Because it’s very easy for the CPU-GPU interface to become the bottleneck, as state-of-the-art resolutions require shoving around literal gigabytes per second to get a standard framerate (seriously, make a rough estimate how much data your 300 ppi phone or tablet is pumping over the bus to the screen, it’s chilling), and the less you do it the better. (See a HN comment about Audacity slowing down in recent years [as screen resolution increases]: https://news.ycombinator.com/item?id=26498649.) Getting a not-quite-SIMD processing unit specializing in throughput above all else to do your heavy lifting is a bonus.

I suspect the underlying question is “why a supposedly-3D-optimized GPU for a 2D task?” While it’s true that modern GPUs are 3D-optimized, that’s AFAICS because the decade-long lull of 1MP-or-so screens and ever-more-powerful desktop CPUs ca. 2000–2010(?) made CPU 2D rendering mostly “fast enough” so as the programmable 3D pipeline emerged the 2D accelerator from the workstation era died out, leaving perhaps only an optimized blit behind.

Compute- and power-constrained handheld devices and higher-resolution screens made developers (software and hardware) wake up in a hurry, but now, a redraw-everything-every frame, 3D-adapted graphics facility is what you have, so a redraw-everything-every-frame, 3D-adapted graphics facility is what you shall use. The much more parallel and power-efficient processor and wider bus is still easily worth it, if you spend the effort to wrangle it.

(It’s interesting to think what 2D-optimized hardware would look like. Do people know how to do analytic or even just AGG-quality 2D rasterization on a GPU? Or anything but simple oversampling.)

Not a graphics programmer, treat with a measure of skepticism.