Boosting CUDA Efficiency with Essential Techniques for New Developers
Table of Contents
Introduction to CUDA Programming and Performance Optimization
Athena Elafrou, a Developer Technology Engineer at NVIDIA, presents a foundational session aimed at developers new to CUDA programming. The talk covers essential principles for optimizing NVIDIA CUDA performance, focusing on GPU architecture and core optimization techniques. Key topics include SIMT execution, control flow, memory access patterns, GPU occupancy, and bottleneck identification. The session emphasizes memory access optimization techniques to boost memory throughput, improve parallelism through ILP and TLP, and manage atomic operations efficiently. Real-world examples and performance analyses are provided to equip developers with actionable knowledge for improving CUDA development skills and maximizing NVIDIA GPU performance efficiency. The talk is part of a series on core performance optimization techniques, tailored for developers looking to enhance their understanding and proficiency in CUDA programming.
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