GPU performance analysis for viscoacoustic wave equations using fast stencil computation from the symbolic specification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-023-05178-3.pdf
Reference26 articles.
1. Carrijo Nasciutti T, Panetta J, Pais Lopes P (2019) Evaluating optimizations that reduce global memory accesses of stencil computations in GPGPUs. Concurr Comput Pract Exp 31(18):4929. https://doi.org/10.1002/cpe.4929
2. Sano K, Yamamoto S, Hatsuda Y (2011) Domain-specific programmable design of scalable streaming-array for power-efficient stencil computation. ACM SIGARCH Comput Archit News 39(4):44–49. https://doi.org/10.1145/2082156.2082168
3. Said I (2015) Contributions of hybrid architectures to depth imaging: a CPU, APU and GPU comparative study. PhD thesis, Université Pierre et Marie Curie-Paris VI
4. Kukreja N, Louboutin M, Vieira F, Luporini F, Lange M, Gorman G (2016) Devito: Automated fast finite difference computation. In: 2016 Sixth International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing (WOLFHPC), pp. 11–19. https://doi.org/10.1109/WOLFHPC.2016.06. IEEE
5. Lange M, Kukreja N, Louboutin M, Luporini F, Vieira F, Pandolfo V, Velesko P, Kazakas P, Gorman G (2016) Devito: towards a generic finite difference dsl using symbolic python. In: 2016 6th Workshop on Python for High-Performance and Scientific Computing (PyHPC), pp. 67–75. https://doi.org/10.48550/arXiv.1609.03361. IEEE
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