Performance of RDF Query Processing on the Intel SCC

Vasil Slavov (1) , Praveen Rao (1) , Dinesh Barenkala (1) , Srivenu Paturi (1)

1 University of Missouri-Kansas City

Chip makers are envisioning hundreds of cores in future processors for throughput oriented computing. These processors, called manycore processors, require new architectural innovations for scaling to a large number of cores as compared with today's multicore processors. We report an early study on the performance of RDF query processing on a manycore processor. In our study, we use the Intel SCC, an experimental manycore processor from Intel Labs. This processor has new architectural features, namely, 48 Pentium cores, a high speed, on-chip mesh network to communicate between cores and access memory controllers, on-chip message passing buffers for high speed message passing, and software controlled fine-grained power management. We classify queries based on their I/O footprint and study the impact of two standard models, namely, task and data parallel programming models. Based on our experiments with synthetic and real RDF datasets on the SCC, we conclude that the task parallelism model provides an immediate way to boost the performance of RDF query processing.

Mots clés: Many-Core; Intel SCC

Domaines: Calcul parallèle, distribué et partagé [cs.DC]

Vasil Slavov, Praveen Rao, Dinesh Barenkala, Srivenu Paturi. Performance of RDF Query Processing on the Intel SCC. The 6th Many-core Applications Research Community (MARC) Symposium, Jul 2012, Toulouse, France. pp.7-12. ⟨hal-00718955⟩