6.022 140 857 102 310 87 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 6.022 140 857 102 310 87(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
6.022 140 857 102 310 87(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.
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 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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(10) =


110(2)


3. Convert to binary (base 2) the fractional part: 0.022 140 857 102 310 87.

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) 0.022 140 857 102 310 87 × 2 = 0 + 0.044 281 714 204 621 74;
  • 2) 0.044 281 714 204 621 74 × 2 = 0 + 0.088 563 428 409 243 48;
  • 3) 0.088 563 428 409 243 48 × 2 = 0 + 0.177 126 856 818 486 96;
  • 4) 0.177 126 856 818 486 96 × 2 = 0 + 0.354 253 713 636 973 92;
  • 5) 0.354 253 713 636 973 92 × 2 = 0 + 0.708 507 427 273 947 84;
  • 6) 0.708 507 427 273 947 84 × 2 = 1 + 0.417 014 854 547 895 68;
  • 7) 0.417 014 854 547 895 68 × 2 = 0 + 0.834 029 709 095 791 36;
  • 8) 0.834 029 709 095 791 36 × 2 = 1 + 0.668 059 418 191 582 72;
  • 9) 0.668 059 418 191 582 72 × 2 = 1 + 0.336 118 836 383 165 44;
  • 10) 0.336 118 836 383 165 44 × 2 = 0 + 0.672 237 672 766 330 88;
  • 11) 0.672 237 672 766 330 88 × 2 = 1 + 0.344 475 345 532 661 76;
  • 12) 0.344 475 345 532 661 76 × 2 = 0 + 0.688 950 691 065 323 52;
  • 13) 0.688 950 691 065 323 52 × 2 = 1 + 0.377 901 382 130 647 04;
  • 14) 0.377 901 382 130 647 04 × 2 = 0 + 0.755 802 764 261 294 08;
  • 15) 0.755 802 764 261 294 08 × 2 = 1 + 0.511 605 528 522 588 16;
  • 16) 0.511 605 528 522 588 16 × 2 = 1 + 0.023 211 057 045 176 32;
  • 17) 0.023 211 057 045 176 32 × 2 = 0 + 0.046 422 114 090 352 64;
  • 18) 0.046 422 114 090 352 64 × 2 = 0 + 0.092 844 228 180 705 28;
  • 19) 0.092 844 228 180 705 28 × 2 = 0 + 0.185 688 456 361 410 56;
  • 20) 0.185 688 456 361 410 56 × 2 = 0 + 0.371 376 912 722 821 12;
  • 21) 0.371 376 912 722 821 12 × 2 = 0 + 0.742 753 825 445 642 24;
  • 22) 0.742 753 825 445 642 24 × 2 = 1 + 0.485 507 650 891 284 48;
  • 23) 0.485 507 650 891 284 48 × 2 = 0 + 0.971 015 301 782 568 96;
  • 24) 0.971 015 301 782 568 96 × 2 = 1 + 0.942 030 603 565 137 92;
  • 25) 0.942 030 603 565 137 92 × 2 = 1 + 0.884 061 207 130 275 84;
  • 26) 0.884 061 207 130 275 84 × 2 = 1 + 0.768 122 414 260 551 68;
  • 27) 0.768 122 414 260 551 68 × 2 = 1 + 0.536 244 828 521 103 36;
  • 28) 0.536 244 828 521 103 36 × 2 = 1 + 0.072 489 657 042 206 72;
  • 29) 0.072 489 657 042 206 72 × 2 = 0 + 0.144 979 314 084 413 44;
  • 30) 0.144 979 314 084 413 44 × 2 = 0 + 0.289 958 628 168 826 88;
  • 31) 0.289 958 628 168 826 88 × 2 = 0 + 0.579 917 256 337 653 76;
  • 32) 0.579 917 256 337 653 76 × 2 = 1 + 0.159 834 512 675 307 52;
  • 33) 0.159 834 512 675 307 52 × 2 = 0 + 0.319 669 025 350 615 04;
  • 34) 0.319 669 025 350 615 04 × 2 = 0 + 0.639 338 050 701 230 08;
  • 35) 0.639 338 050 701 230 08 × 2 = 1 + 0.278 676 101 402 460 16;
  • 36) 0.278 676 101 402 460 16 × 2 = 0 + 0.557 352 202 804 920 32;
  • 37) 0.557 352 202 804 920 32 × 2 = 1 + 0.114 704 405 609 840 64;
  • 38) 0.114 704 405 609 840 64 × 2 = 0 + 0.229 408 811 219 681 28;
  • 39) 0.229 408 811 219 681 28 × 2 = 0 + 0.458 817 622 439 362 56;
  • 40) 0.458 817 622 439 362 56 × 2 = 0 + 0.917 635 244 878 725 12;
  • 41) 0.917 635 244 878 725 12 × 2 = 1 + 0.835 270 489 757 450 24;
  • 42) 0.835 270 489 757 450 24 × 2 = 1 + 0.670 540 979 514 900 48;
  • 43) 0.670 540 979 514 900 48 × 2 = 1 + 0.341 081 959 029 800 96;
  • 44) 0.341 081 959 029 800 96 × 2 = 0 + 0.682 163 918 059 601 92;
  • 45) 0.682 163 918 059 601 92 × 2 = 1 + 0.364 327 836 119 203 84;
  • 46) 0.364 327 836 119 203 84 × 2 = 0 + 0.728 655 672 238 407 68;
  • 47) 0.728 655 672 238 407 68 × 2 = 1 + 0.457 311 344 476 815 36;
  • 48) 0.457 311 344 476 815 36 × 2 = 0 + 0.914 622 688 953 630 72;
  • 49) 0.914 622 688 953 630 72 × 2 = 1 + 0.829 245 377 907 261 44;
  • 50) 0.829 245 377 907 261 44 × 2 = 1 + 0.658 490 755 814 522 88;
  • 51) 0.658 490 755 814 522 88 × 2 = 1 + 0.316 981 511 629 045 76;
  • 52) 0.316 981 511 629 045 76 × 2 = 0 + 0.633 963 023 258 091 52;
  • 53) 0.633 963 023 258 091 52 × 2 = 1 + 0.267 926 046 516 183 04;

