Added example project files

example*

!example*.cpp

!example*.cu

include config.mk

SOURCES := $(wildcard *.cpp)

TARGETS := $(SOURCES:%.cpp=%)

CUDA_SOURCES := $(wildcard *.cu)

CUDA_TARGETS := $(CUDA_SOURCES:%.cu=%)

## targets definitions follow

.PHONY: all host cuda

all: host cuda

host: $(TARGETS)

cuda: $(CUDA_TARGETS)

.PHONY: clean

clean:

	rm -f *.d *.o *.cuo $(TARGETS) $(CUDA_TARGETS)

$(TARGETS): % : %.o

	$(CXX) $(LDFLAGS) -o $@ $< $(LDLIBS)

# use .cuo instead of .cu.o to avoid problems with the implicit rules: https://stackoverflow.com/q/62967939

# (and use the host compiler for linking CUDA, nvcc does not understand that .cuo is an object file)

$(CUDA_TARGETS): % : %.cuo

	$(CXX) $(CUDA_LDFLAGS) -o $@ $< $(CUDA_LDLIBS)

$(SOURCES:%.cpp=%.o): %.o: %.cpp

	$(CXX) $(CPPFLAGS) $(CXXFLAGS) -c -o $@ $<

$(CUDA_SOURCES:%.cu=%.cuo): %.cuo : %.cu

	$(CUDA_CXX) $(CUDA_CPPFLAGS) $(CUDA_CXXFLAGS) -c -o $@ $<

# Example Project

Basic example how to use TNL in a C++/CUDA project with Makefile

See the [TNL documentation](https://mmg-gitlab.fjfi.cvut.cz/doc/tnl/) for details.

# configure the include path(s) according to your TNL installation

TNL_INCLUDE_DIRS := -I ~/.local/include

WITH_OPENMP := yes

WITH_DEBUG := no

# If TNL is installed on your system, the CUDA architecture can be detected

# automatically by tnl-cuda-arch. This is done if CUDA_ARCH is set to "auto".

# Otherwise, CUDA_ARCH has to be set manually to the desired CUDA architecture

# number, e.g. 60, 61, etc.

CUDA_ARCH := auto

# compilers

CXX := g++

CUDA_CXX := nvcc

# host compiler flags

CXXFLAGS := -std=c++14 $(TNL_INCLUDE_DIRS)

ifeq ($(WITH_DEBUG),yes)

    CXXFLAGS += -O0 -g

else

    CXXFLAGS += -O3 -DNDEBUG

endif

# CUDA compiler flags

CUDA_CXXFLAGS := -std=c++14 --expt-relaxed-constexpr --expt-extended-lambda $(TNL_INCLUDE_DIRS)

CUDA_CXXFLAGS += -DHAVE_CUDA

ifeq ($(CUDA_ARCH),auto)

    CUDA_CXXFLAGS += $(shell tnl-cuda-arch)

else

    CUDA_CXXFLAGS += -gencode arch=compute_$(CUDA_ARCH),code=sm_$(CUDA_ARCH)

endif

# determine path to the CUDA toolkit installation

# (autodetection is attempted, set it manually if it fails)

CUDA_PATH ?= $(abspath $(dir $(shell command -v nvcc))/..)

#$(info Detected CUDA_PATH: $(CUDA_PATH))

# flags for linking CUDA with the host compiler

CUDA_LDFLAGS := -L $(CUDA_PATH)/lib64

CUDA_LDLIBS := -lcudart -ldl -lrt

# enable OpenMP

ifeq ($(WITH_OPENMP),yes)

    CXXFLAGS += -fopenmp -DHAVE_OPENMP

    LDLIBS += -lgomp

    CUDA_CXXFLAGS += -Xcompiler -fopenmp -DHAVE_OPENMP

    CUDA_LDLIBS += -lgomp

endif

#include <iostream>

#include <TNL/Containers/Array.h>

int main( int argc, char* argv[] )

{

    TNL::Containers::Array< int, TNL::Devices::Cuda > device_array{ 1, 2, 3 };

    std::cout << "device_array = " << device_array << std::endl;

    return EXIT_SUCCESS;

}