2 323 454 502 200 067 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 2 323 454 502 200 067(10) to 32 bit single precision IEEE 754 binary floating point representation standard (1 bit for sign, 8 bits for exponent, 23 bits for mantissa)

What are the steps to convert decimal number
2 323 454 502 200 067(10) to 32 bit single precision IEEE 754 binary floating point representation (1 bit for sign, 8 bits for exponent, 23 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;
  • 2 323 454 502 200 067 ÷ 2 = 1 161 727 251 100 033 + 1;
  • 1 161 727 251 100 033 ÷ 2 = 580 863 625 550 016 + 1;
  • 580 863 625 550 016 ÷ 2 = 290 431 812 775 008 + 0;
  • 290 431 812 775 008 ÷ 2 = 145 215 906 387 504 + 0;
  • 145 215 906 387 504 ÷ 2 = 72 607 953 193 752 + 0;
  • 72 607 953 193 752 ÷ 2 = 36 303 976 596 876 + 0;
  • 36 303 976 596 876 ÷ 2 = 18 151 988 298 438 + 0;
  • 18 151 988 298 438 ÷ 2 = 9 075 994 149 219 + 0;
  • 9 075 994 149 219 ÷ 2 = 4 537 997 074 609 + 1;
  • 4 537 997 074 609 ÷ 2 = 2 268 998 537 304 + 1;
  • 2 268 998 537 304 ÷ 2 = 1 134 499 268 652 + 0;
  • 1 134 499 268 652 ÷ 2 = 567 249 634 326 + 0;
  • 567 249 634 326 ÷ 2 = 283 624 817 163 + 0;
  • 283 624 817 163 ÷ 2 = 141 812 408 581 + 1;
  • 141 812 408 581 ÷ 2 = 70 906 204 290 + 1;
  • 70 906 204 290 ÷ 2 = 35 453 102 145 + 0;
  • 35 453 102 145 ÷ 2 = 17 726 551 072 + 1;
  • 17 726 551 072 ÷ 2 = 8 863 275 536 + 0;
  • 8 863 275 536 ÷ 2 = 4 431 637 768 + 0;
  • 4 431 637 768 ÷ 2 = 2 215 818 884 + 0;
  • 2 215 818 884 ÷ 2 = 1 107 909 442 + 0;
  • 1 107 909 442 ÷ 2 = 553 954 721 + 0;
  • 553 954 721 ÷ 2 = 276 977 360 + 1;
  • 276 977 360 ÷ 2 = 138 488 680 + 0;
  • 138 488 680 ÷ 2 = 69 244 340 + 0;
  • 69 244 340 ÷ 2 = 34 622 170 + 0;
  • 34 622 170 ÷ 2 = 17 311 085 + 0;
  • 17 311 085 ÷ 2 = 8 655 542 + 1;
  • 8 655 542 ÷ 2 = 4 327 771 + 0;
  • 4 327 771 ÷ 2 = 2 163 885 + 1;
  • 2 163 885 ÷ 2 = 1 081 942 + 1;
  • 1 081 942 ÷ 2 = 540 971 + 0;
  • 540 971 ÷ 2 = 270 485 + 1;
  • 270 485 ÷ 2 = 135 242 + 1;
  • 135 242 ÷ 2 = 67 621 + 0;
  • 67 621 ÷ 2 = 33 810 + 1;
  • 33 810 ÷ 2 = 16 905 + 0;
  • 16 905 ÷ 2 = 8 452 + 1;
  • 8 452 ÷ 2 = 4 226 + 0;
  • 4 226 ÷ 2 = 2 113 + 0;
  • 2 113 ÷ 2 = 1 056 + 1;
  • 1 056 ÷ 2 = 528 + 0;
  • 528 ÷ 2 = 264 + 0;
  • 264 ÷ 2 = 132 + 0;
  • 132 ÷ 2 = 66 + 0;
  • 66 ÷ 2 = 33 + 0;
  • 33 ÷ 2 = 16 + 1;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 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.

2 323 454 502 200 067(10) =


1000 0100 0001 0010 1011 0110 1000 0100 0001 0110 0011 0000 0011(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 51 positions to the left, so that only one non zero digit remains to the left of it:


2 323 454 502 200 067(10) =


1000 0100 0001 0010 1011 0110 1000 0100 0001 0110 0011 0000 0011(2) =


1000 0100 0001 0010 1011 0110 1000 0100 0001 0110 0011 0000 0011(2) × 20 =


1.0000 1000 0010 0101 0110 1101 0000 1000 0010 1100 0110 0000 011(2) × 251


4. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): 51


Mantissa (not normalized):
1.0000 1000 0010 0101 0110 1101 0000 1000 0010 1100 0110 0000 011


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(8-1) - 1 =


51 + 2(8-1) - 1 =


(51 + 127)(10) =


178(10)