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:


0.022 140 857 102 310 87(10) =


0.0000 0101 1010 1011 0000 0101 1111 0001 0010 1000 1110 1010 1110 1(2)

5. Positive number before normalization:

6.022 140 857 102 310 87(10) =


110.0000 0101 1010 1011 0000 0101 1111 0001 0010 1000 1110 1010 1110 1(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 2 positions to the left, so that only one non zero digit remains to the left of it:


6.022 140 857 102 310 87(10) =


110.0000 0101 1010 1011 0000 0101 1111 0001 0010 1000 1110 1010 1110 1(2) =


110.0000 0101 1010 1011 0000 0101 1111 0001 0010 1000 1110 1010 1110 1(2) × 20 =


1.1000 0001 0110 1010 1100 0001 0111 1100 0100 1010 0011 1010 1011 101(2) × 22


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): 2


Mantissa (not normalized):
1.1000 0001 0110 1010 1100 0001 0111 1100 0100 1010 0011 1010 1011 101


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


2 + 2(11-1) - 1 =


(2 + 1 023)(10) =


1 025(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;
  • 1 025 ÷ 2 = 512 + 1;
  • 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;

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) =


1025(10) =


100 0000 0001(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. 1000 0001 0110 1010 1100 0001 0111 1100 0100 1010 0011 1010 1011 101 =


1000 0001 0110 1010 1100 0001 0111 1100 0100 1010 0011 1010 1011


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 0000 0001


Mantissa (52 bits) =
1000 0001 0110 1010 1100 0001 0111 1100 0100 1010 0011 1010 1011


Decimal number 6.022 140 857 102 310 87 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0000 0001 - 1000 0001 0110 1010 1100 0001 0111 1100 0100 1010 0011 1010 1011


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