Compile cuda code for CPU

14
votes

I'm study cuda 5.5 but i don't have any Nvidia GPU. In old version of nvcc have a flag --multicore to compile cuda code for CPU. In the new version of nvcc, what's is the option?? I'm working on Linux.

3
cudanvidianvcc
Thank you for clarifying "Linux". You really need a GPU. But the next best thing is Ocelot: try it. I'm unfamiliar with "--multicore", and I didn't see it anywhere on the NVCC page, so I can't help you there. But I think your best bet is 1) a real GPU, or 2) an emulator like CUDA-Waste or Ocelot. IMHO... – FoggyDay

3 Answers

6
votes

CUDA toolkits since at least CUDA 4.0 have not supported an ability to run cuda code without a GPU.

If you simply want to compile code, refer to this question.

If you want to run CUDA codes compiled with CUDA 5.5, you will need a CUDA capable GPU.

If you're willing to use older CUDA toolkits, you could install one of the various emulators, such as this one.

Or you could install a very old (e.g. ~ CUDA 3.0) cuda toolkit that had the ability to run CUDA codes on the CPU.

2
votes

Ideally, you'd be able to get access to a CUDA-compatible NVidia GPU.

But short of that, here's an emulator that might help:

If you have a Linux box, you can also try Ocelot:

0
votes

In current versions of CUDA, programs are debugged directly while they are running on the GPU. This is far superior to older versions of CUDA, which used an emulator for debugging. The debugging facilities are also much more powerful in current versions of CUDA.

So, if wish to write any CUDA code, a CUDA capable GPU card will give you immediate return on investment when you need to debug.

You can pick up an older used card for very little. Examine the features of each of the compute capabilities to determine how far back you are willing to go.

There are also some sites online that will let you test out CUDA code. NVIDIA has the CUDA test drive program. The Intro to Parallel Programming course at Udacity includes an online CUDA compiler for the coding assignments.