64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: 4 720 032 196 352 540 700 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number 4 720 032 196 352 540 700(10) converted and written in 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;
  • 4 720 032 196 352 540 700 ÷ 2 = 2 360 016 098 176 270 350 + 0;
  • 2 360 016 098 176 270 350 ÷ 2 = 1 180 008 049 088 135 175 + 0;
  • 1 180 008 049 088 135 175 ÷ 2 = 590 004 024 544 067 587 + 1;
  • 590 004 024 544 067 587 ÷ 2 = 295 002 012 272 033 793 + 1;
  • 295 002 012 272 033 793 ÷ 2 = 147 501 006 136 016 896 + 1;
  • 147 501 006 136 016 896 ÷ 2 = 73 750 503 068 008 448 + 0;
  • 73 750 503 068 008 448 ÷ 2 = 36 875 251 534 004 224 + 0;
  • 36 875 251 534 004 224 ÷ 2 = 18 437 625 767 002 112 + 0;
  • 18 437 625 767 002 112 ÷ 2 = 9 218 812 883 501 056 + 0;
  • 9 218 812 883 501 056 ÷ 2 = 4 609 406 441 750 528 + 0;
  • 4 609 406 441 750 528 ÷ 2 = 2 304 703 220 875 264 + 0;
  • 2 304 703 220 875 264 ÷ 2 = 1 152 351 610 437 632 + 0;
  • 1 152 351 610 437 632 ÷ 2 = 576 175 805 218 816 + 0;
  • 576 175 805 218 816 ÷ 2 = 288 087 902 609 408 + 0;
  • 288 087 902 609 408 ÷ 2 = 144 043 951 304 704 + 0;
  • 144 043 951 304 704 ÷ 2 = 72 021 975 652 352 + 0;
  • 72 021 975 652 352 ÷ 2 = 36 010 987 826 176 + 0;
  • 36 010 987 826 176 ÷ 2 = 18 005 493 913 088 + 0;
  • 18 005 493 913 088 ÷ 2 = 9 002 746 956 544 + 0;
  • 9 002 746 956 544 ÷ 2 = 4 501 373 478 272 + 0;
  • 4 501 373 478 272 ÷ 2 = 2 250 686 739 136 + 0;
  • 2 250 686 739 136 ÷ 2 = 1 125 343 369 568 + 0;
  • 1 125 343 369 568 ÷ 2 = 562 671 684 784 + 0;
  • 562 671 684 784 ÷ 2 = 281 335 842 392 + 0;
  • 281 335 842 392 ÷ 2 = 140 667 921 196 + 0;
  • 140 667 921 196 ÷ 2 = 70 333 960 598 + 0;
  • 70 333 960 598 ÷ 2 = 35 166 980 299 + 0;
  • 35 166 980 299 ÷ 2 = 17 583 490 149 + 1;
  • 17 583 490 149 ÷ 2 = 8 791 745 074 + 1;
  • 8 791 745 074 ÷ 2 = 4 395 872 537 + 0;
  • 4 395 872 537 ÷ 2 = 2 197 936 268 + 1;
  • 2 197 936 268 ÷ 2 = 1 098 968 134 + 0;
  • 1 098 968 134 ÷ 2 = 549 484 067 + 0;
  • 549 484 067 ÷ 2 = 274 742 033 + 1;
  • 274 742 033 ÷ 2 = 137 371 016 + 1;
  • 137 371 016 ÷ 2 = 68 685 508 + 0;
  • 68 685 508 ÷ 2 = 34 342 754 + 0;
  • 34 342 754 ÷ 2 = 17 171 377 + 0;
  • 17 171 377 ÷ 2 = 8 585 688 + 1;
  • 8 585 688 ÷ 2 = 4 292 844 + 0;
  • 4 292 844 ÷ 2 = 2 146 422 + 0;
  • 2 146 422 ÷ 2 = 1 073 211 + 0;
  • 1 073 211 ÷ 2 = 536 605 + 1;
  • 536 605 ÷ 2 = 268 302 + 1;
  • 268 302 ÷ 2 = 134 151 + 0;
  • 134 151 ÷ 2 = 67 075 + 1;
  • 67 075 ÷ 2 = 33 537 + 1;
  • 33 537 ÷ 2 = 16 768 + 1;
  • 16 768 ÷ 2 = 8 384 + 0;
  • 8 384 ÷ 2 = 4 192 + 0;
  • 4 192 ÷ 2 = 2 096 + 0;
  • 2 096 ÷ 2 = 1 048 + 0;
  • 1 048 ÷ 2 = 524 + 0;
  • 524 ÷ 2 = 262 + 0;
  • 262 ÷ 2 = 131 + 0;
  • 131 ÷ 2 = 65 + 1;
  • 65 ÷ 2 = 32 + 1;
  • 32 ÷ 2 = 16 + 0;
  • 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.


4 720 032 196 352 540 700(10) =


100 0001 1000 0000 1110 1100 0100 0110 0101 1000 0000 0000 0000 0000 0001 1100(2)


3. 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:


4 720 032 196 352 540 700(10) =


100 0001 1000 0000 1110 1100 0100 0110 0101 1000 0000 0000 0000 0000 0001 1100(2) =


100 0001 1000 0000 1110 1100 0100 0110 0101 1000 0000 0000 0000 0000 0001 1100(2) × 20 =


1.0000 0110 0000 0011 1011 0001 0001 1001 0110 0000 0000 0000 0000 0000 0111 00(2) × 262


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): 62


Mantissa (not normalized):
1.0000 0110 0000 0011 1011 0001 0001 1001 0110 0000 0000 0000 0000 0000 0111 00


5. 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)


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;
  • 1 085 ÷ 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;

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) =


1085(10) =


100 0011 1101(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. 0000 0110 0000 0011 1011 0001 0001 1001 0110 0000 0000 0000 0000 00 0001 1100 =


0000 0110 0000 0011 1011 0001 0001 1001 0110 0000 0000 0000 0000


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 1101


Mantissa (52 bits) =
0000 0110 0000 0011 1011 0001 0001 1001 0110 0000 0000 0000 0000


The base ten decimal number 4 720 032 196 352 540 700 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
0 - 100 0011 1101 - 0000 0110 0000 0011 1011 0001 0001 1001 0110 0000 0000 0000 0000

The latest decimal numbers converted from base ten to 64 bit double precision IEEE 754 floating point binary standard representation

Number 2.251 29 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:09 UTC (GMT)
Number 3 949 040.725 641 96 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:08 UTC (GMT)
Number 3 061 964 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:08 UTC (GMT)
Number 0.101 010 102 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:08 UTC (GMT)
Number -1 059 916 523 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:08 UTC (GMT)
Number 625 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:08 UTC (GMT)
Number -0.134 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:08 UTC (GMT)
Number -0.544 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:08 UTC (GMT)
Number 92.299 999 999 999 997 157 829 056 959 599 259 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:08 UTC (GMT)
Number -0.030 000 000 000 004 converted from decimal system (written in base ten) to 64 bit double precision IEEE 754 binary floating point representation standard May 20 02:07 UTC (GMT)
All base ten decimal numbers converted to 64 bit double precision IEEE 754 binary floating point

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