An efficient transitive closure algorithm for cyclic digraphs
Information Processing Letters
Journal of the ACM (JACM)
Implementation techniques for main memory database systems
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Scan primitives for GPU computing
Proceedings of the 22nd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware
Minimal Deductive Systems for RDF
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
RDF-3X: a RISC-style engine for RDF
Proceedings of the VLDB Endowment
Query execution in column-oriented database systems
Query execution in column-oriented database systems
RDFS Reasoning and Query Answering on Top of DHTs
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Designing efficient sorting algorithms for manycore GPUs
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
DBpedia - A crystallization point for the Web of Data
Web Semantics: Science, Services and Agents on the World Wide Web
Scalable Distributed Reasoning Using MapReduce
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Parallel Materialization of the Finite RDFS Closure for Hundreds of Millions of Triples
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Web Semantics: Science, Services and Agents on the World Wide Web
IEEE Micro
Concurrent classification of EL ontologies
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
Practical RDF schema reasoning with annotated semantic web data
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
Parallel ABox reasoning of EL ontologies
JIST'11 Proceedings of the 2011 joint international conference on The Semantic Web
YAGO2: A spatially and temporally enhanced knowledge base from Wikipedia
Artificial Intelligence
Query generation for semantic datasets
Proceedings of the seventh international conference on Knowledge capture
Hi-index | 0.00 |
Recent developments in hardware have shown an increase in parallelism as opposed to clock rates. In order to fully exploit these new avenues of performance improvement, computationally expensive workloads have to be expressed in a way that allows for fine-grained parallelism. In this paper, we address the problem of describing RDFS entailment in such a way. Different from previous work on parallel RDFS reasoning, we assume a shared memory architecture. We analyze the problem of duplicates that naturally occur in RDFS reasoning and develop strategies towards its mitigation, exploiting all levels of our architecture. We implement and evaluate our approach on two real-world datasets and study its performance characteristics on different levels of parallelization. We conclude that RDFS entailment lends itself well to parallelization but can benefit even more from careful optimizations that take into account intricacies of modern parallel hardware.