English

A nearly-mlogn time solver for SDD linear systems

Data Structures and Algorithms 2011-08-22 v4

Abstract

We present an improved algorithm for solving symmetrically diagonally dominant linear systems. On input of an n×nn\times n symmetric diagonally dominant matrix AA with mm non-zero entries and a vector bb such that Axˉ=bA\bar{x} = b for some (unknown) vector xˉ\bar{x}, our algorithm computes a vector xx such that xxˉA<ϵxˉA||{x}-\bar{x}||_A < \epsilon ||\bar{x}||_A {A||\cdot||_A denotes the A-norm} in time O~(mlognlog(1/ϵ)).{\tilde O}(m\log n \log (1/\epsilon)). The solver utilizes in a standard way a `preconditioning' chain of progressively sparser graphs. To claim the faster running time we make a two-fold improvement in the algorithm for constructing the chain. The new chain exploits previously unknown properties of the graph sparsification algorithm given in [Koutis,Miller,Peng, FOCS 2010], allowing for stronger preconditioning properties. We also present an algorithm of independent interest that constructs nearly-tight low-stretch spanning trees in time O~(mlogn)\tilde{O}(m\log{n}), a factor of O(logn)O(\log{n}) faster than the algorithm in [Abraham,Bartal,Neiman, FOCS 2008]. This speedup directly reflects on the construction time of the preconditioning chain.

Keywords

Cite

@article{arxiv.1102.4842,
  title  = {A nearly-mlogn time solver for SDD linear systems},
  author = {Ioannis Koutis and Gary Miller and Richard Peng},
  journal= {arXiv preprint arXiv:1102.4842},
  year   = {2011}
}

Comments

to appear in FOCS11

R2 v1 2026-06-21T17:30:49.552Z