NVIDIA vs AMD: GPGPU performance

Question

I\'d like to hear from people with experience of coding for both. Myself, I only have experience with NVIDIA.

NVIDIA CUDA seems to be a lot more popular than the competi

Answer 1

Having spent some time with OpenCL for GCN cards after a few years of CUDA for Fermi and Kepler, I still prefer CUDA as a programming language and would choose AMD hardware with CUDA if I had an option.

Main differences of NVIDIA and AMD (OpenCL):

For AMD:

• Even with Maxwell, NVidia still has longer command latencies and complex algorithms are likely to be 10 faster on AMD(assuming same theoretical Tflops) after easy optimizations for both. The gap was up to 60% for Kepler VS GCN. It's harder to optimize complex kernels for NVidia in this sense.

• Cheap cards.

• OpenCL is open standard with other vendors available.

For Nvidia:

• Has the Tesla line of hardware that's suitable for reliable high server loads.

• New Maxwell is way more power efficient.

• Compiler and tools are way more advanced. AMD still can't get to implement maxregcout parameter, so you can easily control occupancy on various hardware and their compiler has a lot of random ideas of what is an optimal code that change with every version, so you may need to revisit old code every half a year because it suddenly became 40% slower.

At this point if GPGPU is your goal, CUDA is the only choice, since opencL with AMD is not ready for server farm and it's significantly harder to write efficient code for AMD due to the fact that the compiler always seems to be "in beta".