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English(EN) GINGER: Spicing Up Graph-Based Vector Search

Google发布GINGER库，加速基于图的向量搜索

作者 PulseAugur 编辑部 · [1 个来源] ·

Google开发了GINGER，一个用于基于图的近似最近邻搜索（ANNS）的开源C++库。GINGER旨在提高大型、高维嵌入数据集的速度和内存效率。它通过诸如Nested TurboQuant（用于高效导航和重排）和AdaptiveGap压缩（用于邻近图）等创新来实现这一点，与现有库相比，查询吞吐量更快，内存占用更少。 AI

影响 该库可以加速依赖于大型向量数据集中高效相似性搜索的AI应用的开发和部署。

排序理由 发布了一篇详细介绍新的基于图的向量搜索开源库的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.IR (Information Retrieval) 阅读 →

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

Google发布GINGER库，加速基于图的向量搜索

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发布了一篇详细介绍新的基于图的向量搜索开源库的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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Topics
infra, other
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报道来源 [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Vahab Mirrokni ·

    GINGER：为基于图的向量搜索增添风味

    We present \textsc{Ginger}, a state-of-the-art open-source C++ library for graph-based approximate nearest neighbor search (ANNS). We developed \textsc{Ginger} at Google to push the speed and memory efficiency of graph search on large and high-dimensional embedding datasets. \tex…

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