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Learn about cost semantics and static resource analysis techniques for CUDA programming in this 31-minute conference talk that explores methods for managing parallelism and analyzing computational resources in GPU computing environments, covering theoretical foundations and practical approaches to understanding the performance characteristics and resource requirements of CUDA programs through static analysis techniques.
Syllabus
Cost semantics and static resource analysis for CUDA
Taught by
Simons Institute