Hadoop Tutorials
Simplified approach to Hadoop ecosystem: architecture, HDFS, MapReduce, YARN, security, and practical examples. Includes Google Cloud integration for hands-on experience.
Microservices Made Easy with Dapr - Ask the Expert
Explore Dapr's distributed application runtime for simplified microservices development. Learn installation, building blocks, language support, and future roadmap. Ideal for developers seeking efficient cloud-native solutions.
Scaling ML Workloads with PyTorch
Explore techniques for scaling machine learning workloads with PyTorch, including distributed training, memory optimization, and profiling tools for large-scale model development.
Easy and Featureful Parallelism with Dagger.jl - JuliaCon 2021
Explore advanced parallelism in Julia with Dagger.jl, offering GPU execution, fault tolerance, and efficient resource utilization. Learn through practical examples and discover its powerful features.
Multi-threading in Julia with PARTR - JuliaCon 2019
Explore multi-threading in Julia with PARTR, covering old and new features, future developments, and practical examples. Includes performance comparisons and Q&A on threading models and implementation details.
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.
Scaling AI at Autodesk with Ray and Metaflow
Explore a 15-minute conference talk from Ray Summit 2024 where Thomas Gale and Peter Meltzer from Autodesk, alongside Savin Goyal from Outerbounds, demonstrate how Autodesk leverages Ray and Metaflow for large-scale 3D generative AI operations. Learn abo…
Scaling Ray to 10,000 NPUs - Huawei's Hyperscale Journey
Dive into Huawei's groundbreaking journey of integrating 10,000 Ascend NPUs with Ray, exploring technical innovations, observability solutions, and strategies for hyperscale AI infrastructure deployment.
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.
How the AI Institute is Revolutionizing Robotics Machine Learning Training
Discover how Boston Dynamics AI Institute revolutionizes robotics ML with an innovative training platform that integrates multimodal data, extensive simulations, and scalable infrastructure using Ray.
Dynamic Scheduling for Large Language Model Serving
Discover how Llumnix optimizes large language model serving through dynamic request scheduling, cross-instance defragmentation, and innovative KV cache migration techniques for improved performance.
Scaling Ray Train to 10,000 Kubernetes Nodes on GKE
Discover how to scale distributed machine learning workloads across 10,000 Kubernetes nodes using Ray Train and GKE, featuring architectural insights and practical solutions for massive AI model training.
How Roblox Scaled Machine Learning by Leveraging Ray for Efficient Batch Inference
Discover how Roblox leverages Ray to scale machine learning infrastructure, focusing on multimodal language models integration, batch inference optimization, and practical implementation strategies.
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.
Building Intelligent AI Infrastructure with ORI - Dynamic Query Routing and Model Management
Discover how ORI dynamically routes AI queries to optimal language models, featuring chain atomic queries, benchmark matching, and ethical frameworks integrated with Ray Serve and vLLM for high-speed inference.
Bootstrapping AI with Web3 Tools - A Technical Overview
Explore the intersection of AI and Web3 technologies through expert insights on leveraging blockchain-based tools for artificial intelligence development and implementation.
DORA - Distributed Oracle Agreement with Simple Majority
Explore the DORA protocol's innovative approach to distributed oracle networks, focusing on agreement distance and simple majority consensus for enhanced blockchain data reliability and scalability.
How AI and Web3 Technologies Intersect - Applications and Opportunities
Discover how AI and Web3 technologies complement each other, exploring practical applications and integration possibilities for next-generation decentralized systems.
Optimization for Reducing Compute Cost of SparkSQL in ByteDance
Discover key optimization techniques for SparkSQL implementation at ByteDance, focusing on compute cost reduction strategies and performance enhancement methods.
Introduction to Reinforcement Learning - Distributed RL Systems - Lecture 9
强化学习分布式系统概述：探讨系统架构、参数更新方法、并行化策略，以及从DQN到AlphaStar的案例研究，深入分析分布式RL系统的发展和实现。
Building Smart Farms with Edge Computing Systems Using Kubernetes
Implementación de sistemas de computación de borde con Kubernetes para crear granjas inteligentes, optimizando la agricultura mediante tecnología avanzada.