#Cuda emulator windows nvcc drivers#

Returns in count the number of devices with compute capability greater or equal to 1.0 that are available forД®xecution. You have to read the docs carefully, though, as there are many quirks that donвЂ™t make a lot of intuituve sense (like: why does cudaGetDeviceCount return 1 when there are 0 devices on the system!) 4.4.2.3 cudaError_t cudaGetDeviceCount (int count) IвЂ™ve tested it on windows, linux, and mac w/o problems. No NVIDIA driver needs to be installed for this to work.

OK, let me quote the docs first and point out that all cudaGetDeviceCount and cudaGetDeviceProperties are available in the cudart library (which you can package with your application in binary form if you want). Yes, but with the same restrictions as my answer for (2). cpp code can link with CUBLAS libraries without the CUDA installed and then the program (associated with the necessary libraries in the same folder) can run on both mathines with and without the GPU card, right? So you can have code like this: int n_gpus = myGetNumerGPUs() But if your application contains both code for the CPU and GPU and you donвЂ™t call the GPU code, then yes it should be OK to run on a machine without a CUDA capable GPU, as long as the necessary libraries are also present. You canвЂ™t run GPU code on the CPU without using some form of GPU emulator. cu code built with CUDA can run on the machine without GPU card, but the machine have installed the CUDA drivers, right? Yes if you want to run GPU code, you have to have a suitable GPU with drivers.

#Cuda emulator windows nvcc drivers#

If want to speed up by the GPU card, the program built with CUDA or linked with CUBLAS libraries should run on the machines with GPU card and with the CUDA drivers installed, right?.