A Particle Filter Approach to a Complex Stochastic Problem?

A lot of the singular value decomposition, kind of matrix multiplication stuff, does fit into the map reduce framework. But there's these other new techniques, coming out like these sort of Monte Carlo techniques where okay, I have a thousand nodes, and I have this problem with millions of pieces of data. Well, let me just send a little bit of data to each one of them, have them do their job, and they're gonna be a little bit inaccurate, because we're not working on all the data. They're gonna come up with some answer, then I'm gonna collect all the answers, and kind of average it out. Is that like a particle filter approach, or?