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Accelerating Seismic Simulations Using the Intel Xeon Phi Knights Landing Processor

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Book cover High Performance Computing (ISC High Performance 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10266))

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Abstract

In this work we present AWP-ODC-OS, an end-to-end optimization of AWP-ODC targeting homogeneous, manycore supercomputers. AWP-ODC is an established community software package simulating seismic wave propagation using a staggered finite difference scheme which is fourth order accurate in space and second order in time. Recent production simulations, e.g. using the software for the computation of seismic hazard maps, largely relied on GPU accelerated supercomputers. In contrast, our work gives a comprehensive overview of the required steps to achieve near-optimal performance on the Intel® Xeon PhiTM x200 processor (code-named Knights Landing), and compares our competitive performance results to the most recent GPU architectures.

At the level of a single vector operation, we apply the vector folding technique to AWP-ODC-OS, yielding a 1.6\(\times \) performance increase over traditional vectorization. Further, we present a novel strategy utilizing both DDR4 RAM and High Bandwidth Memory, increasing the maximum problem size by 26% while still operating at maximum performance. The presented shared and distributed parallelization carefully schedules work to the cores and ensures overlapping communication and computation. We conclude with a detailed study of AWP-ODC-OS’s full-application performance on the Intel Xeon Phi x200 processor, achieving up to 98.5% of the most recent P100 GPU generation’s performance. Additionally, our weak scaling study on up to 9,000 nodes of the supercomputer Cori Phase II achieves a parallel efficiency of greater than 91%, equivalent to the performance of over twenty thousand NVIDIA Tesla K20X GPUs.

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Notes

  1. 1.

    https://github.com/HPGeoC/awp-odc-os.

  2. 2.

    https://github.com/01org/yask.

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Acknowledgements

We acknowledge support from the National Energy Research Scientific Computing Center (NERSC) for access to the Cori supercomputer. We acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this paper. We thank Jack Deslippe, Sudip Dosanjh and Richard Gerber at NERSC and Lars Koesterke, Tommy Minyard and Dan Stanzione at TACC. The UCSD team was supported by NSF awards ACI-1450451, EAR-1349180, EAR-1135455 and Keck Foundation grant 005590-00001.

Optimization Notice: Software and workloads used in performance tests may have been optimized for performance only on Intel microprocessors. Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more information go to http://www.intel.com/performance. Intel, Xeon, and Intel Xeon Phi are trademarks of Intel Corporation in the U.S. and/or other countries.

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Tobin, J., Breuer, A., Heinecke, A., Yount, C., Cui, Y. (2017). Accelerating Seismic Simulations Using the Intel Xeon Phi Knights Landing Processor. In: Kunkel, J.M., Yokota, R., Balaji, P., Keyes, D. (eds) High Performance Computing. ISC High Performance 2017. Lecture Notes in Computer Science(), vol 10266. Springer, Cham. https://doi.org/10.1007/978-3-319-58667-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-58667-0_8

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