4 593 991 788 760 435 134 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 4 593 991 788 760 435 134(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
4 593 991 788 760 435 134(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;
  • 4 593 991 788 760 435 134 ÷ 2 = 2 296 995 894 380 217 567 + 0;
  • 2 296 995 894 380 217 567 ÷ 2 = 1 148 497 947 190 108 783 + 1;
  • 1 148 497 947 190 108 783 ÷ 2 = 574 248 973 595 054 391 + 1;
  • 574 248 973 595 054 391 ÷ 2 = 287 124 486 797 527 195 + 1;
  • 287 124 486 797 527 195 ÷ 2 = 143 562 243 398 763 597 + 1;
  • 143 562 243 398 763 597 ÷ 2 = 71 781 121 699 381 798 + 1;
  • 71 781 121 699 381 798 ÷ 2 = 35 890 560 849 690 899 + 0;
  • 35 890 560 849 690 899 ÷ 2 = 17 945 280 424 845 449 + 1;
  • 17 945 280 424 845 449 ÷ 2 = 8 972 640 212 422 724 + 1;
  • 8 972 640 212 422 724 ÷ 2 = 4 486 320 106 211 362 + 0;
  • 4 486 320 106 211 362 ÷ 2 = 2 243 160 053 105 681 + 0;
  • 2 243 160 053 105 681 ÷ 2 = 1 121 580 026 552 840 + 1;
  • 1 121 580 026 552 840 ÷ 2 = 560 790 013 276 420 + 0;
  • 560 790 013 276 420 ÷ 2 = 280 395 006 638 210 + 0;
  • 280 395 006 638 210 ÷ 2 = 140 197 503 319 105 + 0;
  • 140 197 503 319 105 ÷ 2 = 70 098 751 659 552 + 1;
  • 70 098 751 659 552 ÷ 2 = 35 049 375 829 776 + 0;
  • 35 049 375 829 776 ÷ 2 = 17 524 687 914 888 + 0;
  • 17 524 687 914 888 ÷ 2 = 8 762 343 957 444 + 0;
  • 8 762 343 957 444 ÷ 2 = 4 381 171 978 722 + 0;
  • 4 381 171 978 722 ÷ 2 = 2 190 585 989 361 + 0;
  • 2 190 585 989 361 ÷ 2 = 1 095 292 994 680 + 1;
  • 1 095 292 994 680 ÷ 2 = 547 646 497 340 + 0;
  • 547 646 497 340 ÷ 2 = 273 823 248 670 + 0;
  • 273 823 248 670 ÷ 2 = 136 911 624 335 + 0;
  • 136 911 624 335 ÷ 2 = 68 455 812 167 + 1;
  • 68 455 812 167 ÷ 2 = 34 227 906 083 + 1;
  • 34 227 906 083 ÷ 2 = 17 113 953 041 + 1;
  • 17 113 953 041 ÷ 2 = 8 556 976 520 + 1;
  • 8 556 976 520 ÷ 2 = 4 278 488 260 + 0;
  • 4 278 488 260 ÷ 2 = 2 139 244 130 + 0;
  • 2 139 244 130 ÷ 2 = 1 069 622 065 + 0;
  • 1 069 622 065 ÷ 2 = 534 811 032 + 1;
  • 534 811 032 ÷ 2 = 267 405 516 + 0;
  • 267 405 516 ÷ 2 = 133 702 758 + 0;
  • 133 702 758 ÷ 2 = 66 851 379 + 0;
  • 66 851 379 ÷ 2 = 33 425 689 + 1;
  • 33 425 689 ÷ 2 = 16 712 844 + 1;
  • 16 712 844 ÷ 2 = 8 356 422 + 0;
  • 8 356 422 ÷ 2 = 4 178 211 + 0;
  • 4 178 211 ÷ 2 = 2 089 105 + 1;
  • 2 089 105 ÷ 2 = 1 044 552 + 1;
  • 1 044 552 ÷ 2 = 522 276 + 0;
  • 522 276 ÷ 2 = 261 138 + 0;
  • 261 138 ÷ 2 = 130 569 + 0;
  • 130 569 ÷ 2 = 65 284 + 1;
  • 65 284 ÷ 2 = 32 642 + 0;
  • 32 642 ÷ 2 = 16 321 + 0;
  • 16 321 ÷ 2 = 8 160 + 1;
  • 8 160 ÷ 2 = 4 080 + 0;
  • 4 080 ÷ 2 = 2 040 + 0;
  • 2 040 ÷ 2 = 1 020 + 0;
  • 1 020 ÷ 2 = 510 + 0;
  • 510 ÷ 2 = 255 + 0;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 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.

4 593 991 788 760 435 134(10) =


11 1111 1100 0001 0010 0011 0011 0001 0001 1110 0010 0000 1000 1001 1011 1110(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 61 positions to the left, so that only one non zero digit remains to the left of it:


4 593 991 788 760 435 134(10) =


11 1111 1100 0001 0010 0011 0011 0001 0001 1110 0010 0000 1000 1001 1011 1110(2) =


11 1111 1100 0001 0010 0011 0011 0001 0001 1110 0010 0000 1000 1001 1011 1110(2) × 20 =


1.1111 1110 0000 1001 0001 1001 1000 1000 1111 0001 0000 0100 0100 1101 1111 0(2) × 261


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): 61


Mantissa (not normalized):
1.1111 1110 0000 1001 0001 1001 1000 1000 1111 0001 0000 0100 0100 1101 1111 0


5. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


61 + 2(11-1) - 1 =


(61 + 1 023)(10) =


1 084(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;
  • 1 084 ÷ 2 = 542 + 0;
  • 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;

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) =


1084(10) =


100 0011 1100(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. 1111 1110 0000 1001 0001 1001 1000 1000 1111 0001 0000 0100 0100 1 1011 1110 =


1111 1110 0000 1001 0001 1001 1000 1000 1111 0001 0000 0100 0100


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 1100


Mantissa (52 bits) =
1111 1110 0000 1001 0001 1001 1000 1000 1111 0001 0000 0100 0100


Decimal number 4 593 991 788 760 435 134 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 100 0011 1100 - 1111 1110 0000 1001 0001 1001 1000 1000 1111 0001 0000 0100 0100

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