Beschreibung

With the ever-growing amount of RDF data available across the Web, the discovery of links between datasets and deduplication of resources within knowledge bases have become tasks of crucial importance. Over the last years, several link discovery approaches have been developed to tackle the runtime and complexity problems that are intrinsic to link discovery. Yet, so far, little attention has been paid to the management of hardware resources for the execution of link discovery tasks. This paper addresses this research gap by investigating the efficient use of hardware resources for link discovery. We implement the HR³ approach for three different parallel processing paradigms including the use of GPUs and MapReduce platforms. We also perform a thorough performance comparison for these implementations. Our results show that certain tasks that appear to require cloud computing techniques can actually be accomplished using standard parallel hardware. Moreover, our evaluation provides break-even points that can serve as guidelines for deciding on when to use which hardware for link discovery.

ESWC 2013 Best Paper Award

The research paper "When to Reach for the Cloud: Using Parallel Hardware for Link Discovery" has received the (shared) Best Paper Award of the 10th Extended Semantic Web Conference (ESWC) in Montpellier. The paper is the result of a close cooperation between the database group and the AKSW team.

Keywords

• Link Discovery
• GPU
• MapReduce
• Data Skew, Load Balancing

BibTex

@inproceedings{DBLP:conf/esws/NgomoKHHAR13,
  author    = {Axel-Cyrille Ngonga Ngomo and
               Lars Kolb and
               Norman Heino and
               Michael Hartung and
               S{\"o}ren Auer and
               Erhard Rahm},
  title     = {{When to Reach for the Cloud: Using Parallel Hardware for
               Link Discovery}},
  booktitle = {ESWC},
  year      = {2013},
  pages     = {275-289},
  ee        = {http://dx.doi.org/10.1007/978-3-642-38288-8_19},
  crossref  = {DBLP:conf/esws/2013},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}