GPU and ASIC as a Boost for High Performance Computing
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1017-1_9
Reference28 articles.
1. Ouro, P., Lopez-Novoa, U., Guest, M.F.: On the performance of a highly-scalable computational fluid dynamics code on AMD, ARM and Intel processor-based HPC systems. Comput. Phys. Commun. 269, 108105 (2021). https://doi.org/10.1016/j.cpc.2021.108105
2. Mantovani, F., et al.: Performance and energy consumption of HPC workloads on a cluster based on Arm ThunderX2 CPU. Futur. Gener. Comput. Syst. 112, 800–818 (2020). https://doi.org/10.1016/j.future.2020.06.033
3. V./Ml: Exploring the GPU Architecture. https://core.vmware.com/resource/exploring-gpu-architectureforthelatestversion
4. Deluzet, F., Fubiani, G., Garrigues, L., Guillet, C., Narski, J.: Efficient parallelization for 3D–3V sparse grid Particle-In-Cell: single GPU architectures. Comput. Phys. Commun. 289, 108755 (2023). https://doi.org/10.1016/j.cpc.2023.108755
5. Ueda, S., Ogawa, H.: Multi-fidelity approach for global trajectory optimization using GPU-based highly parallel architecture. Aerosp. Sci. Technol. 116, 106829 (2021). https://doi.org/10.1016/j.ast.2021.106829
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