6. Convert the adjusted exponent from the decimal (base 10) to 8 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 178 ÷ 2 = 89 + 0;
  • 89 ÷ 2 = 44 + 1;
  • 44 ÷ 2 = 22 + 0;
  • 22 ÷ 2 = 11 + 0;
  • 11 ÷ 2 = 5 + 1;
  • 5 ÷ 2 = 2 + 1;
  • 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) =


178(10) =


1011 0010(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 23 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. 000 0100 0001 0010 1011 0110 1000 0100 0001 0110 0011 0000 0011 =


000 0100 0001 0010 1011 0110


9. The three elements that make up the number's 32 bit single precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (8 bits) =
1011 0010


Mantissa (23 bits) =
000 0100 0001 0010 1011 0110


Decimal number 2 323 454 502 200 067 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1011 0010 - 000 0100 0001 0010 1011 0110

How to convert decimal numbers from base ten to 32 bit single precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 32 bit single 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 base ten 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 of the previous dividing 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 previous multiplying operations, starting from the top of the constructed list 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, by shifting the decimal point (or if you prefer, the decimal mark) "n" positions either to the left or to the right, so that only one non zero digit remains to the left of the decimal point.
  • 7. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign if the case) and adjust its length to 23 bits, either by removing the excess bits from the right (losing precision...) or by adding extra '0' bits 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 -25.347 from decimal system (base ten) to 32 bit single precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-25.347| = 25.347

  • 2. First convert the integer part, 25. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 25 ÷ 2 = 12 + 1;
    • 12 ÷ 2 = 6 + 0;
    • 6 ÷ 2 = 3 + 0;
    • 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:

    25(10) = 1 1001(2)

  • 4. Then convert the fractional part, 0.347. 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) 0.347 × 2 = 0 + 0.694;
    • 2) 0.694 × 2 = 1 + 0.388;
    • 3) 0.388 × 2 = 0 + 0.776;
    • 4) 0.776 × 2 = 1 + 0.552;
    • 5) 0.552 × 2 = 1 + 0.104;
    • 6) 0.104 × 2 = 0 + 0.208;
    • 7) 0.208 × 2 = 0 + 0.416;
    • 8) 0.416 × 2 = 0 + 0.832;
    • 9) 0.832 × 2 = 1 + 0.664;
    • 10) 0.664 × 2 = 1 + 0.328;
    • 11) 0.328 × 2 = 0 + 0.656;
    • 12) 0.656 × 2 = 1 + 0.312;
    • 13) 0.312 × 2 = 0 + 0.624;
    • 14) 0.624 × 2 = 1 + 0.248;
    • 15) 0.248 × 2 = 0 + 0.496;
    • 16) 0.496 × 2 = 0 + 0.992;
    • 17) 0.992 × 2 = 1 + 0.984;
    • 18) 0.984 × 2 = 1 + 0.968;
    • 19) 0.968 × 2 = 1 + 0.936;
    • 20) 0.936 × 2 = 1 + 0.872;
    • 21) 0.872 × 2 = 1 + 0.744;
    • 22) 0.744 × 2 = 1 + 0.488;
    • 23) 0.488 × 2 = 0 + 0.976;
    • 24) 0.976 × 2 = 1 + 0.952;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 23) 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:

    0.347(10) = 0.0101 1000 1101 0100 1111 1101(2)

  • 6. Summarizing - the positive number before normalization:

    25.347(10) = 1 1001.0101 1000 1101 0100 1111 1101(2)

  • 7. Normalize the binary representation of the number, shifting the decimal point 4 positions to the left so that only one non-zero digit stays to the left of the decimal point:

    25.347(10) =
    1 1001.0101 1000 1101 0100 1111 1101(2) =
    1 1001.0101 1000 1101 0100 1111 1101(2) × 20 =
    1.1001 0101 1000 1101 0100 1111 1101(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 32 bit single precision IEEE 754 binary floating point:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

  • 9. Adjust the exponent in 8 bit excess/bias notation and then convert it from decimal (base 10) to 8 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as already demonstrated above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(8-1) - 1 = (4 + 127)(10) = 131(10) =
    1000 0011(2)

  • 10. Normalize the mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal point) and adjust its length to 23 bits, by removing the excess bits from the right (losing precision...):

    Mantissa (not-normalized): 1.1001 0101 1000 1101 0100 1111 1101

    Mantissa (normalized): 100 1010 1100 0110 1010 0111

  • Conclusion:

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

    Exponent (8 bits) = 1000 0011

    Mantissa (23 bits) = 100 1010 1100 0110 1010 0111

  • Number -25.347, converted from the decimal system (base 10) to 32 bit single precision IEEE 754 binary floating point =
    1 - 1000 0011 - 100 1010 1100 0110 1010 0111