Why do so many AI agent tool calls run on the CPU? Drawing on NVIDIA's CUDA guide and a research paper: GPUs can execute branches, and divergent branches run one after another. In SWE-Agent, doubling ...

本文围绕 Ray 官方文档中的反模式 "Over-parallelizing with too fine-grained tasks harms speedup"，用可复现的基准代码对比"串行 / 过细粒度并行 / 批量并行"三种写法的真实耗时，并结合源码剖析开销来源，给出批大小选择、任务粒度划分等实战建议，帮助你写出真正能跑出加速比而非负优化效果的 Ray 程序。

Yinghan Sun, Aoji Zhu, Xiang Ji, Yamei Li, Jiachi Zhao, Yun Wang, Li Zhang, Huijun Gao, Lidong Yang. In the proposed framework, we develop a fully vectorized simulator with more than 10,000 artificial ...

AI chip startup Tensordyne has taped out its data center inference chip, which the company said will offer an order-of-magnitude improvement in power efficiency compared with leading GPU alternatives.

In this tutorial, we build a complete pgvector playground inside Google Colab and explore how PostgreSQL can work as a powerful vector database for modern AI applications. We start by installing ...

AI systems can appear magical until you’re sitting around waiting for them to answer. Whether it’s a large language model (LLM) in the cloud, an on‑device vision model or a recommendation system, ...

The larger our dataset, the longer it takes to process. While we can wait for the whole process to end, sometimes it takes too much time and needs to meet the business standards. That’s why there are ...

Python is powerful, versatile, and programmer-friendly, but it isn’t the fastest programming language around. Some of Python’s speed limitations are due to its default implementation, CPython, being ...