On Sort-Merge Algorithm for Band Joins
IEEE Transactions on Knowledge and Data Engineering
A Truncating Hash Algorithm for Processing Band-Join Queries
Proceedings of the Ninth International Conference on Data Engineering
Data Streams: Models and Algorithms (Advances in Database Systems)
Data Streams: Models and Algorithms (Advances in Database Systems)
Maximizing the output rate of multi-way join queries over streaming information sources
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Processing sliding window multi-joins in continuous queries over data streams
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Executing stream joins on the cell processor
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Relational joins on graphics processors
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
A Fast Similarity Join Algorithm Using Graphics Processing Units
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Using the graphics processor unit to realize data streaming operations
Proceedings of the 6th Middleware Doctoral Symposium
How soccer players would do stream joins
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
The tradeoffs of fused memory hierarchies in heterogeneous computing architectures
Proceedings of the 9th conference on Computing Frontiers
Exploiting Coarse-Grained Parallelism in B+ Tree Searches on an APU
SCC '12 Proceedings of the 2012 SC Companion: High Performance Computing, Networking Storage and Analysis
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Upcoming processors are combining different computing units in a tightly-coupled approach using a unified shared memory hierarchy. This tightly-coupled combination leads to novel properties with regard to cooperation and interaction. This paper demonstrates the advantages of those processors for a stream-join operator as an important data-intensive example. In detail, we propose our HELLS-Join approach employing all heterogeneous devices by outsourcing parts of the algorithm on the appropriate device. Our HELLS-Join performs better than CPU stream joins, allowing wider time windows, higher stream frequencies, and more streams to be joined as before.