A demonstration of MAGiQ
| Autor: | Fuad Jamour, Ibrahim Abdelaziz, Panos Kalnis |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
020203 distributed computing
Theoretical computer science business.industry Computer science General Engineering 02 engineering and technology computer.file_format Porting Software 020204 information systems Scalability 0202 electrical engineering electronic engineering information engineering SPARQL Graph (abstract data type) Enhanced Data Rates for GSM Evolution RDF business computer Sparse matrix |
| Zdroj: | Proceedings of the VLDB Endowment. 11:1978-1981 |
| ISSN: | 2150-8097 |
| DOI: | 10.14778/3229863.3236239 |
| Popis: | Existing RDF engines follow one of two design paradigms: relational or graph-based. Such engines are typically designed for specific hardware architectures, mainly CPUs, and are not easily portable to new architectures. Porting an existing engine to a different architecture (e.g., many-core architectures) entails almost redesign from scratch. We explore sparse matrix algebra as a third paradigm for designing a portable, scalable, and efficient RDF engine. We demonstrate MAGiQ; a matrix algebra approach for evaluating complex SPARQL queries over large RDF datasets. MAGiQ represents an RDF graph as a sparse matrix, and translates SPARQL queries to matrix algebra programs. MAGiQ takes advantage of the existing rich software infrastructure for processing sparse matrices, optimized for many architectures (e.g., CPUs, GPUs, distributed), effortlessly. This demo motivates the adoption of matrix algebra in RDF graph processing by showing MAGiQ's performance with different matrix algebra backend engines. MAGiQ, using a GPU, is orders of magnitude faster in solving complex queries on a billion edge graph than state-of-the-art RDF systems. |
| Databáze: | OpenAIRE |
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