Balancing GPU workloads on PowerVR hardware
If you’ve been following this series of posts from the beginning you probably know the drill by now. We have a new documentation website, which is packed full of helpful tips and tricks for developers of all knowledge levels. One of our most useful documents, for both new and experienced developers, is our PowerVR Performance Recommendations. This document gives you the knowledge you need to get the most out of your applications running on PowerVR hardware. This post is based on one of these recommendations and is focussed on eliminating performance bottlenecks by balancing different GPU workloads.
Removing performance bottlenecks
Performance bottlenecks are the bane of any graphics developer’s existence. They can be incredibly aggravating and very painful if you’re forced to choose between performance and visual quality. But wait – before you rush to do anything drastic, it’s important to remember that bottlenecks can be caused by a particularly heavy workload on an individual processing element of the GPU. By spreading out that workload across more of your GPU’s capabilities, you can potentially eliminate the bottleneck entirely.
However, before you can figure out how to balance the GPU workload, you have to know how it is distributed in the first place. This is where PowerVR’s powerful profiling and analysis tools come in.
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