Template:CUDA ISP for NVIDIA Jetson/Main contents: Difference between revisions

Template:CUDA ISP for NVIDIA Jetson/Main contents (view source)

Revision as of 20:32, 10 March 2023

4 bytes removed , 10 March 2023

→‎Use cases

Lleon

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 CUDA ISP provides an alternative solution to reduce CPU usage by allowing the GPU handle the image processing.
-* '''Application with large percentage of CPU usage'''
+* '''Application with a large percentage of CPU usage'''
 If you ever found yourself overloading the CPU processing capacity, the GPU can handle it via CUDA ISP.
 |-
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 * '''Computers with no ISP built-in'''
-Computers with x86 architecture does not have a built-in ISP. By adding a discrete GPU to the architecture, CUDA ISP can be used as an alternative processor.
+Computers with x86 architecture do not have a built-in ISP. Adding a discrete GPU to the architecture allows CUDA ISP to be used as an alternative processor.
 * '''Artificial intelligence applications'''
-Developing artificial intelligence (AI) applications, such as computer vision, can require intensive computations in which the GPU can help with the processing. It is possible to find CUDA ISP working on a multi-GPU environment, where the ISP is running on a GPU and the AI applications on another one.
+Developing artificial intelligence (AI) applications, such as computer vision, can require intensive computations in which the GPU can help with the processing. It is possible to find CUDA ISP working on a multi-GPU environment, where the ISP runs on a GPU and the AI applications on another one.
 *'''Streaming applications'''
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 * '''Flexibility'''
-CUDA ISP is flexible and extensible. You can add more algorithms to perform ISP tasks. We can team-up in your next project to speed up the ISP.
+CUDA ISP is flexible and extensible. You can add more algorithms to perform ISP tasks. We can team up in your next project to speed up the ISP.
 == Tested Platforms ==