把素数搜索变成分布式实验，看看你的CPU能算出多大的质数！
Article URL: https://github.com/max-russo-com/max-prime-challenge Comments URL: https://news.ycombinator.com/item?id=49331879 Points: 1 # Comments: 1
芯片电源签核周期从几周缩至几天，芯晓科技自研分布式方案展现硬科技突破潜力。
一枚先进制程芯片从设计、验证，到流片、制造，需要经过上百个环节。其中电源签核（Sign-off）是设计流程最后的、也最重要的一环，相当于建造一栋大楼时对全楼供电系统进行竣工验收。 具体来说，电源核签是通过对电源网络的上亿个节点进行整体分析，测试供电网络的功耗、电压降与电迁移等表现，从而决定芯片能否顺…
分布式架构下高效近似轮廓系数的新方法，适合大规模聚类评估场景。
arXiv:2607.01993v1 Announce Type: cross Abstract: The silhouette is one of the most widely used measures to assess the quality of a $k$-clustering of …
12条实用技巧，教你设计AI驱动的高性能计算工作流，涵盖分布式计算关键要点。
arXiv:2606.07491v1 Announce Type: cross Abstract: High-performance computing (HPC) clusters remain the backbone of large-scale scientific computation,…
本地运行AI不仅省电，更是一场分布式的绿色计算革命，值得关注。
Data Centers: Dream Factories, Carbon Factories Behind every cloud query lies a colossal infrastructure. Millions of servers, spread across giant data…
揭秘千亿级AI工厂背后的高速网络架构，直击数据中心互联核心技术
arXiv:2605.21187v1 Announce Type: cross Abstract: As distributed model training scales to span hundreds of thousands of GPUs, scale-out networks face …
OpenAI官方分享训练大型神经网络的核心技术与工程挑战，GPU集群同步计算的关键方法。
Large neural networks are at the core of many recent advances in AI, but training them is a difficult engineering and research challenge which require…
新运行时系统TrainMover能弹性应对机器学习训练中断，比传统检查点恢复更高效可靠
arXiv:2412.12636v3 Announce Type: replace-cross Abstract: Large-scale ML training jobs are frequently interrupted by hardware and software anomalies, …
二阶优化方法加速LLM训练的瓶颈被Asteria运行时系统破解，大幅提升训练效率。
arXiv:2605.16184v1 Announce Type: cross Abstract: Second-order methods offer an attractive path toward more sample-efficient LLM training, but their p…