Implementing New Algorithm with CUDA Kernels - CUDA C++ Class Part 3

Learn to implement new algorithms on the GPU using CUDA kernels in this comprehensive video tutorial from NVIDIA's Modern CUDA C++ Programming Class. Master the fundamentals of CUDA kernel development, starting with basic kernel concepts and progressing through advanced optimization techniques including atomic operations, shared memory utilization, and cooperative algorithms. Work through hands-on exercises covering symmetry operations, histogram implementations, and debugging tools while exploring privatized histograms, thread scope management, and streaming multiprocessor (SM) architecture. Discover how to optimize performance using shared memory, leverage the CUB library for efficient parallel primitives, and implement cooperative histogram algorithms. Practice debugging CUDA code and apply atomic operations to solve race conditions in parallel computing scenarios. Access accompanying slides and Google Colab exercises to run GPU code for free, with step-by-step solutions provided for each programming challenge. Designed for C++ developers seeking to write clean, efficient, and idiomatic GPU code using modern CUDA best practices, whether you're new to CUDA programming or looking to modernize existing GPU applications.