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GTC ON-DEMAND

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Abstract:
Dynamic parallelism enables a CUDA kernel to create and synchronize new nested work by launching child kernels from the GPU. Such a nested parallelism programming model maps directly to many real-world programming patterns like adaptive grids or tree-traversal based computations. We'll systematically analyze the performance characteristics of dynamic parallelism by means of real-world application case studies and suggest programming guidelines to get the best performance out of the dynamic parallelism feature. (This talk will be held in collaboration with Thejaswi Rao.)
Dynamic parallelism enables a CUDA kernel to create and synchronize new nested work by launching child kernels from the GPU. Such a nested parallelism programming model maps directly to many real-world programming patterns like adaptive grids or tree-traversal based computations. We'll systematically analyze the performance characteristics of dynamic parallelism by means of real-world application case studies and suggest programming guidelines to get the best performance out of the dynamic parallelism feature. (This talk will be held in collaboration with Thejaswi Rao.)  Back
 
Topics:
Performance Optimization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6807
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