WebGPU is now available on Android

It should work on slightly older or lower end Exynos chips, which have ARM Mali GPUs. Their switch to AMD RDNA was a fairly recent thing, and so far it has only been integrated into their flagship-tier parts.

What will be curious about WebGPU getting wider Android deployment is if it results in reducing the effect of variation in the drivers, which very much remain a headache. For example, WebGL type API implementations have had a somewhat flexible idea about data sizes and layout which due to the nature of WebGPU are much less acceptable there. One of the big wins of Vulkan has been that it has levelled the playing field somewhat and poor drivers have less of an impact.

I think a lot of people will be disappointed by what proportion of devices currently in the wild actually successfully make this jump because it is under appreciated the extent to which shortcuts have been taken. I look forward to the day I never have to think about the Mali GLSL compiler ever again.

> Timestamp queries allow WebGPU applications to measure precisely (down to the nanosecond) how much time their GPU commands take to execute compute and render passes

> ...

> Due to timing attack concerns, timestamp queries are quantized with a resolution of 100 microseconds, which provides a good compromise between precision and security.

I don't have a particular need of nanosecond granularity timestamps for WebGPU- there are other parts of the web stack where I could really use better time measurement- but I understand the security concern and it's far better to be safe than sorry.

But they quote two wildly different granularities in the same article, within a paragraph of each other...

I'm not sure I understand you.

Can you expand your comment somewhat?

It should enable much more performant (and battery friendly) 3D content on the web. WebGL has a level of synchronization in the main render loop of the browser that is just not the right way to do it, and WebGPU fixes that.

Additionally it is more suited to GPU based compute, which can be used to accelerate neural network inferencing, though not quite as well as dedicated NN accelerators which are fairly common these days.

I would tend to agree that the business case for these things is not as strong as many would like though, and things have a distinct habit of ceasing to be interesting the moment they are widely achievable.