JavaScript Test Automation Complete Tutorial - Selenium WebDriver With JavaScript
Comprehensive tutorial on JavaScript test automation with Selenium WebDriver, covering setup, assertions, parallel testing, reporting, cloud execution, headless testing, and parameterization.
K-Means Clustering - Theory, Algorithm, Implementation, Scaling
Comprehensive exploration of k-means clustering, covering theory, implementation, and scaling techniques. Includes hands-on demonstrations and practical applications using cloud computing resources.
Managing Uncertainty in Water Resource Modelling
Explore uncertainty analysis in water resource modeling, covering parameter selection, handling external uncertainties, model adaptation, and incorporating observations for improved predictions.
Deep Learning for Fundamental Sciences Using High-Performance Computing
Exploring deep learning applications in fundamental sciences using high-performance computing to uncover universe secrets and improve discovery sensitivity.
Distributed TensorFlow Training - Google I/O 2018
Learn to scale TensorFlow training across multiple GPUs and machines efficiently. Explore distribution strategies, performance optimization techniques, and practical implementation using Google Cloud.
Evolving Ray Core - Scalability, Reliability, and Compiled Graphs
Discover the latest advancements in Ray Core's architecture, including streaming generators, weekly releases, and the new Compiled Graphs backend for enhanced performance in accelerator-driven computing environments.
The Evolution of Multi-GPU Inference in vLLM
Dive into advanced parallelism strategies for distributed LLM inference, exploring tensor, pipeline, and expert parallelism techniques through vLLM's architecture and optimization approaches.
Exascale Cloud Computing - A Foggy Tale of Networks, AI, Containers, and Ultra Ethernet
Dive into advanced cloud computing concepts, exploring datacenter networks, AI acceleration services, and Ultra Ethernet through real-world performance analyses and industry developments.
SeismicWaves.jl - Wave Simulation Package for Full Waveform Inversion on Multi-xPUs
Discover how SeismicWaves.jl enables efficient wave equation solving through finite-difference methods, offering high-performance computing capabilities for both small-scale prototyping and large-scale simulations.
Improving the Life-Cycle of Tensor Algorithm Development with ITensors
Explore advanced tensor algorithm development in Julia, focusing on generic programming strategies for efficient computation across CPU, GPU, and QPU architectures using the ITensors framework.
Seamless Transition from Single-core Python to Julia Multi-GPU
Discover how to transform single-core Python code into scalable Julia applications for GPU supercomputers, with focus on automatic verification and parallel computing optimization.
爬虫基础教学 Python Scraping 教程
从网页结构到高效爬虫库，全面学习Python网络爬虫 技术。掌握BeautifulSoup、Requests、多进程、异步加载、Selenium和Scrapy等工具，实现高效数据采集。
CUDA Explained Five Minutes
Comprehensive overview of CUDA architecture, parallel computing, and programming model, covering key concepts and applications in an accessible Hindi-language format.
The Road to Innovation for AI Chips in China
Explore China's AI chip innovation landscape, including market growth, startups, academic advancements, and emerging technologies like reconfigurable computing and neuromorphic chips.
Computação Quântica - A Nova Fronteira da Tecnologia
Exploração da computação quântica, suas aplicações e impactos futuros nos negócios e na vida cotidiana, apresentada de forma acessível por um especialista na área.
Um Bug Mudou A Minha Vida - Como um Erro de Computador Transformou uma Carreira
Jovem hacker inspira adolescentes a perseguir sonhos, compartilhando sua jornada desde invadir a NASA até criar empresas de tecnologia, abordando riscos e oportunidades no mundo digital.
RDMA Programming Using Rust Async
使用Rust异步框架实现RDMA编程,构建Rust友好的RDMA绑定,提供自动内存管理和异步I/O,大大简化RDMA应用开发,促进Rust社区利用RDMA构建高性能应用。
ML Training Acceleration with Heterogeneous Resources in ByteDance
探讨如何利用字节跳动的异构计算资源加速机器学习模型训练,包括GPU共享机制、NUMA亲和性资源分配和RDMA网络通信等技术。
Practice of Building AI Training Clusters Based on Kubernetes and RoCEv2
探讨基于Kubernetes和RoCEv2构建AI训练集群的实践,包括网络集成、资源调度和任务优化等方面的挑战与解决方案,助力提升AI训练效率。
Run AI Workloads and Microservices on Kubernetes with Volcano
使用Volcano在Kubernetes上高效运行AI工作负载和微服务,提供作业调度、资源管理等功能,支持大数据、人工智能等高性能计算场景,已被50多个用户采用。
Boost ML on Heterogeneous AI Accelerators with Ray on Kubernetes
探讨如何在Kubernetes上利用Ray和图编译器自动提升异构AI加速器的机器学习性能,无需修改用户代码,实现透明的后端加速。