Performance evaluation of quantum ESPRESSO on NEC SX-ACE

Osamu Watanabe, Akihiro Musa, Hiroaki Hokari, Shivanshu Singh, Raghunandan Mathur, Hiroaki Kobayashi

研究成果: Conference contribution


In recent years, a lot of computer simulation codes have been developed as open-source software. Meanwhile major processors adopt a concept of a vector processing in high performance computing. Hence, the computer simulation codes need to follow a vector processing manner to have a benefit of a computational potential of the vector processing. Our study is evaluation and analysis of performance of various simulation codes developed as open-source software on several vector architectures. In this paper, we evaluate one package of Quantum ESPRESSO as an open-source software code in materials science. Quantum ESPRESSO makes use of several numerical libraries and it is known that parallel parameters called parallelization levels affect the performance in parallel execution. We discuss adjustability of the code to a vector architecture. Moreover, we clarify that the performance of PWscf, which is one of major packages of Quantum ESPRESSO, depends on numerical libraries and parallelization levels of PWscf. For evaluation of performance, we use a vector-parallel supercomputer system named NEC SX-ACE and an Intel Xeon-based cluster system named NEC LX 406Re-2. From this evaluation, we confirm that the code is suitable for vector architectures. Additionally, we clarify the effectiveness of applying optimum numerical libraries to each architecture with appropriate parallel parameters to obtain the high performance.

ホスト出版物のタイトルProceedings - 2017 IEEE International Conference on Cluster Computing, CLUSTER 2017
出版社Institute of Electrical and Electronics Engineers Inc.
出版ステータスPublished - 2017 9月 22
イベント2017 IEEE International Conference on Cluster Computing, CLUSTER 2017 - Honolulu, United States
継続期間: 2017 9月 52017 9月 8


名前Proceedings - IEEE International Conference on Cluster Computing, ICCC


Other2017 IEEE International Conference on Cluster Computing, CLUSTER 2017
国/地域United States

ASJC Scopus subject areas

  • ソフトウェア
  • ハードウェアとアーキテクチャ
  • 信号処理


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