Patrick_Hutecker said:
The number I'm producing is something and its called infinity. You can't show infinity on a computer, which doesn't make it false or not a concept. Just because their isn't enough ram to make my number doesn't mean it does exist.
You are using "int y=100000000;" and the int64 unsigned range is 0 to 18,446,744,073,709,551,615 which is quite far from both infinity and Graham's number ...
Now, it's true that you can "show" many (virtual) things on a computer (including flying dogs), and one way to handle extremely large numbers is the binary64 double-precision floating-point format, with a max exponent of 1023, however the numbers you get is rounded approximations and does not qualify as a real number.
Beyond that, there is
Arbitrary-precision arithmetic, that was originally implemented in
Lisp and nowadays is supported in most modern languages like Java, Ruby, C/C++, etc. Using this technique, the digits of precision are limited only by the available memory of the host system (including integer). The processing speed is naturally much slower, since fast CPU registers can not be utilized as normal.
This brings us back to the "Observable Universe Samsung Semiconductor Plant", which is the final inexorable bottleneck for digital precision computing.
Why!?
Well, let's say Samsung finds a very clever way to utilize every particle in the observable universe for storing one digital bit (1/0) — how man many bits can we store?
10^{90} bits
Normally the approximation is 10^{80} atoms in the observable universe, but
Seth Lloyd (MIT) has published a paper
Computational capacity of the universe where he calculate the number of bosons and fermions (particles/antiparticles) and thus get the bigger number (he also take gravitational energy into account but that's overkill = 10^{120} bits).
So, how big is the digital number Samsung/Seth Lloyd can ever store in the entire observable universe?
2^{10^{90}}
That's a very big number, and I tried the
Big Online Calculator (with 2048 bits mantissa and 256 bits exponent) but it halted at 2^{10^{76}} and returned:
1.75\times 10^{301029995663981195213738894724493026768189 8814621085413104274611271081892744}
Not giving the full picture, that's a hefty number ...
But how hefty is it in comparison with the Real Monsters? Well, we can directly see that the 'tiny' (in this league) Googolplex 10^{10^{100}} is already much bigger.
Conclusion:
If you use a digital computer to find the largest number — you're doomed to lose.
(And that goes for seconds and abacus as well, unless you plan to live longer than the universe! 
)
