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English(EN) Ariel-ML: Computing Parallelization with Embedded Rust for Neural Networks on Heterogeneous Multi-core Microcontrollers

Ariel-ML工具包支持在多核微控制器上进行基于Rust的并行神经网络推理

一个名为Ariel-ML的新工具包已被开发出来,用于使用嵌入式Rust在多核微控制器上自动化神经网络推理的并行化。该工具包旨在利用各种32位微控制器中存在的异构多核架构的能力,包括Arm Cortex-M、RISC-V和ESP-32系列。基准测试表明,与现有的解决方案相比,Ariel-ML实现了更低的推理延迟,同时保持了与使用C/C++的工具包相当的内存占用。 AI

影响 能够更有效地在低功耗、多核嵌入式系统上部署AI模型。

排序理由 详细介绍用于嵌入式AI的新软件工具包的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Ariel-ML工具包支持在多核微控制器上进行基于Rust的并行神经网络推理

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详细介绍用于嵌入式AI的新软件工具包的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Zhaolan Huang, Kaspar Schleiser, Gyungmin Myung, Emmanuel Baccelli ·

    Ariel-ML:异构多核微控制器上用于神经网络的嵌入式 Rust 计算并行化

    arXiv:2512.09800v2 Announce Type: replace Abstract: Low-power microcontroller (MCU) hardware is currently evolving from single-core architectures to predominantly multi-core architectures. In parallel, new embedded software building blocks are more and more written in Rust, while…