Understanding Communication Patterns in Distributed ML: A Deep Dive into NCCL, MPI, and Gloo
Understand key communication patterns (Broadcast, Scatter/Gather, All-Reduce, All-Gather, All-to-All) and core protocols (NCCL, MPI, Gloo) crucial for efficiently scaling distributed ML workloads, including LLMs, computer vision, and multimodal models.
3 Key Parallel Computing Concepts for Distributed ML
Understand foundational parallel computing concepts such as SIMD, multithreading, and GPU kernels that underpin distributed machine learning. Learn how mastering these fundamentals helps optimize your ML systems before scaling to multi-node setups.
Scaling AI: The Essentials of Distributed Machine Learning
Distributed ML powers today's massive AI models like GPT-4 and Stable Diffusion. This article introduces key concepts in Distributed ML, explains parallel computing clearly, and highlights real-world challenges and strategies.