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English(EN) torch-sla: Differentiable Sparse Linear Algebra with Adjoint Solvers and Sparse Tensor Parallelism for PyTorch

PyTorch 获得可微分稀疏线性代数库

研究人员开发了 torch-sla,一个开源的 Python 库,旨在为 PyTorch 提供可微分稀疏线性代数功能。该库弥补了 PyTorch 现有功能中的不足,目前仅提供低级内核或仅限 CPU、不可微分的求解器。Torch-sla 支持跨多个后端(包括 CPU 和 GPU 选项)的各种求解器类型的统一 API,并支持分布式执行以增强可扩展性。 AI

影响 通过提供必要的微分稀疏线性代数工具,支持更先进的科学机器学习模型。

排序理由 该集群包含一篇学术论文,详细介绍了一个特定技术领域的新的开源库。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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

PyTorch 获得可微分稀疏线性代数库

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该集群包含一篇学术论文,详细介绍了一个特定技术领域的新的开源库。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Mingyuan Chi, Shizheng Wen ·

    torch-sla: PyTorch 的带伴随求解器和稀疏张量并行的可微分稀疏线性代数

    arXiv:2601.13994v3 Announce Type: replace-cross Abstract: Differentiable sparse linear algebra is foundational for scientific machine learning, yet PyTorch lacks a unified library for it: torch.sparse provides only low-level kernels and a non-differentiable, CPU-only spsolve, and…