Scalable Distributed High-Order Stencil Computations
Mathias Jacquelin, Mauricio Araya-Polo, Jie Meng
摘要
Stencil computations lie at the heart of many scientific and industrial applications. Stencil algorithms pose several challenges on machines with cache based memory hierarchy, due to low re-use of memory accesses if special care is not taken to optimize them. This work shows that for stencil computation a novel algorithm that leverages a localized communication strategy effectively exploits the second generation Cerebras Wafer-Scale Engine (WSE-2), which has no cache hierarchy. This study focuses on a 25-point stencil finite-difference method for the 3D wave equation, a kernel frequently used in earth modeling as numerical simulation. In essence, the algorithm trades memory accesses for data communication and takes advantage of the fast communication fabric provided by the architecture. The algorithm -historically memory-bound- becomes compute-bound. This allows the implementation to achieve near perfect weak scaling, reaching up to 503 TFLOPs on WSE-2, a figure that only full clusters can eventually yield.
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- ConvStencil: Transform Stencil Computation to Matrix Multiplication on Tensor CoresYuetao Chen, Kun Li, Yuhao Wang, Donglin Bai 等PPoPP 2024 · 被引用 25 次
- LoRAStencil: Low-Rank Adaptation of Stencil Computation on Tensor CoresYiwei Zhang, Kun Li, Liang Yuan, Jiawen Cheng 等SC 2024 · 被引用 13 次
- FlashFFTStencil: Bridging Fast Fourier Transforms to Memory-Efficient Stencil Computations on Tensor Core UnitsHaozhi Han, Kun Li, Wei Cui, Donglin Bai 等PPoPP 2025 · 被引用 7 次
- SARIS: Accelerating Stencil Computations on Energy-Efficient RISC-V Compute Clusters with Indirect Stream RegistersPaul Scheffler, Luca Colagrande, Luca BeniniDAC 2024 · 被引用 3 次
- SparStencil: Retargeting Sparse Tensor Cores to Scientific Stencil Computations via Structured Sparsity TransformationQi Li, Kun Li, Haozhi Han, Liang Yuan 等SC 2025 · 被引用 3 次
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