64bit IEEE 754: Decimal ↗ Double Precision Floating Point Binary: -9.954 034 474 611 633 627 Convert the Number to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard, From a Base Ten Decimal System Number

Number -9.954 034 474 611 633 627(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. Start with the positive version of the number:

|-9.954 034 474 611 633 627| = 9.954 034 474 611 633 627

2. First, convert to binary (in base 2) the integer part: 9.
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;
  • 9 ÷ 2 = 4 + 1;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

3. Construct the base 2 representation of the integer part of the number.

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


9(10) =


1001(2)


4. Convert to binary (base 2) the fractional part: 0.954 034 474 611 633 627.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.954 034 474 611 633 627 × 2 = 1 + 0.908 068 949 223 267 254;
  • 2) 0.908 068 949 223 267 254 × 2 = 1 + 0.816 137 898 446 534 508;
  • 3) 0.816 137 898 446 534 508 × 2 = 1 + 0.632 275 796 893 069 016;
  • 4) 0.632 275 796 893 069 016 × 2 = 1 + 0.264 551 593 786 138 032;
  • 5) 0.264 551 593 786 138 032 × 2 = 0 + 0.529 103 187 572 276 064;
  • 6) 0.529 103 187 572 276 064 × 2 = 1 + 0.058 206 375 144 552 128;
  • 7) 0.058 206 375 144 552 128 × 2 = 0 + 0.116 412 750 289 104 256;
  • 8) 0.116 412 750 289 104 256 × 2 = 0 + 0.232 825 500 578 208 512;
  • 9) 0.232 825 500 578 208 512 × 2 = 0 + 0.465 651 001 156 417 024;
  • 10) 0.465 651 001 156 417 024 × 2 = 0 + 0.931 302 002 312 834 048;
  • 11) 0.931 302 002 312 834 048 × 2 = 1 + 0.862 604 004 625 668 096;
  • 12) 0.862 604 004 625 668 096 × 2 = 1 + 0.725 208 009 251 336 192;
  • 13) 0.725 208 009 251 336 192 × 2 = 1 + 0.450 416 018 502 672 384;
  • 14) 0.450 416 018 502 672 384 × 2 = 0 + 0.900 832 037 005 344 768;
  • 15) 0.900 832 037 005 344 768 × 2 = 1 + 0.801 664 074 010 689 536;
  • 16) 0.801 664 074 010 689 536 × 2 = 1 + 0.603 328 148 021 379 072;
  • 17) 0.603 328 148 021 379 072 × 2 = 1 + 0.206 656 296 042 758 144;
  • 18) 0.206 656 296 042 758 144 × 2 = 0 + 0.413 312 592 085 516 288;
  • 19) 0.413 312 592 085 516 288 × 2 = 0 + 0.826 625 184 171 032 576;
  • 20) 0.826 625 184 171 032 576 × 2 = 1 + 0.653 250 368 342 065 152;
  • 21) 0.653 250 368 342 065 152 × 2 = 1 + 0.306 500 736 684 130 304;
  • 22) 0.306 500 736 684 130 304 × 2 = 0 + 0.613 001 473 368 260 608;
  • 23) 0.613 001 473 368 260 608 × 2 = 1 + 0.226 002 946 736 521 216;
  • 24) 0.226 002 946 736 521 216 × 2 = 0 + 0.452 005 893 473 042 432;
  • 25) 0.452 005 893 473 042 432 × 2 = 0 + 0.904 011 786 946 084 864;
  • 26) 0.904 011 786 946 084 864 × 2 = 1 + 0.808 023 573 892 169 728;
  • 27) 0.808 023 573 892 169 728 × 2 = 1 + 0.616 047 147 784 339 456;
  • 28) 0.616 047 147 784 339 456 × 2 = 1 + 0.232 094 295 568 678 912;
  • 29) 0.232 094 295 568 678 912 × 2 = 0 + 0.464 188 591 137 357 824;
  • 30) 0.464 188 591 137 357 824 × 2 = 0 + 0.928 377 182 274 715 648;
  • 31) 0.928 377 182 274 715 648 × 2 = 1 + 0.856 754 364 549 431 296;
  • 32) 0.856 754 364 549 431 296 × 2 = 1 + 0.713 508 729 098 862 592;
  • 33) 0.713 508 729 098 862 592 × 2 = 1 + 0.427 017 458 197 725 184;
  • 34) 0.427 017 458 197 725 184 × 2 = 0 + 0.854 034 916 395 450 368;
  • 35) 0.854 034 916 395 450 368 × 2 = 1 + 0.708 069 832 790 900 736;
  • 36) 0.708 069 832 790 900 736 × 2 = 1 + 0.416 139 665 581 801 472;
  • 37) 0.416 139 665 581 801 472 × 2 = 0 + 0.832 279 331 163 602 944;
  • 38) 0.832 279 331 163 602 944 × 2 = 1 + 0.664 558 662 327 205 888;
  • 39) 0.664 558 662 327 205 888 × 2 = 1 + 0.329 117 324 654 411 776;
  • 40) 0.329 117 324 654 411 776 × 2 = 0 + 0.658 234 649 308 823 552;
  • 41) 0.658 234 649 308 823 552 × 2 = 1 + 0.316 469 298 617 647 104;
  • 42) 0.316 469 298 617 647 104 × 2 = 0 + 0.632 938 597 235 294 208;
  • 43) 0.632 938 597 235 294 208 × 2 = 1 + 0.265 877 194 470 588 416;
  • 44) 0.265 877 194 470 588 416 × 2 = 0 + 0.531 754 388 941 176 832;
  • 45) 0.531 754 388 941 176 832 × 2 = 1 + 0.063 508 777 882 353 664;
  • 46) 0.063 508 777 882 353 664 × 2 = 0 + 0.127 017 555 764 707 328;
  • 47) 0.127 017 555 764 707 328 × 2 = 0 + 0.254 035 111 529 414 656;
  • 48) 0.254 035 111 529 414 656 × 2 = 0 + 0.508 070 223 058 829 312;
  • 49) 0.508 070 223 058 829 312 × 2 = 1 + 0.016 140 446 117 658 624;
  • 50) 0.016 140 446 117 658 624 × 2 = 0 + 0.032 280 892 235 317 248;
  • 51) 0.032 280 892 235 317 248 × 2 = 0 + 0.064 561 784 470 634 496;
  • 52) 0.064 561 784 470 634 496 × 2 = 0 + 0.129 123 568 941 268 992;
  • 53) 0.129 123 568 941 268 992 × 2 = 0 + 0.258 247 137 882 537 984;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (losing precision...)


5. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.954 034 474 611 633 627(10) =


0.1111 0100 0011 1011 1001 1010 0111 0011 1011 0110 1010 1000 1000 0(2)


6. Positive number before normalization:

9.954 034 474 611 633 627(10) =


1001.1111 0100 0011 1011 1001 1010 0111 0011 1011 0110 1010 1000 1000 0(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 3 positions to the left, so that only one non zero digit remains to the left of it:


9.954 034 474 611 633 627(10) =


1001.1111 0100 0011 1011 1001 1010 0111 0011 1011 0110 1010 1000 1000 0(2) =


1001.1111 0100 0011 1011 1001 1010 0111 0011 1011 0110 1010 1000 1000 0(2) × 20 =


1.0011 1110 1000 0111 0111 0011 0100 1110 0111 0110 1101 0101 0001 0000(2) × 23


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): 3


Mantissa (not normalized):
1.0011 1110 1000 0111 0111 0011 0100 1110 0111 0110 1101 0101 0001 0000


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


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


3 + 2(11-1) - 1 =


(3 + 1 023)(10) =


1 026(10)


10. 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;
  • 1 026 ÷ 2 = 513 + 0;
  • 513 ÷ 2 = 256 + 1;
  • 256 ÷ 2 = 128 + 0;
  • 128 ÷ 2 = 64 + 0;
  • 64 ÷ 2 = 32 + 0;
  • 32 ÷ 2 = 16 + 0;
  • 16 ÷ 2 = 8 + 0;
  • 8 ÷ 2 = 4 + 0;
  • 4 ÷ 2 = 2 + 0;
  • 2 ÷ 2 = 1 + 0;
  • 1 ÷ 2 = 0 + 1;

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

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


Exponent (adjusted) =


1026(10) =


100 0000 0010(2)


12. 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. 0011 1110 1000 0111 0111 0011 0100 1110 0111 0110 1101 0101 0001 0000 =


0011 1110 1000 0111 0111 0011 0100 1110 0111 0110 1101 0101 0001


13. 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 0000 0010


Mantissa (52 bits) =
0011 1110 1000 0111 0111 0011 0100 1110 0111 0110 1101 0101 0001


The base ten decimal number -9.954 034 474 611 633 627 converted and written in 64 bit double precision IEEE 754 binary floating point representation:
1 - 100 0000 0010 - 0011 1110 1000 0111 0111 0011 0100 1110 0111 0110 1101 0101 0001

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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