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davisking
Choose backend (GPU/CPU)
So I couldn't find a way to do this in the documentation but I was wondering if there was a way to force dlib to use the CPU if it's built with CUDA enabled? I ask because I'm making a multithreaded application with dlib and only a maximum of 2 threads at a time can use CUDA (because of limitations of the GPU itself). So I'd like to in a thread get dlib to use the GPU in the thread if <2 threads are using the GPU and otherwise fallback to using the CPU.
Also a slightly related question how would dlib cope with a machine with multiple GPUs installed all for compute purposes?
There is no way to switch at runtime. However you build it is the mode in which it will run. To assign things to different GPUs you use the normal cudaSetDevice() method provided by the CUDA runtime.
On Wed, Jul 31, 2019 at 5:05 PM xd009642 [email protected] wrote:
So I couldn't find a way to do this in the documentation but I was wondering if there was a way to force dlib to use the CPU if it's built with CUDA enabled? I ask because I'm making a multithreaded application with dlib and only a maximum of 2 threads at a time can use CUDA (because of limitations of the GPU itself). So I'd like to in a thread get dlib to use the GPU in the thread if <2 threads are using the GPU and otherwise fallback to using the CPU.
Also a slightly related question how would dlib cope with a machine with multiple GPUs installed all for compute purposes?
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Would there be any interest in adding the ability to run something on CPU if built with GPU support? Just because being able to handle this in a single binary would be preferential to building two different binaries linked to two different builds of dlib and coordinating between the two.
Cuda set device is super useful for the second question though cheers! Just saw on docs that it sets the device for the host thread 😊
Sure, such an option would be cool. So a PR that set that up would be great. It would probably best be accomplished via an API similar to cudaSetDevice(). That is, calling some global function to set CPU or GPU, for the current thread.
On Thu, Aug 1, 2019 at 6:38 PM xd009642 [email protected] wrote:
Would there be any interest in adding the ability to run something on CPU if built with GPU support? Just because being able to handle this in a single binary would be preferential to building two different binaries linked to two different builds of dlib and coordinating between the two.
Cuda set device is super useful for the second question though cheers! Just saw on docs that it sets the device for the host thread 😊
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Is there a chance to reopen this? Maybe @xd009642 made some progress? I am in a situation where I use dlib in GPU mode for inferencing, but depending on the training set, need to switch to CPU as GPU memory runs out.
Continuing on a closed thread @davisking unless you think this warrants a new issue.
I took at quick look at the code, it looks like CPU code is compiled out when DLIB_USE_CUDA is used so its not a simple matter of setting a runtime flag. Supporting switching to CPU when GPU is enabled would be a non trivial effort that would involve keeping both code bases compiled in. Is that right or am I going down the wrong path?
I didn't make any progress aside from looking at the code, unfortunately real-life interfered and I lost the need for this functionality at work. My approach though would have been to keep both code-bases compiling in as well as provide an option to keep the old behaviour (just in case any users had a requirement on the old behaviour for binary size etc).
I could potentially have another look at this over the Christmas holidays but I won't realistically get a chance before December 20th so you can always give it a shot if you wish
I don't think it's a big deal to support this. The change is basically just to replace a bunch of:
#ifdef DLIB_USE_CUDA
do_this();
#else
do_that();
#endif
statements with something like:
if (dlib::use_cuda())
do_this();
else
do_that();
Where dlib::use_cuda() simply returns a thread local bool. The state of the bool needs to be initialized based on the DLIB_USE_CUDA macro, and a few variable declarations that are conditionally created based on DLIB_USE_CUDA need to be updated. But other than that it doesn't seem like there is anything else to do.
I don't think there needs to be any option to keep the old behavior where one path is compiled out.
I don't think there needs to be any option to keep the old behavior where one path is compiled out.
In my opinion, it would be really nice if we could still build CPU-only versions that have no CUDA dependencies whatsoever (during compiling, linking, or runtime execution).
Oh yeah, I didn’t mean cuda would become required. The options would be cpu or cpu and gpu. No gpu only option.