Paper Info
Title
Relational algorithms for multi-bulk-synchronous processors
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.
Year
DOI
Venue
2013
10.1145/2442516.2442555
PPOPP
Keywords
Field
DocType
core organization,single-instruction multiple-data,massive volume,processor architecture,multi-bulk-synchronous processor,primitive relational algebra operation,lightweight multi-threading,relational databases,important application infrastructure,data warehousing application,relational algorithm,gpgpu,relational algebra
Data warehouse,Relational database,CUDA,Computer science,Parallel computing,SIMD,Theoretical computer science,Relational algebra,General-purpose computing on graphics processing units,Throughput,Design space exploration,Distributed computing
Conference
Volume
Issue
ISSN
48
8
0362-1340
Citations 
PageRank 
References 
12
0.69
17
Authors
5
Name
Order
Citations
PageRank
Gregory Frederick Diamos1111751.07
Haicheng Wu22048.42
Jin Wang31175.80
Ashwin Lele4121.36
Sudhakar Yalamanchili51836184.95