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Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system

Linchuan Li, Xingjian Li, Guangming Tan, Mingyu Chen, Peiheng Zhang
Key Laboratory of Computer System and Architecture, Institute of Computing Technology, Chinese Academy of Science, Beijing, China
Proceedings of the 20th international symposium on High performance distributed computing, HPDC ’11, 2011

@inproceedings{li2011experience,

   title={Experience of parallelizing cryo-EM 3D reconstruction on a CPU-GPU heterogeneous system},

   author={Li, L. and Li, X. and Tan, G. and Chen, M. and Zhang, P.},

   booktitle={Proceedings of the 20th international symposium on High performance distributed computing},

   pages={195–204},

   year={2011},

   organization={ACM}

}

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Heterogeneous architecture is becoming an important way to build a massive parallel computer system, i.e. the CPU-GPU heterogeneous systems ranked in Top500 list. However, it is a challenge to efficiently utilize massive parallelism of both applications and architectures on such heterogeneous systems. In this paper we present a practice on how to exploit and orchestrate parallelism at algorithm level to take advantage of underlying parallelism at architecture level. A potential Petaflops application — cryo-EM 3D reconstruction is selected as an example. We exploit all possible parallelism in cryo-EM 3D reconstruction, and leverage a self-adaptive dynamic scheduling algorithm to create a proper parallelism mapping between the application and architecture. The parallelized programs are evaluated on a subsystem of Dawning Nebulae supercomputer, whose node is composed of two Intel six-core Xeon CPUs and one Nvidia Fermi GPU. The experiment confirms that hierarchical parallelism is an efficient pattern of parallel programming to utilize capabilities of both CPU and GPU in a heterogeneous system. The CUDA kernels run more than 3 times faster than the OpenMP parallelized ones using 12 cores (threads). Based on the GPU-only version, the hybrid CPU-GPU program further improves the whole application’s performance by 30% on the average.
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