GPU architecture enables massive parallel processing through thousands of CUDA cores, contrasting with CPU's sequential processing capabilities. CUDA programming provides a platform for developers to harness GPU's parallel power through kernel functions and thread management. The document explores memory management, shared memory optimization, and practical applications in LLM workloads like FlashAttention.

https://www.pyspur.dev/blog/introduction_cuda_programming

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