PaScaL_TDMA 2.0: A multi-GPU-based library for solving massive tridiagonal systems
- Authors
- Yang, Mingyu; Kang, Ji-Hoon; Kim, Ki-Ha; Kwon, Oh-Kyoung; Choi, Jung-Il
- Issue Date
- Sep-2023
- Publisher
- ELSEVIER
- Citation
- COMPUTER PHYSICS COMMUNICATIONS, v.290
- Journal Title
- COMPUTER PHYSICS COMMUNICATIONS
- Volume
- 290
- URI
- https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/6725
- DOI
- 10.1016/j.cpc.2023.108785
- ISSN
- 0010-4655
1879-2944
- Abstract
- We introduce an updated library, PaScaL_TDMA 2.0, which was originally designed for the efficient computation of batched tridiagonal systems and is now capable of exploiting multi-GPU environments. The library extends its functionality to include GPU support and minimizes CPU-GPU data transfer by utilizing the device-resident memory while retaining the original CPU-based capabilities. The library employs pipeline copying with shared memory for low-latency memory access and incorporates CUDA-aware MPI for efficient multi-GPU communication. Our GPU implementation demonstrated outstanding computational performance compared to the original CPU implementation while consuming much less energy. In summary, this updated version presents a time-efficient and energy-saving approach for solving batched tridiagonal systems on modern computing platforms, including both GPU and CPU.
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Collections - College of Science > 이과대학 수학 > 1. Journal Articles
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