Parallel computing continues to advance, addressing the demands of high-performance tasks such as deep learning, scientific simulations, and data-intensive computations. A fundamental operation within ...

The main result of this paper shows that the block-based digital medial axis transform can be computed in parallel by a constant number of calls to scan (parallel prefix) operations. This gives time- ...

Learn about common parallel algorithms and patterns in CUDA, such as data parallelism, task parallelism, map, scan, stencil, and reduce. Discover CUDA libraries and best practices.