0000 0100 0000 0001 0000 0000 0010 1001 0000 0000 0001 1101 0010 0000(2) × 20 =


1.1100 0000 0000 1000 0000 0010 0000 0000 0101 0010 0000 0000 0011 1010 0100 000(2) × 263


4. 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): 63


Mantissa (not normalized):
1.1100 0000 0000 1000 0000 0010 0000 0000 0101 0010 0000 0000 0011 1010 0100 000


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


63 + 2(11-1) - 1 =


(63 + 1 023)(10) =


1 086(10)


6. 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;
  • 1 086 ÷ 2 = 543 + 0;
  • 543 ÷ 2 = 271 + 1;
  • 271 ÷ 2 = 135 + 1;
  • 135 ÷ 2 = 67 + 1;
  • 67 ÷ 2 = 33 + 1;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

7. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1086(10) =


100 0011 1110(2)


8. 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. 1100 0000 0000 1000 0000 0010 0000 0000 0101 0010 0000 0000 0011 101 0010 0000 =


1100 0000 0000 1000 0000 0010 0000 0000 0101 0010 0000 0000 0011


9. 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 0011 1110


Mantissa (52 bits) =
1100 0000 0000 1000 0000 0010 0000 0000 0101 0010 0000 0000 0011


Decimal number 16 142 028 064 602 201 376 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0011 1110 - 1100 0000 0000 1000 0000 0010 0000 0000 0101 0010 0000 0000 0011


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