Ever since its introduction in CUDA 10, CUDA Graphs has been used in a variety of applications. A graph groups a set of CUDA kernels and other CUDA operations together and executes them with a specified dependency tree. It speeds up the workflow by combining the driver activities associated with CUDA kernel launches and CUDA API calls. It also enforces the dependencies with hardware accelerations��
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