high performance computing on graphics processing units: hgpu.org

In the last decades, rising energy consumption and production became one of the main problems of humanity. Energy efficiency can help save energy. GPUs are an example of highly energy-efficient hardware. However, energy efficiency is not enough, energy proportionality is needed. The objective of this work is to create an entire platform that allows execution of GPU operators in an energy proportional DBMS, WattBD, and also a GPU Sort operator to prove that this new platform works. A different approach to integrate the GPU into the database has been used. Existing solutions to this problem aims to optimize specific areas of the DBMS, or provides extensions to the SQL language to specify GPU operation, thus, lacking flexibility to optimize all database operations, or provide transparency of the GPU execution to the user. This framework differs from existing strategies manipulating the creation and insertion of GPU operators directly into the query plan tree, allowing a more flexible and transparent framework to integrate new GPU-enabled operators. Results show that it was possible to easily develop a GPU sort operator with this framework. We believe that this framework will allow a new approach to integrate GPUs into existing databases, and therefore achieve more energy efficient DBMS.