7 522 000 000 000 000 000 000 140 Converted to 32 Bit Single Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 7 522 000 000 000 000 000 000 140(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
7 522 000 000 000 000 000 000 140(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;
  • 7 522 000 000 000 000 000 000 140 ÷ 2 = 3 761 000 000 000 000 000 000 070 + 0;
  • 3 761 000 000 000 000 000 000 070 ÷ 2 = 1 880 500 000 000 000 000 000 035 + 0;
  • 1 880 500 000 000 000 000 000 035 ÷ 2 = 940 250 000 000 000 000 000 017 + 1;
  • 940 250 000 000 000 000 000 017 ÷ 2 = 470 125 000 000 000 000 000 008 + 1;
  • 470 125 000 000 000 000 000 008 ÷ 2 = 235 062 500 000 000 000 000 004 + 0;
  • 235 062 500 000 000 000 000 004 ÷ 2 = 117 531 250 000 000 000 000 002 + 0;
  • 117 531 250 000 000 000 000 002 ÷ 2 = 58 765 625 000 000 000 000 001 + 0;
  • 58 765 625 000 000 000 000 001 ÷ 2 = 29 382 812 500 000 000 000 000 + 1;
  • 29 382 812 500 000 000 000 000 ÷ 2 = 14 691 406 250 000 000 000 000 + 0;
  • 14 691 406 250 000 000 000 000 ÷ 2 = 7 345 703 125 000 000 000 000 + 0;
  • 7 345 703 125 000 000 000 000 ÷ 2 = 3 672 851 562 500 000 000 000 + 0;
  • 3 672 851 562 500 000 000 000 ÷ 2 = 1 836 425 781 250 000 000 000 + 0;
  • 1 836 425 781 250 000 000 000 ÷ 2 = 918 212 890 625 000 000 000 + 0;
  • 918 212 890 625 000 000 000 ÷ 2 = 459 106 445 312 500 000 000 + 0;
  • 459 106 445 312 500 000 000 ÷ 2 = 229 553 222 656 250 000 000 + 0;
  • 229 553 222 656 250 000 000 ÷ 2 = 114 776 611 328 125 000 000 + 0;
  • 114 776 611 328 125 000 000 ÷ 2 = 57 388 305 664 062 500 000 + 0;
  • 57 388 305 664 062 500 000 ÷ 2 = 28 694 152 832 031 250 000 + 0;
  • 28 694 152 832 031 250 000 ÷ 2 = 14 347 076 416 015 625 000 + 0;
  • 14 347 076 416 015 625 000 ÷ 2 = 7 173 538 208 007 812 500 + 0;
  • 7 173 538 208 007 812 500 ÷ 2 = 3 586 769 104 003 906 250 + 0;
  • 3 586 769 104 003 906 250 ÷ 2 = 1 793 384 552 001 953 125 + 0;
  • 1 793 384 552 001 953 125 ÷ 2 = 896 692 276 000 976 562 + 1;
  • 896 692 276 000 976 562 ÷ 2 = 448 346 138 000 488 281 + 0;
  • 448 346 138 000 488 281 ÷ 2 = 224 173 069 000 244 140 + 1;
  • 224 173 069 000 244 140 ÷ 2 = 112 086 534 500 122 070 + 0;
  • 112 086 534 500 122 070 ÷ 2 = 56 043 267 250 061 035 + 0;
  • 56 043 267 250 061 035 ÷ 2 = 28 021 633 625 030 517 + 1;
  • 28 021 633 625 030 517 ÷ 2 = 14 010 816 812 515 258 + 1;
  • 14 010 816 812 515 258 ÷ 2 = 7 005 408 406 257 629 + 0;
  • 7 005 408 406 257 629 ÷ 2 = 3 502 704 203 128 814 + 1;
  • 3 502 704 203 128 814 ÷ 2 = 1 751 352 101 564 407 + 0;
  • 1 751 352 101 564 407 ÷ 2 = 875 676 050 782 203 + 1;
  • 875 676 050 782 203 ÷ 2 = 437 838 025 391 101 + 1;
  • 437 838 025 391 101 ÷ 2 = 218 919 012 695 550 + 1;
  • 218 919 012 695 550 ÷ 2 = 109 459 506 347 775 + 0;
  • 109 459 506 347 775 ÷ 2 = 54 729 753 173 887 + 1;
  • 54 729 753 173 887 ÷ 2 = 27 364 876 586 943 + 1;
  • 27 364 876 586 943 ÷ 2 = 13 682 438 293 471 + 1;
  • 13 682 438 293 471 ÷ 2 = 6 841 219 146 735 + 1;
  • 6 841 219 146 735 ÷ 2 = 3 420 609 573 367 + 1;
  • 3 420 609 573 367 ÷ 2 = 1 710 304 786 683 + 1;
  • 1 710 304 786 683 ÷ 2 = 855 152 393 341 + 1;
  • 855 152 393 341 ÷ 2 = 427 576 196 670 + 1;
  • 427 576 196 670 ÷ 2 = 213 788 098 335 + 0;
  • 213 788 098 335 ÷ 2 = 106 894 049 167 + 1;
  • 106 894 049 167 ÷ 2 = 53 447 024 583 + 1;
  • 53 447 024 583 ÷ 2 = 26 723 512 291 + 1;
  • 26 723 512 291 ÷ 2 = 13 361 756 145 + 1;
  • 13 361 756 145 ÷ 2 = 6 680 878 072 + 1;
  • 6 680 878 072 ÷ 2 = 3 340 439 036 + 0;
  • 3 340 439 036 ÷ 2 = 1 670 219 518 + 0;
  • 1 670 219 518 ÷ 2 = 835 109 759 + 0;
  • 835 109 759 ÷ 2 = 417 554 879 + 1;
  • 417 554 879 ÷ 2 = 208 777 439 + 1;
  • 208 777 439 ÷ 2 = 104 388 719 + 1;
  • 104 388 719 ÷ 2 = 52 194 359 + 1;
  • 52 194 359 ÷ 2 = 26 097 179 + 1;
  • 26 097 179 ÷ 2 = 13 048 589 + 1;
  • 13 048 589 ÷ 2 = 6 524 294 + 1;
  • 6 524 294 ÷ 2 = 3 262 147 + 0;
  • 3 262 147 ÷ 2 = 1 631 073 + 1;
  • 1 631 073 ÷ 2 = 815 536 + 1;
  • 815 536 ÷ 2 = 407 768 + 0;
  • 407 768 ÷ 2 = 203 884 + 0;
  • 203 884 ÷ 2 = 101 942 + 0;
  • 101 942 ÷ 2 = 50 971 + 0;
  • 50 971 ÷ 2 = 25 485 + 1;
  • 25 485 ÷ 2 = 12 742 + 1;
  • 12 742 ÷ 2 = 6 371 + 0;
  • 6 371 ÷ 2 = 3 185 + 1;
  • 3 185 ÷ 2 = 1 592 + 1;
  • 1 592 ÷ 2 = 796 + 0;
  • 796 ÷ 2 = 398 + 0;
  • 398 ÷ 2 = 199 + 0;
  • 199 ÷ 2 = 99 + 1;
  • 99 ÷ 2 = 49 + 1;
  • 49 ÷ 2 = 24 + 1;
  • 24 ÷ 2 = 12 + 0;
  • 12 ÷ 2 = 6 + 0;
  • 6 ÷ 2 = 3 + 0;
  • 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.

