It's very likely that multiple instances, if run in parallel and with no data sharing, will explore a lot of the same space.
Also, making a public cluster would be a security challenge. It runs arbitrary C/C++ code, and can trigger code paths that the developers didn't even realize. How would your box stand up to multiple grabs of 4GB of memory?
Security would be an issue. A VM would probably be a hard requirement. That can bound the memory usage, hardware calls, etc.
Nor is it obvious that state reporting is useful. I ran afl for about 4 days. It ran my test code about 1,000 times per second, for a total of nearly 1/2 billion test cases.
That's a lot of data exchange for each program to report and resynchronize.
I'm not saying it's impossible. I'm suggesting that it's likely not worthwhile. It would be better to support multiprocessing first, before looking towards distributed computing.
By parallelized, do you mean on the same machine or across a distributed cluster? If they only share the same set of interesting inputs, won't the different nodes also end up searching much of the same space? .... Hmm, no I see how I could be wrong. With interesting seeds, boring space is easy to re-identify, so there's a trivial amount of duplicate work, and the rest is spent just trying to find something new and interesting.