Pi and e In Binary
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Some people are curious about the binary representations of the mathematical constants pi and e. Mathematically, they’re like every other irrational number — infinite strings of 0s and 1s (with no discernible pattern). In a computer, they’re finite, making them only approximations to their true values. I will show you what their approximations look like in five different levels of binary floating-point precision.

The first 43 bits of pi and e
Binary Floating-Point Formats
In binary floating-point, infinitely precise values are rounded to finite precision. Here’s how rounding works in five different levels of precision:
- In half-precision, values are rounded to 11 significant bits.
- In single-precision, values are rounded to 24 significant bits.
- In double-precision, values are rounded to 53 significant bits.
- In extended-precision, values are rounded to 64 significant bits.
- In quadruple-precision, values are rounded to 113 significant bits.
The rounding rule used most often in practice is round-to-nearest, round-half-to-even; that’s the rule I will use. For pi and e, there are no “half to even” cases, since their binary expansions are infinite. This makes the rounding rule simple: if the rounding bit is 0, round down; if the rounding bit is 1, round up.
I will show the correctly rounded approximations of pi and e in these five formats.
Pi (π)
Here are the first 50 decimal digits of pi:
3.1415926535897932384626433832795028841971693993751…
Here are the first 128 bits of pi:
11.00100100001111110110101010001000100001011010001100001000110100 1100010011000110011000101000101110000000110111000001110011010001...
Here are the 128 bits again, with the rounding bit for each level of precision highlighted (bits 12, 25, 54, 65, and 114):
11.00100100001111110110101010001000100001011010001100001000110100 1100010011000110011000101000101110000000110111000001110011010001...
Here are the correctly rounded values of pi in each of the five levels of precision, shown in normalized binary scientific notation and as hexadecimal floating-point constants:
Half-Precision
pi = 1.1001001 x 21 = 0x1.92p+1
This equals 3.140625 in decimal (all binary floating-point numbers have exact decimal representations), which approximates pi accurately to about 4 decimal digits.
(You can verify this conversion by hand, by adding the powers of two corresponding to the positions of the 1 bits: 11.001001 = 21 + 20 + 2-3 + 2-6 = 3.140625.)
Single-Precision
pi = 1.10010010000111111011011 x 21 = 0x1.921fb6p+1
This equals 3.1415927410125732421875, which approximates pi accurately to about 8 decimal digits.
Double-Precision
pi = 1.1001001000011111101101010100010001000010110100011 x 21 = 0x1.921fb54442d18p+1
This equals 3.141592653589793115997963468544185161590576171875, which approximates pi accurately to about 16 decimal digits.
Extended-Precision
pi = 1.100100100001111110110101010001000100001011010001100001000110
101 x 21
= 0x1.921fb54442d1846ap+1
This equals
3.14159265358979323851280895940618620443274267017841339111328125
which approximates pi accurately to about 20 decimal digits.
Quadruple-Precision
pi = 1.100100100001111110110101010001000100001011010001100001000110
1001100010011000110011000101000101110000000110111 x 21
= 0x1.921fb54442d18469898cc51701b8p+1
This equals
3.141592653589793238462643383279502797479068098137295573004504331
874296718662975536062731407582759857177734375
which approximates pi accurately to about 35 decimal digits.
Euler’s Number (e)
Here are the first 50 decimal digits of e:
2.7182818284590452353602874713526624977572470936999…
Here are the first 128 bits of e:
10.10110111111000010101000101100010100010101110110100101010011010 1010111111011100010101100010000000100111001111010011110011110001...
Here are the 128 bits again, with the rounding bits for each level of precision highlighted:
10.10110111111000010101000101100010100010101110110100101010011010 1010111111011100010101100010000000100111001111010011110011110001...
Here are the correctly rounded values of e in each of the five levels of precision:
Half-Precision
e = 1.010111 x 21 = 0x1.5cp+1
This equals 2.71875, which approximates e accurately to about 4 decimal digits.
Single-Precision
e = 1.010110111111000010101 x 21 = 0x1.5bf0a8p+1
This equals 2.71828174591064453125, which approximates e accurately to about 8 decimal digits.
Double-Precision
e = 1.0101101111110000101010001011000101000101011101101001 x 21 = 0x1.5bf0a8b145769p+1
This equals 2.718281828459045090795598298427648842334747314453125, which approximates e accurately to about 16 decimal digits.
Extended-Precision
e = 1.010110111111000010101000101100010100010101110110100101010011
011 x 21
= 0x1.5bf0a8b145769536p+1
This equals
2.71828182845904523542816810799394033892895095050334930419921875
which approximates e accurately to about 20 decimal digits.
Quadruple-Precision
e = 1.010110111111000010101000101100010100010101110110100101010011
010101011111101110001010110001000000010011100111101 x 21
= 0x1.5bf0a8b1457695355fb8ac404e7ap+1
This equals
2.718281828459045235360287471352662314358421867193548862669230860
32766716801933881697550532408058643341064453125
which approximates e accurately to about 34 decimal digits.

(6 votes, average: 4.50 out of 5)
June 22nd, 2012 at 4:02 pm
this is pretty pointless…why does it matter how to convert to different floating point precisions?
June 24th, 2012 at 11:35 pm
@Anonymous (sorry for the delay — your comment was marked as spam),
This article was a response to regular searches on my site for “pi in binary” and “e in binary”. My approach was to show how they look in binary in a computer, in IEEE floating-point in particular. This allowed me to give examples of correct rounding and to show how different levels of binary precision correspond to different levels of decimal precision. And as a side effect, I’ve given hex constants that can be copied and used in code that requires correctly rounded values of these constants.