Abstract
The rapid increase in the data volumes for the past few decades has intensified the need for high processing power for database and data mining applications. Researchers have actively sought to design and develop new architectures for improving the performance. Recent research shows that the performance can be significantly improved using either (a) effective utilization of architectural features and memory hierarchies used by the conventional processors, or (b) the high computational power and memory bandwidth in commodity hardware such as network processing units (NPUs), Cell processors and graphics processing units (GPUs). This tutorial will survey the micro-architectural and architectural differences across these processors with data management in mind, and will present previous work and future opportunities for expanding query processing algorithms to other hardware than general-purpose processors. In addition to the database community, we intend to increase awareness in the computer architecture scene about opportunities to construct heterogeneous chips.
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