Decimal to 64 Bit IEEE 754 Binary: Convert Number -8 466 092 655 776 054 260 to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From Base Ten Decimal System

Number -8 466 092 655 776 054 260(10) converted and written in 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. Start with the positive version of the number:

|-8 466 092 655 776 054 260| = 8 466 092 655 776 054 260


2. 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;
  • 8 466 092 655 776 054 260 ÷ 2 = 4 233 046 327 888 027 130 + 0;
  • 4 233 046 327 888 027 130 ÷ 2 = 2 116 523 163 944 013 565 + 0;
  • 2 116 523 163 944 013 565 ÷ 2 = 1 058 261 581 972 006 782 + 1;
  • 1 058 261 581 972 006 782 ÷ 2 = 529 130 790 986 003 391 + 0;
  • 529 130 790 986 003 391 ÷ 2 = 264 565 395 493 001 695 + 1;
  • 264 565 395 493 001 695 ÷ 2 = 132 282 697 746 500 847 + 1;
  • 132 282 697 746 500 847 ÷ 2 = 66 141 348 873 250 423 + 1;
  • 66 141 348 873 250 423 ÷ 2 = 33 070 674 436 625 211 + 1;
  • 33 070 674 436 625 211 ÷ 2 = 16 535 337 218 312 605 + 1;
  • 16 535 337 218 312 605 ÷ 2 = 8 267 668 609 156 302 + 1;
  • 8 267 668 609 156 302 ÷ 2 = 4 133 834 304 578 151 + 0;
  • 4 133 834 304 578 151 ÷ 2 = 2 066 917 152 289 075 + 1;
  • 2 066 917 152 289 075 ÷ 2 = 1 033 458 576 144 537 + 1;
  • 1 033 458 576 144 537 ÷ 2 = 516 729 288 072 268 + 1;
  • 516 729 288 072 268 ÷ 2 = 258 364 644 036 134 + 0;
  • 258 364 644 036 134 ÷ 2 = 129 182 322 018 067 + 0;
  • 129 182 322 018 067 ÷ 2 = 64 591 161 009 033 + 1;
  • 64 591 161 009 033 ÷ 2 = 32 295 580 504 516 + 1;
  • 32 295 580 504 516 ÷ 2 = 16 147 790 252 258 + 0;
  • 16 147 790 252 258 ÷ 2 = 8 073 895 126 129 + 0;
  • 8 073 895 126 129 ÷ 2 = 4 036 947 563 064 + 1;
  • 4 036 947 563 064 ÷ 2 = 2 018 473 781 532 + 0;
  • 2 018 473 781 532 ÷ 2 = 1 009 236 890 766 + 0;
  • 1 009 236 890 766 ÷ 2 = 504 618 445 383 + 0;
  • 504 618 445 383 ÷ 2 = 252 309 222 691 + 1;
  • 252 309 222 691 ÷ 2 = 126 154 611 345 + 1;
  • 126 154 611 345 ÷ 2 = 63 077 305 672 + 1;
  • 63 077 305 672 ÷ 2 = 31 538 652 836 + 0;
  • 31 538 652 836 ÷ 2 = 15 769 326 418 + 0;
  • 15 769 326 418 ÷ 2 = 7 884 663 209 + 0;
  • 7 884 663 209 ÷ 2 = 3 942 331 604 + 1;
  • 3 942 331 604 ÷ 2 = 1 971 165 802 + 0;
  • 1 971 165 802 ÷ 2 = 985 582 901 + 0;
  • 985 582 901 ÷ 2 = 492 791 450 + 1;
  • 492 791 450 ÷ 2 = 246 395 725 + 0;
  • 246 395 725 ÷ 2 = 123 197 862 + 1;
  • 123 197 862 ÷ 2 = 61 598 931 + 0;
  • 61 598 931 ÷ 2 = 30 799 465 + 1;
  • 30 799 465 ÷ 2 = 15 399 732 + 1;
  • 15 399 732 ÷ 2 = 7 699 866 + 0;
  • 7 699 866 ÷ 2 = 3 849 933 + 0;
  • 3 849 933 ÷ 2 = 1 924 966 + 1;
  • 1 924 966 ÷ 2 = 962 483 + 0;
  • 962 483 ÷ 2 = 481 241 + 1;
  • 481 241 ÷ 2 = 240 620 + 1;
  • 240 620 ÷ 2 = 120 310 + 0;
  • 120 310 ÷ 2 = 60 155 + 0;
  • 60 155 ÷ 2 = 30 077 + 1;
  • 30 077 ÷ 2 = 15 038 + 1;
  • 15 038 ÷ 2 = 7 519 + 0;
  • 7 519 ÷ 2 = 3 759 + 1;
  • 3 759 ÷ 2 = 1 879 + 1;
  • 1 879 ÷ 2 = 939 + 1;
  • 939 ÷ 2 = 469 + 1;
  • 469 ÷ 2 = 234 + 1;
  • 234 ÷ 2 = 117 + 0;
  • 117 ÷ 2 = 58 + 1;
  • 58 ÷ 2 = 29 + 0;
  • 29 ÷ 2 = 14 + 1;
  • 14 ÷ 2 = 7 + 0;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

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

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

8 466 092 655 776 054 260(10) =


111 0101 0111 1101 1001 1010 0110 1010 0100 0111 0001 0011 0011 1011 1111 0100(2)


4. Normalize the binary representation of the number.

Shift the decimal mark 62 positions to the left, so that only one non zero digit remains to the left of it:


8 466 092 655 776 054 260(10) =


111 0101 0111 1101 1001 1010 0110 1010 0100 0111 0001 0011 0011 1011 1111 0100(2) =


111 0101 0111 1101 1001 1010 0110 1010 0100 0111 0001 0011 0011 1011 1111 0100(2) × 20 =


1.1101 0101 1111 0110 0110 1001 1010 1001 0001 1100 0100 1100 1110 1111 1101 00(2) × 262


5. 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): 62


Mantissa (not normalized):
1.1101 0101 1111 0110 0110 1001 1010 1001 0001 1100 0100 1100 1110 1111 1101 00


6. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


62 + 2(11-1) - 1 =


(62 + 1 023)(10) =


1 085(10)


7. 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;
  • 1 085 ÷ 2 = 542 + 1;
  • 542 ÷ 2 = 271 + 0;
  • 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;

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

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


Exponent (adjusted) =


1085(10) =


100 0011 1101(2)


9. 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. 1101 0101 1111 0110 0110 1001 1010 1001 0001 1100 0100 1100 1110 11 1111 0100 =


1101 0101 1111 0110 0110 1001 1010 1001 0001 1100 0100 1100 1110


10. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
100 0011 1101


Mantissa (52 bits) =
1101 0101 1111 0110 0110 1001 1010 1001 0001 1100 0100 1100 1110


The base ten decimal number -8 466 092 655 776 054 260 converted and written in 64 bit double precision IEEE 754 binary floating point representation:

1 - 100 0011 1101 - 1101 0101 1111 0110 0110 1001 1010 1001 0001 1100 0100 1100 1110

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