7 522 000 000 000 000 000 000 140(10) =


110 0011 1000 1101 1000 0110 1111 1110 0011 1110 1111 1111 0111 0101 1001 0100 0000 0000 0000 1000 1100(2)


3. Normalize the binary representation of the number.

Shift the decimal mark 82 positions to the left, so that only one non zero digit remains to the left of it:


7 522 000 000 000 000 000 000 140(10) =


110 0011 1000 1101 1000 0110 1111 1110 0011 1110 1111 1111 0111 0101 1001 0100 0000 0000 0000 1000 1100(2) =


110 0011 1000 1101 1000 0110 1111 1110 0011 1110 1111 1111 0111 0101 1001 0100 0000 0000 0000 1000 1100(2) × 20 =


1.1000 1110 0011 0110 0001 1011 1111 1000 1111 1011 1111 1101 1101 0110 0101 0000 0000 0000 0010 0011 00(2) × 282


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): 82


Mantissa (not normalized):
1.1000 1110 0011 0110 0001 1011 1111 1000 1111 1011 1111 1101 1101 0110 0101 0000 0000 0000 0010 0011 00


5. Adjust the exponent.

Use the 8 bit excess/bias notation:


Exponent (adjusted) =


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


82 + 2(8-1) - 1 =


(82 + 127)(10) =


209(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;
  • 209 ÷ 2 = 104 + 1;
  • 104 ÷ 2 = 52 + 0;
  • 52 ÷ 2 = 26 + 0;
  • 26 ÷ 2 = 13 + 0;
  • 13 ÷ 2 = 6 + 1;
  • 6 ÷ 2 = 3 + 0;
  • 3 ÷ 2 = 1 + 1;
  • 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) =


209(10) =


1101 0001(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. 100 0111 0001 1011 0000 1101 111 1110 0011 1110 1111 1111 0111 0101 1001 0100 0000 0000 0000 1000 1100 =


100 0111 0001 1011 0000 1101


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) =
1101 0001


Mantissa (23 bits) =
100 0111 0001 1011 0000 1101


Decimal number 7 522 000 000 000 000 000 000 140 converted to 32 bit single precision IEEE 754 binary floating point representation:

0 - 1101 0001 - 100 0111 0001 1011 0000 1101


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