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Relational Joins On Gpus For In-Memory Database Query Processing, Ran Rui
Relational Joins On Gpus For In-Memory Database Query Processing, Ran Rui
USF Tampa Graduate Theses and Dissertations
Relational join processing is one of the core functionalities in database management systems. Implementing join algorithms on parallel platforms, especially modern GPUs, has gain a lot of momentum in the past decade. This dissertation addresses the following issues on GPU join algorithms. First, we present empirical evaluations of a state-of-the-art work on GPU-based join processing. Since 2008, the compute capabilities of GPUs have increased following a pace faster than that of the multi-core CPUs. We run a comprehensive set of experiments to study how join operations can benefit from such rapid expansion of GPU capabilities. We also present improved GPU …
Algorithms And Framework For Computing 2-Body Statistics On Graphics Processing Units, Napath Pitaksirianan
Algorithms And Framework For Computing 2-Body Statistics On Graphics Processing Units, Napath Pitaksirianan
USF Tampa Graduate Theses and Dissertations
Various types of two-body statistics (2-BS) are regarded as essential components of low-level data analysis in scientific database systems. In relational algebraic terms, a 2-BS is essentially a Cartesian product between two datasets (or two instances of the same dataset) followed by a user-defined aggregate. The quadratic complexity of these computations hinders the timely processing of data. Thus using modern parallel hardware has become an obvious solution to meet such challenges. This dissertation presents our recent work in designing and optimizing parallel algorithms for 2-BS computation on Graphics Processing Units (GPUs). The unique architecture, however, provides abundant opportunities for optimizing …