CUDA Programming for NVIDIA H100s – Comprehensive Course
TL;DR
This comprehensive 24-hour course teaches advanced CUDA programming for NVIDIA H100 Hopper GPUs, covering asynchronous execution models, Tensor Memory Accelerator operations, WGMMA pipelines, and multi-GPU scaling strategies necessary for training trillion-parameter AI models.
🎯 Prerequisites & Architecture Fundamentals 3 insights
Solid C++ and CUDA foundations required
You must understand C++ syntax, CUDA thread hierarchies, and shuffle operations before attempting Hopper's asynchronous programming model.
Matrix tiling knowledge is mandatory
Understanding how matrices are tiled and multiplied forms the essential foundation for WGMMA operations and memory layout optimizations.
H100 introduces asynchronous execution paradigm
The architecture represents a significant shift from synchronous models, requiring new mental models for warp-group level computation and memory management.
⚡ Async Data Movement & Memory 3 insights
Tensor Memory Accelerator handles bulk transfers
TMA uses tensor map descriptors to execute asynchronous global-to-shared memory copies without consuming SM execution resources.
cp.async.bulk instruction powers data movement
This PTX instruction enables structured and unstructured bulk copies with features like L2 cache hinting and multicast capabilities unique to Hopper.
M-barriers synchronize compute and memory
Hardware barrier primitives manage the massive speed gap between fast tensor cores and relatively slow memory accesses.
🧮 Compute Optimization & WGMMA 3 insights
WGMMA operates at warpgroup granularity
Warpgroup Matrix Multiply Accumulate instructions replace warp-level operations, requiring careful register management and descriptor-based matrix fetching.
FP8 precision requires specific memory layouts
Hopper's FP8 implementation demands K-major layouts and specific packing strategies when accumulating in FP32.
Sparse operations support 2:4 structured sparsity
WGMMA can operate on structurally sparse tensors to effectively double computational throughput for compatible matrices.
🚀 Kernel Design & Multi-GPU Scaling 3 insights
Persistent scheduling maximizes tensor core utilization
Modern kernel design uses warp specialization, circular buffering, and persistent warps to eliminate idle cycles and maintain near-100% occupancy.
Production code analysis includes CUTLASS and fast.cu
The course examines SM90 pipeline implementations and a from-scratch kernel achieving 107% of cuBLAS performance.
Multi-GPU scaling covers NCCL and parallelism strategies
Training trillion-parameter models requires understanding NCCL primitives, NVLink topologies, and data/model/pipeline parallelism techniques.
Bottom Line
Master H100 programming by developing strong mental models of asynchronous warpgroup execution and persistent pipelining to achieve near-peak tensor core performance for AI workloads.
More from freeCodeCamp.org
View all
TypeScript in React - Full Tutorial
This tutorial demonstrates how to migrate an existing React application to TypeScript by refactoring JavaScript files into TypeScript, implementing type-safe state management with generics, and creating reusable type definitions for functions and components.
AI Agents For Beginners – OpenClaw Case Study
This beginner course teaches AI agent development by progressing from LLM fundamentals to building a multi-agent system (Zippy, Savvy, Meshy, and Cody), culminating in a security-focused case study of OpenClaw to understand production-ready agent architecture.
Mastering JavaScript Dates and Times – Fundamentals to Advanced Techniques
This tutorial demystifies JavaScript date handling by explaining that time is relative rather than absolute, establishing epoch time (January 1, 1970 UTC) as the universal reference point, and teaching developers to store timestamps in UTC while displaying them in local time zones to avoid production bugs across global users.
Command Line Basics for Beginners - Full Course
This beginner course teaches essential command line skills through a hands-on file organization project, covering core terminal commands for navigation and demonstrating why CLI workflows outperform graphical interfaces for development tasks.