Parallel pseudorandom number generators
There seem to be many ways to tackle this problem, but one simple way would be to use the Blum Blum Shub PRNG. This PRNG is defined by the recurrance relation $x_{i+1} = x_i^2 \mbox{ mod }N$, where $N$ is a semiprime. To get a random bit out of this you can simply take the bit parity of $x_i$. What's nice about this is that since $x_{i+k} = x_i^{2^k}\mbox{ mod }N = x_i^{2^k \mbox{ mod } \lambda(N)}\mbox{mod }N$ you can directly calculate any step in time constant in $k$ (i.e. $O(\log(N)^3)$ or faster depending on which multiplication algorithm you use for the modular exponential). Thus is you have $M$ machines, then for the machine indexed by $y$ you can use the generator $x_{i+1,y} = x_i^{2^M \mbox{mod }\lambda(N)}\mbox{ mod }N$, where $x_{0,y} = x_0^{2^y \mbox{ mod }\lambda(N)}\mbox{ mod }N$, where $x_0$ is your seed. Conveniently this generates exactly the same stream of numbers as if you used a single stream and distributed it's output to each of the machines in turn.

This isn't the fastest of PRNGs, though, so it will only be useful if the overhead of whatever you are doing in the simulation is significantly more than the cost of the PRNG. However it is worth pointing out that it will be much faster for certain combinations of $M$ and $N$ than others, particularly if the binary representation of $2^M \mbox{ mod }\lambda(N)$ contains few 1s or is small.