16896

GPU SQL Query Accelerator

Keh Kok Yong, Hong Hoe Ong, Vooi Voon Yap
Accelerative Technology Lab, MIMOS Berhad, Kuala Lumpur, Malaysia
International Journal of Information Technology, Vol.22, No.1, 2016

@article{yong2016gpu,

   title={GPU SQL Query Accelerator},

   author={Yong, Keh Kok and Ong, Hong Hoe and Yap, Vooi Voon},

   journal={International Journal of Information Technology},

   volume={22},

   number={1},

   year={2016}

}

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The world rapidly grows with every connected sensors and devices with geo-location capabilities to update its location. Data analytic industries are finding ways to store the data, and also turn this raw data into valuable information as an eminent business intelligence services. It has inadvertently conformed a flood of granular data about our world. Crucially, this data flood has outpaced the traditional compute capabilities to process and analyze it. Thus, it reveals the potential economic benefits and becomes an overwhelming new research area that requiring sophisticated mechanisms and technologies to reach the demand. Over the past decade, there have attempts of using accelerators along with multicore CPUs in boosting large-scale data computation. We proposed an emerging SQL-like query accelerator, Mi-Galactica. In addition, we extended our system by offloading geo-spatial computation to the GPU devices. The query operation executes parallelly with drawing support from a high performance and energy efficient NVIDIA Tesla technology. Our result has shown the significant speedup.
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