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Is there a stand-alone C/C++ library for Deep Learning?
This question is based on my previous question:
Why does cudaMallocHost need to be called as a host function?
I just read the answer, but I still have some questions:
1) Why cudaMallocHost needs to be called as a host function?
2) Why we can’t start with kernel launching with host function?
If it has something to do with GPU programming, is there a stand-alone library that people used?
AFAIK, cudaMallocHost is called from the kernel, and cudaMallocHost is much slower than the cudaMalloc call.
CUDA provides an abstraction layer for device and host code: the application layer. It contains both the kernel calls and the host calls and makes it easier to code. Thus, the application layer doesn’t care where the device objects or memory is, and all the application logic is abstracted away and placed within the kernel.
The kernel calls are low-level and run in “parallel”. This means that if a kernel call is used, there will always be only one of those calls running on a GPU, whereas you can have up to thousands of host threads in one single host call. Additionally, the rest of the application logic is executed on the host.
You should try to understand the concept of CUDA programming first: there are lots of good tutorials and books about that on the Internet, such as CUDA by Example, Developing Programs for CUDA, CUDA Programming Guide. You can find the “developers guide” to the language on the NVIDIA website.
Of course, here are some examples to demonstrate how to interact with the CUDA API:
Simple CUDA example with the CUDA Toolkit API
CUDA_example with the C API
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