Dynamic Parallelism in CUDA is supported via an extension to the CUDA programming model that enables a CUDA kernel to cr
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been provided to support debugging CUDA code. cuda-gdb is supported on 32-
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Apr 24, 2007 ... ii. CUDA Programming Guide Version 0.8.2 ... CUDA: A New Architecture for
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Aug 27, 2009 - NVIDIA OpenCL Programming Guide Version 2.3 ... CUDA's Scalable Programming Model . ..... and Application Programming Interfaces. 1.3.
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Aug 27, 2009 - 1BOpenCL on the CUDA Architecture. 12. NVIDIA OpenCL Programming Guide Version 2.3. A kernel is executed over an NDRange by a grid ...
CUDA programming on NVIDIA GPUs. Mike Giles [email protected].
Oxford University Mathematical Institute. Oxford-Man Institute for Quantitative ...
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which to operate. Additional parallelism can be exposed to the GPU's hardware schedulers and load balancers dynamically,
DYNAMIC PARALLELISM IN CUDA
Dynamic Parallelism in CUDA is supported via an extension to the CUDA programming model that enables a CUDA kernel to create and synchronize new nested work. Basically, a child CUDA Kernel can be called from within a parent CUDA kernel and then optionally synchronize on the completion of that child CUDA Kernel. The parent CUDA kernel can consume the output produced from the child CUDA Kernel, all without CPU involvement. Example: __global__ ChildKernel(void* data){ //Operate on data } __global__ ParentKernel(void *data){ ChildKernel(data); } // In Host Code ParentKernel
