Tile-Level Pipeline for Linear Scalable Stencil Computation on AMD AI Engines

Stencil computation is an essential method, particularly useful for numerical simulations in areas like acoustics, heat transfer, and electromagnetism. Recent studies have utilized AMD AI Engines (AIEs) for stencil computations by configuring multiple AIE tiles within a Compute Unit to exploit task-level parallelism, achieving notable speedup through concurrent task execution. However, this setup suffers from suboptimal performance due to high memory bandwidth demands, resulting in underutilization of the available AIE tiles. This work introduces a Tile-Level Pipeline architecture designed for stencil computation that operates with constant memory bandwidth. This approach achieves linear scalability, where performance scales linearly with the number of AIE tiles, and ensures full utilization of all AIE tiles on the chip. We empirically demonstrate these benefits using AIEs.

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Publication Details

Published
2025-02-26
DOI
https://doi.org/10.1145/3706628.3708822
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
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Tile-Level Pipeline for Linear Scalable Stencil Computation on AMD AI Engines

Miaoxiang Yu, Yanze Zhang, Jillian Cai, Zhenyu Xu et al.
Parallel Computing and Optimization Techniques
article

Tile-Level Pipeline for Linear Scalable Stencil Computation on AMD AI Engines

Miaoxiang Yu, Yanze Zhang, Jillian Cai, Zhenyu Xu, Qing Yang, Tao Wei
article en

Abstract

Stencil computation is an essential method, particularly useful for numerical simulations in areas like acoustics, heat transfer, and electromagnetism. Recent studies have utilized AMD AI Engines (AIEs) for stencil computations by configuring multiple AIE tiles within a Compute Unit to exploit task-level parallelism, achieving notable speedup through concurrent task execution. However, this setup suffers from suboptimal performance due to high memory bandwidth demands, resulting in underutilization of the available AIE tiles. This work introduces a Tile-Level Pipeline architecture designed for stencil computation that operates with constant memory bandwidth. This approach achieves linear scalability, where performance scales linearly with the number of AIE tiles, and ensures full utilization of all AIE tiles on the chip. We empirically demonstrate these benefits using AIEs.

University of Rhode Island (US), Clemson University (US)
Affordable and clean energy
Openalex Percentile: Top 97%
Parallel Computing and Optimization Techniques
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