By John Gruber
Build internal tools in minutes with Retool, where visual programming meets the power of real code.
Andy Somerfield, lead for (the great) Affinity Photo app:
In Photo, an ideal GPU would do three different things well: 1.) High compute performance 2.) Fast on-chip bandwidth 3.) Fast transfer on and off the GPU.
Way back in 2009, no GPU did all three things well - but we thought that eventually the industry would get there, so we took a risk and designed the entire architecture based on that assumption. Things didn’t go entirely to plan.
We shipped Photo in 2015 - six years after the design phase - without GPU compute support :(
A GPU which did all the things we needed simply didn’t exist. We wondered if we had backed the wrong horse. Happily, a short while later it did exist - but it was in an iPad 😬!
Fast-forward a few tweets in the thread to today:
The #M1Max is the fastest GPU we have ever measured in the @affinitybyserif Photo benchmark. It outperforms the W6900X — a $6000, 300W desktop part — because it has immense compute performance, immense on-chip bandwidth and immediate transfer of data on and off the GPU (UMA).
A laptop GPU outperforming a $6,000 300-watt (300 watts!) desktop GPU. Bananas. But here I am, typing this sentence on that laptop.
The entire Apple silicon story — along with the Affinity Photo team’s prescient bet — feels like a perfect illustration of the Bill Gates axiom: “We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten. Don’t let yourself be lulled into inaction.”
★ Tuesday, 26 October 2021