Needed strong CPU to max occupancy?


As I know if we want to get the full power of top GPU we need a strong CPU. For example the GTX 1080 won’t shows its power with an Intel Corei3 CPU. I’m not sure if this theory is true only to Games and Graphics. Do you know that this can state with GPGPU processing?
For example the mentioned GTX 1080 with Core i3 will work only half speed than Corei7 top cpu + GTX 1080.

For which particular use case? There are GPU-accelerated applications that need little CPU performance, because pretty much the entire workload runs on the GPU, and there is only a small amount of communication needed with the CPU. Some molecular dynamics applications fall into this category, to give a concrete example.

Looking at the totality of GPU-accelerated applications (thousands by now, I think), one observes that while many get excellent acceleration from the use of GPUs in the parallel portion of the workload, they still contain a certain, sometimes significant, serial portion. As GPUs get faster much quicker than CPUs, that serial portion becomes more and more of a bottleneck for the overall application (-> Amdahl’s Law).

Therefore I usually recommend to CUDA programmers and users the use of CPUs with very high single-thread performance (specifically, a non-boost CPU frequency > 3.4 GHz) to address the serial portion of hybrid CPU+GPU codes, while going easy on the core count (4 or 6 cores with hyperthreading) for cost reasons.

There are other aspects, such as CPU/GPU communication which can be impacted by the number of available PCIe lanes provided by the CPU, but this is a less common issue.

Note that “occupancy” is a crude measure of GPU utilization and has nothing to do with the CPU (at least not in any way I can think off right now). It is a function of the GPU architecture and resource utilization of the code running on the GPU.