English

Abstract Graph Machine

Distributed, Parallel, and Cluster Computing 2016-04-29 v2

Abstract

An Abstract Graph Machine(AGM) is an abstract model for distributed memory parallel stabilizing graph algorithms. A stabilizing algorithm starts from a particular initial state and goes through series of different state changes until it converges. The AGM adds work dependency to the stabilizing algorithm. The work is processed within the processing function. All processes in the system execute the same processing function. Before feeding work into the processing function, work is ordered using a strict weak ordering relation. The strict weak ordering relation divides work into equivalence classes, hence work within a single equivalence class can be processed in parallel, but work in different equivalence classes must be executed in the order they appear in equivalence classes. The paper presents the AGM model, semantics and AGM models for several existing distributed memory parallel graph algorithms.

Keywords

Cite

@article{arxiv.1604.04772,
  title  = {Abstract Graph Machine},
  author = {Thejaka Amila Kanewala and Marcin Zalewski and Andrew Lumsdaine},
  journal= {arXiv preprint arXiv:1604.04772},
  year   = {2016}
}

Comments

10 pages, including Appendix and References

R2 v1 2026-06-22T13:33:55.977Z