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English(EN) JLIR: A Julia-Native MLIR-Inspired Intermediate Representation with Automatic JACC Kernel Extraction

JLIR 框架将 MLIR 风格的编译带入 Julia

研究人员开发了 JLIR,一个受 MLIR 启发的、原生于 Julia 的中间表示框架。JLIR 旨在将 MLIR 的多级、面向方言的编译优势引入 Julia 生态系统,同时可以作为标准的 Julia 代码使用。该框架通过 Julia 的原生机制支持可扩展的操作和转换通道,允许在确定具体类型之前保留部分类型信息以供转换。JLIR 已应用于为 Julia for Accelerators (JACC) 自动生成内核。 AI

排序理由 学术论文,详细介绍了一种新的编程语言中间表示框架。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.CL 阅读 →

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

JLIR 框架将 MLIR 风格的编译带入 Julia

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学术论文,详细介绍了一种新的编程语言中间表示框架。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Narasinga Rao Miniskar, Seyong Lee, Keita Teranishi, Jeffrey S Vetter ·

    JLIR:一种受 MLIR 启发的 Julia 原生中间表示,支持自动 JACC 内核提取

    arXiv:2609.04585v1 Announce Type: cross Abstract: The Multi-Level Intermediate Representation (MLIR) has made reusable compiler infrastructure practical for domain-specific computation. However, MLIR's strong compile-time type requirements and low-level (C++) extension model can …