Abstract
A lot of different indexes have been developed for accelerating search operations on large data sets. Search trees, representing the most prominent class, are ubiquitous in database management systems but are also widely used in non-DBMS applications. An approach for lowering the implementation complexity of these structures are index frameworks like generalized search trees (GiST). Common data management operations are implemented within the framework which can be specialized by data organization and evaluation strategies in order to model the actual index type. These frameworks are particularly useful in scientific and engineering applications where characteristics of the underlying data set are not known a priori and a lot of prototyping is required in order to find suitable index structures for the workload.
However, existing frameworks only abstract data organization and data maintenance aspects to model different index families, while traversal operations for executing searches are implemented serially. This paper presents an approach for enabling parallel processing in GiST in order to leverage the full power of parallel processor architectures for different index implementations at once. Further, results of a prototypical implementation are evaluated on a hybrid CPU/GPU system architecture to verify the applicability of this generic framework idea on different hardware platforms.
About the authors
Felix Beier studied Computer Science at the Technische Universität Ilmenau, Germany and received his Diploma (M. Sc.) in 2010. Since May 2010, he is a Ph. D. student in the Database and Information Systems group at the Department of Computer Science and Automation and the Graduate School for Image Processing and Image Interpretation of the Technische Universität Ilmenau. In his Ph. D. research he develops a framework for accelerating generalized index structures on massively parallel processor architectures and received an IBM Ph. D. Fellowship Award for his work in 2013. In August 2015, he joined IBM in Böblingen and works as software engineer in the IBM DB2 Analytics Accelerator for z/OS team.
IBM Deutschland Research & Development GmbH, Schönaicher Str. 220, 71032 Böblingen, Germany
Kai-Uwe Sattler leads the Database and Information Systems group at the Department of Computer Science and Automation of the TU Ilmenau, Germany. He received his Diploma (M. Sc.) in Computer Science from the University of Magdeburg, Germany. In 1998, he received his Ph. D. and in 2003 his Habilitation (venia legendi) in Computer Science from the same university. From 1998 to September 2003 he was a member of the Database research group at the University of Magdeburg. From October 2001 until March 2002, he worked as a visiting assistant professor at the UC Davis, US. Kai-Uwe Sattler published more than 200 reviewed research papers in conference proceedings and international journals as well as 8 textbooks on database systems and algorithms. Currently, he serves as the coordinator of the DFG Priority Program SPP-2037 “Scalable Data Management for Future Hardware”.
Technische Universität Ilmenau, Databases and Information Systems Group, Postfach 100 565, 98684 Ilmenau, Germany
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