Metal Without Magic: When GPU Helps — and When It Hurts

Metal is often perceived as a universal way to accelerate any bottleneck by offloading work to the GPU. In practice, however, many teams see minimal gains or even performance regressions when introducing Metal into their applications.

In this talk, we’ll explore when using Metal is truly justified, which architectural and measurement mistakes most commonly lead to performance degradation, and how to properly evaluate GPU acceleration results.

We’ll focus on performance methodology and success criteria rather than shader implementation details. Using an image-processing example from single filters to a multi-pass GPU pipeline, we’ll examine how CPU and GPU behavior differs, why the GPU only begins to win under certain pipeline structures, and how to decide whether Metal is worth the added complexity.

This talk is aimed at iOS developers who view Metal as an optimization tool and want a clear, engineering-driven framework for deciding when it accelerates and when it simply complicates the system without delivering real benefits.