Hitting the memory wall: implications of the obvious
ACM SIGARCH Computer Architecture News
Database Architecture Optimized for the New Bottleneck: Memory Access
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
DBMSs on a Modern Processor: Where Does Time Go?
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
High-Performance and Scalability through Application Tier,In-Memory Data Management
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Reflections on the memory wall
Proceedings of the 1st conference on Computing frontiers
Fast computation of database operations using graphics processors
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
GPUTeraSort: high performance graphics co-processor sorting for large database management
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Hardware acceleration in commercial databases: a case study of spatial operations
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Relational joins on graphics processors
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Sorting networks and their applications
AFIPS '68 (Spring) Proceedings of the April 30--May 2, 1968, spring joint computer conference
FAST: fast architecture sensitive tree search on modern CPUs and GPUs
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
A balanced programming model for emerging heterogeneous multicore systems
HotPar'10 Proceedings of the 2nd USENIX conference on Hot topics in parallelism
Designing fast architecture-sensitive tree search on modern multicore/many-core processors
ACM Transactions on Database Systems (TODS)
VAST-Tree: a vector-advanced and compressed structure for massive data tree traversal
Proceedings of the 15th International Conference on Extending Database Technology
Parallel multi-dimensional range query processing with R-trees on GPU
Journal of Parallel and Distributed Computing
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Recent approaches exploiting the massively parallel architecture of graphics processors (GPUs) to accelerate database operations have achieved intriguing results. While parallel sorting received significant attention, parallel search has not been explored. With p-ary search we present a novel parallel search algorithm for large-scale database index operations that scales with the number of processors and outperforms traditional thread-level parallel GPU and CPU implementations. With parallel architectures becoming omnipresent, and with searching being a fundamental functionality for many applications, we expect it to be applicable beyond the database domain. While GPUs do not appear to be ready to be adopted for general-purpose database applications yet, given their rapid development, we expect this to change in the near future. The trend towards massively parallel architectures, combining CPU and GPU processing, encourages development of parallel techniques on both architectures.