Abstract
High-performance computing (HPC) platforms become an important technology to support computational research. The design of HPC architecture at each organization depends on several factors. In this paper, we survey five HPC services and discuss their differences. We then presented the HPC service at Chiang Mai University, namely, ERAWAN HPC. Our HPC platform was designed based on the requirements of researchers and the knowledge received from the observational study. By benchmarking with LINPACK, the ERAWAN HPC exhibits its floating-point computing power of 131,500 GFlops. We use AI benchmarks with different convolutional neural network models to evaluate the training runtime. The results indicate that the GPUs equipped in ERAWAN HPC could help to reduce the computation duration significantly.
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References
Marksteiner, P.: High-performance computing — an overview. Comput. Phys. Commun. 97(1–2), 16–35 (1996)
Dongarra, J.: An overview of high performance computing and challenges for the future. In: Palma, J.M.L.M., Amestoy, P.R., Daydé, M., Mattoso, M., Lopes, J.C. (eds.) VECPAR 2008. LNCS, vol. 5336, pp. 1–1. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-92859-1_1
NSTDA Supercomputer Center. thaisc.io/. Accessed 5 May 2023
CHALAWAN-NARIT High Performance Computing. chalawan.narit.or.th/home. Accessed 6 May 2023
HPC Service | UBDA. www.polyu.edu.hk/ubda. Accessed 5 May 2023
Bashar, Dr. Abul.: Survey on evolving deep learning neural network architectures. J. Artif. Intell. Capsule Netw. 2019(2), 73–82 (2019)
Abiodun, O.I., et al.: State-of-the-art in artificial neural network applications: a survey. Heliyon 4(11), e00938 (2018)
Shanmugamani, Rajalingappaa. Deep Learning for Computer Vision Expert Techniques to Train Advanced Neural Networks Using TensorFlow and Keras. Packt Publishing (2018)
HPL - A Portable implementation of the high-performance linpack benchmark for distributed-memory computers. https://netlib.org/benchmark/hpl/ Accessed 2 May 2023
AI Benchmark. ai-benchmark.com/. Accessed 6 May 2023
GROMACS. gromacs.org/. Accessed 1 May 2023
Acknowledgments
This work is supported by One Faculty One MoU (OFOM) and the Quick Win project of Chiang Mai University. The CMU HPC project is supported by the Program Management Unit Competitiveness (PMUC). We especially thank Professor Li Qing, who is the head of the Department of Computing, at the Hong Kong Polytechnic University for supporting us during our observational study at PolyU. We received a lot of meaningful advice on this work.
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Panyadee, P. et al. (2023). ERAWAN HPC: A High-Performance Computing Platform for Data Analysis. In: Barolli, L. (eds) Advances in Networked-based Information Systems. NBiS 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 183. Springer, Cham. https://doi.org/10.1007/978-3-031-40978-3_10
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DOI: https://doi.org/10.1007/978-3-031-40978-3_10
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