Parallel symbolic state-space exploration is difficult, but what is the alternative?

Details Parallel symbolic state-space exploration is difficult, but what is the alternative? Parallel symbolic state-space exploration is difficult, but what is the alternative?

2009-12-15

arxiv.org/abs/0912.2785v1

EPTCS 14, 2009, pp. 1-17

Computer Science

Logic in Computer Science

Scientific paper

10.4204/EPTCS.14.1

State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal.

Affiliated with

Also associated with

No associations

Rating

Parallel symbolic state-space exploration is difficult, but what is the alternative? does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Parallel symbolic state-space exploration is difficult, but what is the alternative?, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Parallel symbolic state-space exploration is difficult, but what is the alternative? will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-304752