6 445 756 566 797 977.647 337 125 893 6 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 6 445 756 566 797 977.647 337 125 893 6(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
6 445 756 566 797 977.647 337 125 893 6(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: 6 445 756 566 797 977.
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;
  • 6 445 756 566 797 977 ÷ 2 = 3 222 878 283 398 988 + 1;
  • 3 222 878 283 398 988 ÷ 2 = 1 611 439 141 699 494 + 0;
  • 1 611 439 141 699 494 ÷ 2 = 805 719 570 849 747 + 0;
  • 805 719 570 849 747 ÷ 2 = 402 859 785 424 873 + 1;
  • 402 859 785 424 873 ÷ 2 = 201 429 892 712 436 + 1;
  • 201 429 892 712 436 ÷ 2 = 100 714 946 356 218 + 0;
  • 100 714 946 356 218 ÷ 2 = 50 357 473 178 109 + 0;
  • 50 357 473 178 109 ÷ 2 = 25 178 736 589 054 + 1;
  • 25 178 736 589 054 ÷ 2 = 12 589 368 294 527 + 0;
  • 12 589 368 294 527 ÷ 2 = 6 294 684 147 263 + 1;
  • 6 294 684 147 263 ÷ 2 = 3 147 342 073 631 + 1;
  • 3 147 342 073 631 ÷ 2 = 1 573 671 036 815 + 1;
  • 1 573 671 036 815 ÷ 2 = 786 835 518 407 + 1;
  • 786 835 518 407 ÷ 2 = 393 417 759 203 + 1;
  • 393 417 759 203 ÷ 2 = 196 708 879 601 + 1;
  • 196 708 879 601 ÷ 2 = 98 354 439 800 + 1;
  • 98 354 439 800 ÷ 2 = 49 177 219 900 + 0;
  • 49 177 219 900 ÷ 2 = 24 588 609 950 + 0;
  • 24 588 609 950 ÷ 2 = 12 294 304 975 + 0;
  • 12 294 304 975 ÷ 2 = 6 147 152 487 + 1;
  • 6 147 152 487 ÷ 2 = 3 073 576 243 + 1;
  • 3 073 576 243 ÷ 2 = 1 536 788 121 + 1;
  • 1 536 788 121 ÷ 2 = 768 394 060 + 1;
  • 768 394 060 ÷ 2 = 384 197 030 + 0;
  • 384 197 030 ÷ 2 = 192 098 515 + 0;
  • 192 098 515 ÷ 2 = 96 049 257 + 1;
  • 96 049 257 ÷ 2 = 48 024 628 + 1;
  • 48 024 628 ÷ 2 = 24 012 314 + 0;
  • 24 012 314 ÷ 2 = 12 006 157 + 0;
  • 12 006 157 ÷ 2 = 6 003 078 + 1;
  • 6 003 078 ÷ 2 = 3 001 539 + 0;
  • 3 001 539 ÷ 2 = 1 500 769 + 1;
  • 1 500 769 ÷ 2 = 750 384 + 1;
  • 750 384 ÷ 2 = 375 192 + 0;
  • 375 192 ÷ 2 = 187 596 + 0;
  • 187 596 ÷ 2 = 93 798 + 0;
  • 93 798 ÷ 2 = 46 899 + 0;
  • 46 899 ÷ 2 = 23 449 + 1;
  • 23 449 ÷ 2 = 11 724 + 1;
  • 11 724 ÷ 2 = 5 862 + 0;
  • 5 862 ÷ 2 = 2 931 + 0;
  • 2 931 ÷ 2 = 1 465 + 1;
  • 1 465 ÷ 2 = 732 + 1;
  • 732 ÷ 2 = 366 + 0;
  • 366 ÷ 2 = 183 + 0;
  • 183 ÷ 2 = 91 + 1;
  • 91 ÷ 2 = 45 + 1;
  • 45 ÷ 2 = 22 + 1;
  • 22 ÷ 2 = 11 + 0;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 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.

6 445 756 566 797 977(10) =


1 0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001(2)


