Abstract

The Q100 uses hardware specialization to improve the energy efficiency of analytic database applications. The proposed accelerators are called database processing units. DPUs are analogous to GPUs, but where GPUs target graphics applications, DPUs target analytic database workloads. This article demonstrates a proof of concept design, called the Q100, which provides one to two orders of magnitude improvement in efficiency over single- and multithreaded software database management systems. The Q100 exploits the innate structure of the workload, viewing the data in terms of tables and columns rather than as an unstructured array of bytes, to more efficiently move and manipulate database content. Because a large proportion of a chip's energy is spent delivering data to the computation engines, this approach both improves overall energy efficiency and complements other specialized computation engines.

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