NVIDIA 24-Way GPU Comparison With Many OpenCL, CUDA Workloads

[piotrj3]

I would say from pespective of such productivity results, 2xxx serie is not anyhow failure, RTX 2060 is faster then GTX 1080. If you add new encoder/decoder stuff, it was success. It just wasn't success in performance/$ in games without DLSS.

[rene]

But, … nobody really into OpenSource uses Nvidia anyway, ... :-/

[oleid]

I was wondering, since there is lots of CUDA code around, did anybody of you try to port that to ROCm via the HIP compiler? AFAIK it was used for tensorflow and the performance is not bad. Quite often, the OpenCL code paths are not really good. Porting CUDA code could help, if this was "easy".

[gsedej]

Michael, can you include also radeon via ROCm? OpenCL started working for Blender for navi and polaris. Polaris also woks in tensorflow.

[Michael]

percent results would be better..
(good job)

You can click on the OpenBenchmarking.org link, then hit the "normalize results" checkbox. You can also use 'highlight result' options if wanting to normalize against a particular GPU. And other options on OB to slice and dice the data however you want.

[Niejaki]

percent results would be better..
(good job)

[phoronix]

Phoronix: NVIDIA 24-Way GPU Comparison With Many OpenCL, CUDA Workloads

As part of re-testing all hardware prior to major GPU/driver launches, here is a look at the latest NVIDIA OpenCL/CUDA performance on Linux -- complementing the recent Blender 2.90 benchmarks and the latest NVIDIA vs. AMD Linux gaming performance. In still waiting to find out when we will get any NVIDIA Ampere hardware for Linux testing, I have been having some benchmarking fun and extended this to a 24-way graphics card comparison back to Maxwell in looking at not only the raw GPU compute performance but also the performance-per-Watt / power consumption and GPU thermal values.

http://www.phoronix.com/vr.php?view=29492