CUDA Graph在多流执行中效果有限，仅能消除CPU开销导致的GPU气泡，无法解决其他流中阻塞内核引起的气泡。若GPU利用率已高，启用CUDA Graph收益甚微，不应过度投入。仅当气泡主要由CPU开销造成时，启用才可能有益，但需验证分析痕迹的准确性。

The engineering team at Stripe recently described how they automated database incident recovery by modeling their global infrastructure as a graph. Using graph search algorithms together with...

How and Why Netflix Built a Real-Time Distributed Graph: Part 3 — Querying the graph with gRPC execution APIAuthors: Nilesh Mishra and Ajit KotiThis is the third entry of a multi-part blog series...

Vercel Labs has introduced Zero, an experimental systems programming language aimed at AI rather than human users. It employs unique features like a specific toolchain contract and structured...

本文介绍CodeQL中用于分析Java程序调用图的类：Callable（可被调用的方法或构造器）和Call（调用点），以及导航谓词getCallee、getCaller和polyCalls。通过示例展示如何编写查询查找未使用的方法，并逐步优化查询，排除库代码、类初始化器、finalize方法、公共方法、默认构造器及测试类，以减少误报。

本文介绍了CodeQL在Java中的调用图分析，用户可以通过Callable和Call类识别未被调用的方法。示例查询展示了如何找到未被其他方法调用的可调用对象，并提供了排除特定方法和构造函数的策略，以减少查询结果。同时，文章提到反射调用和JUnit测试方法的特殊情况，强调了识别未使用方法的复杂性。

电子科技大学的论文《Experience Memory Graph》提出了一种通过图匹配范式改进智能体错误恢复的新方法。该方法在训练阶段将成功与失败轨迹转化为有向图，在测试时一次性检索纠正策略，避免了传统反思循环的低效和高成本。实验结果表明，EMG在ALFWorld和ScienceWorld基准上优于现有方法，提升了准确率和效率，适用于小型语言模型。

本文介绍了Git中的commit-graph和pack bitmap机制及其作用。commit-graph用于加速遍历提交历史，记录提交的拓扑和代数编号；pack bitmap则预计算对象的可达性位图，以优化遍历性能。这两者不改变对象库的语义，删除后功能仍然正常，但可能会变慢。建议在本地仓库进行性能对比实验。

Cassie Shum discusses the architectural evolution of GraphRAG and why data foundations are critical for advanced AI workflows. She explains how traditional vector RAG falls short when addressing...

PostgreSQL 19 Beta has been announced, with general availability expected in September, following the project's yearly major-release cadence. This release introduces native SQL Property Graph...

AWS disclosed that Resilient Network Graphs, a flat network architecture based on quasi-random graph theory, is now the default for most new data center builds. The design replaces fat-tree...

PostgreSQL 19 adds GRAPH_TABLE, letting you query property graphs with Cypher-like pattern matching over your existing relational tables.

By Oleksii Tkachuk, Kartik Sathyanarayanan, Rajiv ShringiIntroductionNetflix has a diverse range of graph use cases, each serving specific business needs with unique functionality and performance...

By Oleksii Tkachuk, Kartik Sathyanarayanan, Rajiv ShringiIntroductionNetflix has a diverse range of graph use cases, each serving specific business needs with unique functionality and performance...

Netflix has developed a graph-based architecture for managing machine learning systems, called the Model Lifecycle Graph. This system maps interconnections between datasets, models, features, and...

Saish Sali, Nipun Kumar, Sura ElamuruguIntroductionAs Netflix has grown, machine learning continues to support our ability to deliver value to members and drive excellence across multiple areas of...

Saish Sali, Nipun Kumar, Sura ElamuruguIntroductionAs Netflix has grown, machine learning continues to support our ability to deliver value to members and drive excellence across multiple areas of...

Mariia Bulycheva discusses the transition from classic deep learning to GNNs for Zalando's landing page. She explains the complexities of converting user logs into heterogeneous graphs, the...