cuda nvcc make __device__ conditional - cuda

Question

I am trying to add a cuda backend to a 20k loc c++ expression template library. So far it is working great, but i am drowned in completely bogus "warning: calling a __host__ function from a __host__ __device__ function is not allowed" warnings.
Most of the code can be summarized like this:
template<class Impl>
struct Wrapper{
Impl impl;
// lots and lots of decorator code
__host__ __device__ void call(){ impl.call();};
};
//Guaranteed to never ever be used on gpu.
struct ImplCPU{
void call();
};
//Guaranteed to never ever be used on cpu.
struct ImplGPU{
__host__ __device__ void call();//Actually only __device__, but needed to shut up the compiler as well
};
Wrapper<ImplCPU> wrapCPU;
Wrapper<ImplGPU> wrapGPU;
In all cases, call() in Wrapper is trivial, while the wrapper itself is a rather complicated beast (only host-functions containing meta-information).
conditional compilation is not an option, both paths are intended to be used side by side.
I am one step short of "--disable-warnings", because honestly the cost of copying and maintaining 10k loc of horrible template magic outweighs the benefits of warnings.
I would be super happy about a way to have call being device or host conditionally based on whether the implementation is for gpu or cpu(because Impl knows what it is for)
Just to show bad it is. A single warning:
/home/user/Remora/include/remora/detail/matrix_expression_classes.hpp(859): warning: calling a __host__ function from a __host__ __device__ function is not allowed
detected during:
instantiation of "remora::matrix_matrix_prod<MatA, MatB>::size_type remora::matrix_matrix_prod<MatA, MatB>::size1() const [with MatA=remora::dense_triangular_proxy<const float, remora::row_major, remora::lower, remora::hip_tag>, MatB=remora::matrix<float, remora::column_major, remora::hip_tag>]"
/home/user/Remora/include/remora/cpu/../assignment.hpp(258): here
instantiation of "MatA &remora::assign(remora::matrix_expression<MatA, Device> &, const remora::matrix_expression<MatB, Device> &) [with MatA=remora::dense_matrix_adaptor<float, remora::row_major, remora::continuous_dense_tag, remora::hip_tag>, MatB=remora::matrix_matrix_prod<remora::dense_triangular_proxy<const float, remora::row_major, remora::lower, remora::hip_tag>, remora::matrix<float, remora::column_major, remora::hip_tag>>, Device=remora::hip_tag]"
/home/user/Remora/include/remora/cpu/../assignment.hpp(646): here
instantiation of "remora::noalias_proxy<C>::closure_type &remora::noalias_proxy<C>::operator=(const E &) [with C=remora::matrix<float, remora::row_major, remora::hip_tag>, E=remora::matrix_matrix_prod<remora::dense_triangular_proxy<const float, remora::row_major, remora::lower, remora::hip_tag>, remora::matrix<float, remora::column_major, remora::hip_tag>>]"
/home/user/Remora/Test/hip_triangular_prod.cpp(325): here
instantiation of "void Remora_hip_triangular_prod::triangular_prod_matrix_matrix_test(Orientation) [with Orientation=remora::row_major]"
/home/user/Remora/Test/hip_triangular_prod.cpp(527): here

Answer 1

This problem is actually quite unfortunate deficiency in CUDA language extensions.
Standard approach to deal with these warnings (in Thrust and similar templated CUDA libs) is to disable the warning for the function/method that causes it by using #pragma hd_warning_disable, or in newer CUDA (9.0 or newer) #pragma nv_exec_check_disable.
So in your case it would be:
template<class Impl>
struct Wrapper{
Impl impl;
// lots and lots of decorator code
#pragma nv_exec_check_disable
__host__ __device__ void call(){ impl.call();};
};
Similar question already asked

Answer 2

I'm sorry, but you're abusing the language and misleading readers. It is not true that your wrapper classes has a __host__ __device__ method; what you mean to say is that it has either a __host__ method or a __device__ method. You should treat the warning as more an error.
So, you can't just use the sample template instantiation for ImplCPU and ImplGPU; but - you could do something like this?
template<typename Impl> struct Wrapper;
template<> struct Wrapper<ImplGPU> {
ImplGPU impl;
__device__ void call(){ impl.call();};
}
template<> struct Wrapper<ImplCPU> {
ImplGPU impl;
__host__ void call(){ impl.call();};
}
or if you want to be more pedantic, it could be:
enum implementation_device { CPU, GPU };
template<implementation_device ImplementationDevice> Wrapper;
template<> Wrapper<CPU> {
__host__ void call();
}
template<> Wrapper<GPU> {
__device__ void call();
}
Having said that - you were expecting to use a single Wrapper class, and here I am telling you that you can't do that. I suspect your question presents an X-Y problem, and you should really consider the entire approach of using that wrapper. Perhaps you need to have the code which uses it templated different for CPU or GPU. Perhaps you need type erasure somewhere. But this won't do.

Answer 3

The solution i came up in the mean-time with far far less code duplication is to replace call by a functor level:
template<class Impl, class Device>
struct WrapperImpl;
template<class Impl>
struct WrapperImpl<Impl, CPU>{
typename Impl::Functor f;
__host__ operator()(){ f();}
};
//identical to CPU up to __device__
template<class Impl>
struct WrapperImpl<Impl, GPU>{
typename Impl::Functor f;
__device__ operator()(){ f();}
};
template<class Impl>
struct Wrapper{
typedef WrapperImpl<Impl, typename Impl::Device> Functor;
Impl impl;
// lots and lots of decorator code that i now do not need to duplicate
Functor call_functor()const{
return Functor{impl.call_functor();};
}
};
//repeat for around 20 classes
Wrapper<ImplCPU> wrapCPU;
wrapCPU.call_functor()();