Parametric multi-step scheme for GPU-accelerated graph decomposition into strongly connected components

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00100646" target="_blank" >RIV/00216224:14330/17:00100646 - isvavai.cz</a>

Alternative codes found

RIV/00216305:26230/16:PU126379

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-319-58943-5_42" target="_blank" >http://dx.doi.org/10.1007/978-3-319-58943-5_42</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-58943-5_42" target="_blank" >10.1007/978-3-319-58943-5_42</a>

Result language

angličtina

Original language name

Parametric multi-step scheme for GPU-accelerated graph decomposition into strongly connected components

Original language description

The problem of decomposing a directed graph into strongly connected components (SCCs) is a fundamental graph problem that is inherently present in many scientific and commercial applications. Clearly, there is a strong need for good high-performance, e.g., GPU-accelerated, algorithms to solve it. Unfortunately, among existing GPU-enabled algorithms to solve the problem, there is none that can be considered the best on every graph, disregarding the graph characteristics. Indeed, the choice of the right and most appropriate algorithm to be used is often left to inexperienced users. In this paper, we introduce a novel parametric multi-step scheme to evaluate existing GPU-accelerated algorithms for SCC decomposition in order to alleviate the burden of the choice and to help the user to identify which combination of existing techniques for SCC decomposition would fit an expected use case the most. We support our scheme with an extensive experimental evaluation that dissects correlations between the internal structure of GPU-based algorithms and their performance on various classes of graphs. The measurements confirm that there is no algorithm that would beat all other algorithms in the decomposition on all of the classes of graphs. Our contribution thus represents an important step towards an ultimate solution of automatically adjusted scheme for the GPU-accelerated SCC decomposition.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016

ISBN

9783319589428

ISSN

0302-9743

e-ISSN

—

Number of pages

13

Pages from-to

519-531

Publisher name

Springer Verlag

Place of publication

Cham

Event location

Grenoble; France

Event date

Jan 1, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000529303100042