OmniDB: Towards Portable and Efficient Query Processing on Parallel CPU/GPU Architectures

Shuhao Zhang, Jiong He, Bingsheng He, Mian Lu
Nanyang Technological University
VLDB, 2013

   title={Omnidb: Towards portable and efficient query processing on parallel cpu/gpu architectures},

   author={Zhang, Shuhao and He, Jiong and He, Bingsheng and Lu, Mian},

   journal={Proceedings of the VLDB Endowment},





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Driven by the rapid hardware development of parallel CPU/GPU architectures, we have witnessed emerging relational query processing techniques and implementations on those parallel architectures. However, most of those implementations are not portable across different architectures, because they are usually developed from scratch and target at a specific architecture. This paper proposes a kernel-adapter based design (OmniDB), a portable yet efficient query processor on parallel CPU/GPU architectures. OmniDB attempts to develop an extensible query processing kernel (qKernel) based on an abstract model for parallel architectures, and to leverage an architecture-specific layer (adapter) to make qKernel be aware of the target architecture. The goal of OmniDB is to maximize the common functionality in qKernel so that the development and maintenance efforts for adapters are minimized across different architectures. In this demo, we demonstrate our initial efforts in implementing OmniDB, and present the preliminary results on the portability and efficiency
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