Relational algorithms for multi-bulk-synchronous processors

Authors:
Gregory Diamos;Haicheng Wu;Jin Wang;Ashwin Lele;Sudhakar Yalamanchili
Affiliations:
NVIDIA Research, Santa Clara, CA, USA;Georgia Institute of Technology, Atlanta, GA, USA;Georgia Institute of Technology, Atlanta, GA, USA;Georgia Institute of Technology, Atlanta, GA, USA;Georgia Institute of Technology, Atlanta, GA, USA
Venue:
Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming
Year:
2013

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Abstract

Relational databases remain an important application infrastructure for organizing and analyzing massive volumes of data. At the same time, processor architectures are increasingly gravitating towards Multi-Bulk-Synchronous processor (Multi-BSP) architectures employing throughput-optimized memory systems, lightweight multi-threading, and Single-Instruction Multiple-Data (SIMD) core organizations. This paper explores the mapping of primitive relational algebra operations onto such architectures to improve the throughput of data warehousing applications built on relational databases.