3. Convert to binary (base 2) the fractional part: 0.647 337 125 893 6.

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) 0.647 337 125 893 6 × 2 = 1 + 0.294 674 251 787 2;
  • 2) 0.294 674 251 787 2 × 2 = 0 + 0.589 348 503 574 4;
  • 3) 0.589 348 503 574 4 × 2 = 1 + 0.178 697 007 148 8;
  • 4) 0.178 697 007 148 8 × 2 = 0 + 0.357 394 014 297 6;
  • 5) 0.357 394 014 297 6 × 2 = 0 + 0.714 788 028 595 2;
  • 6) 0.714 788 028 595 2 × 2 = 1 + 0.429 576 057 190 4;
  • 7) 0.429 576 057 190 4 × 2 = 0 + 0.859 152 114 380 8;
  • 8) 0.859 152 114 380 8 × 2 = 1 + 0.718 304 228 761 6;
  • 9) 0.718 304 228 761 6 × 2 = 1 + 0.436 608 457 523 2;
  • 10) 0.436 608 457 523 2 × 2 = 0 + 0.873 216 915 046 4;
  • 11) 0.873 216 915 046 4 × 2 = 1 + 0.746 433 830 092 8;
  • 12) 0.746 433 830 092 8 × 2 = 1 + 0.492 867 660 185 6;
  • 13) 0.492 867 660 185 6 × 2 = 0 + 0.985 735 320 371 2;
  • 14) 0.985 735 320 371 2 × 2 = 1 + 0.971 470 640 742 4;
  • 15) 0.971 470 640 742 4 × 2 = 1 + 0.942 941 281 484 8;
  • 16) 0.942 941 281 484 8 × 2 = 1 + 0.885 882 562 969 6;
  • 17) 0.885 882 562 969 6 × 2 = 1 + 0.771 765 125 939 2;
  • 18) 0.771 765 125 939 2 × 2 = 1 + 0.543 530 251 878 4;
  • 19) 0.543 530 251 878 4 × 2 = 1 + 0.087 060 503 756 8;
  • 20) 0.087 060 503 756 8 × 2 = 0 + 0.174 121 007 513 6;
  • 21) 0.174 121 007 513 6 × 2 = 0 + 0.348 242 015 027 2;
  • 22) 0.348 242 015 027 2 × 2 = 0 + 0.696 484 030 054 4;
  • 23) 0.696 484 030 054 4 × 2 = 1 + 0.392 968 060 108 8;
  • 24) 0.392 968 060 108 8 × 2 = 0 + 0.785 936 120 217 6;
  • 25) 0.785 936 120 217 6 × 2 = 1 + 0.571 872 240 435 2;
  • 26) 0.571 872 240 435 2 × 2 = 1 + 0.143 744 480 870 4;
  • 27) 0.143 744 480 870 4 × 2 = 0 + 0.287 488 961 740 8;
  • 28) 0.287 488 961 740 8 × 2 = 0 + 0.574 977 923 481 6;
  • 29) 0.574 977 923 481 6 × 2 = 1 + 0.149 955 846 963 2;
  • 30) 0.149 955 846 963 2 × 2 = 0 + 0.299 911 693 926 4;
  • 31) 0.299 911 693 926 4 × 2 = 0 + 0.599 823 387 852 8;
  • 32) 0.599 823 387 852 8 × 2 = 1 + 0.199 646 775 705 6;
  • 33) 0.199 646 775 705 6 × 2 = 0 + 0.399 293 551 411 2;
  • 34) 0.399 293 551 411 2 × 2 = 0 + 0.798 587 102 822 4;
  • 35) 0.798 587 102 822 4 × 2 = 1 + 0.597 174 205 644 8;
  • 36) 0.597 174 205 644 8 × 2 = 1 + 0.194 348 411 289 6;
  • 37) 0.194 348 411 289 6 × 2 = 0 + 0.388 696 822 579 2;
  • 38) 0.388 696 822 579 2 × 2 = 0 + 0.777 393 645 158 4;
  • 39) 0.777 393 645 158 4 × 2 = 1 + 0.554 787 290 316 8;
  • 40) 0.554 787 290 316 8 × 2 = 1 + 0.109 574 580 633 6;
  • 41) 0.109 574 580 633 6 × 2 = 0 + 0.219 149 161 267 2;
  • 42) 0.219 149 161 267 2 × 2 = 0 + 0.438 298 322 534 4;
  • 43) 0.438 298 322 534 4 × 2 = 0 + 0.876 596 645 068 8;
  • 44) 0.876 596 645 068 8 × 2 = 1 + 0.753 193 290 137 6;
  • 45) 0.753 193 290 137 6 × 2 = 1 + 0.506 386 580 275 2;
  • 46) 0.506 386 580 275 2 × 2 = 1 + 0.012 773 160 550 4;
  • 47) 0.012 773 160 550 4 × 2 = 0 + 0.025 546 321 100 8;
  • 48) 0.025 546 321 100 8 × 2 = 0 + 0.051 092 642 201 6;
  • 49) 0.051 092 642 201 6 × 2 = 0 + 0.102 185 284 403 2;
  • 50) 0.102 185 284 403 2 × 2 = 0 + 0.204 370 568 806 4;
  • 51) 0.204 370 568 806 4 × 2 = 0 + 0.408 741 137 612 8;
  • 52) 0.408 741 137 612 8 × 2 = 0 + 0.817 482 275 225 6;
  • 53) 0.817 482 275 225 6 × 2 = 1 + 0.634 964 550 451 2;

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:


0.647 337 125 893 6(10) =


0.1010 0101 1011 0111 1110 0010 1100 1001 0011 0011 0001 1100 0000 1(2)

5. Positive number before normalization:

6 445 756 566 797 977.647 337 125 893 6(10) =


1 0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001.1010 0101 1011 0111 1110 0010 1100 1001 0011 0011 0001 1100 0000 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 52 positions to the left, so that only one non zero digit remains to the left of it:


6 445 756 566 797 977.647 337 125 893 6(10) =


1 0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001.1010 0101 1011 0111 1110 0010 1100 1001 0011 0011 0001 1100 0000 1(2) =


1 0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001.1010 0101 1011 0111 1110 0010 1100 1001 0011 0011 0001 1100 0000 1(2) × 20 =


1.0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001 1010 0101 1011 0111 1110 0010 1100 1001 0011 0011 0001 1100 0000 1(2) × 252


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): 52


Mantissa (not normalized):
1.0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001 1010 0101 1011 0111 1110 0010 1100 1001 0011 0011 0001 1100 0000 1


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


52 + 2(11-1) - 1 =


(52 + 1 023)(10) =


1 075(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;
  • 1 075 ÷ 2 = 537 + 1;
  • 537 ÷ 2 = 268 + 1;
  • 268 ÷ 2 = 134 + 0;
  • 134 ÷ 2 = 67 + 0;
  • 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;

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) =


1075(10) =


100 0011 0011(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. 0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001 1 0100 1011 0110 1111 1100 0101 1001 0010 0110 0110 0011 1000 0001 =


0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001


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 0011 0011


Mantissa (52 bits) =
0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001


Decimal number 6 445 756 566 797 977.647 337 125 893 6 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0011 0011 - 0110 1110 0110 0110 0001 1010 0110 0111 1000 1111 1110 1001 1001


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