Sharing CUDA Resources Through Interoperability with NvSciBuf and NvSciSync – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-03-25T15:22:02Z http://www.open-lab.net/blog/feed/ Rekha Mukund <![CDATA[Sharing CUDA Resources Through Interoperability with NvSciBuf and NvSciSync]]> http://www.open-lab.net/blog/?p=22340 2023-02-13T17:01:23Z 2020-12-10T17:02:38Z There is a growing need among embedded and HPC applications to share resources and control execution for pipelined workflows spanning multiple hardware engines...]]> There is a growing need among embedded and HPC applications to share resources and control execution for pipelined workflows spanning multiple hardware engines...

There is a growing need among embedded and HPC applications to share resources and control execution for pipelined workflows spanning multiple hardware engines and software applications. The following diagram gives an insight into the number of engines that can be supported on NVIDIA-embedded platforms. In addition to GPUs, this includes image processing units like image signal processors��

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