Re: WebWorker and Device

FYI: I have the simplest multi-canvas demo here
<https://webgpu-multi-swapchain.glitch.me/> that works for me on Canary.

On Sun, Apr 19, 2020 at 12:31 AM Kai Ninomiya <kainino@google.com> wrote:

> crbug.com/new
>
> Component: Blink>WebGPU if you can set it, but please just email me the
> bug link once filed. Thanks!
>
> On Sat, Apr 18, 2020, 3:12 PM Rob Conde <jaha84@gmail.com> wrote:
>
>> Thanks for that clarification. Would it be useful for me to add an issue
>> for the overhead? If so, which bug tracker would be appropriate.
>>
>> Rob
>>
>> On Apr 18, 2020, at 5:51 PM, Kai Ninomiya <kainino@google.com> wrote:
>>
>> 
>> Yes, the spec will support single device with many workers and many
>> canvases. The GPUDevice and other objects will be cloneable.
>>
>> But we do not have any support in Chrome yet for multiple workers, and
>> for that matter I'm not sure if multi-canvas is tested, so we should test
>> to make sure we don't break it.
>>
>> I'm surprised the per-device overhead is so high; I don't think it should
>> be. I guess we have something else to investigate there.
>>
>> On Sat, Apr 18, 2020, 2:31 PM Robert Conde <jaha84@gmail.com> wrote:
>>
>>> Using chrome canary, I've been playing with using multiple webgpu
>>> canvases in the same page. If I make a separate get adapter/device call for
>>> each canvas it has a very high overhead (at least on Windows the gpu
>>> process was 1.7 GB for 20 canvases each drawing a single triangle). Using a
>>> single shared device across all canvases works and greatly alleviates the
>>> problem.It also made initialization of each canvas significantly faster.
>>>
>>> As of now offscreen canvas support for webgpu is not implemented in
>>> chrome (https://bugs.chromium.org/p/chromium/issues/detail?id=1064109).
>>> However, I was setting up a demo just to confirm this was still broken and
>>> to have a test to periodically try. I found that I would get a "GPUDevice
>>> object could not be cloned." error trying to pass the GPUDevice to the
>>> worker. The GPUDevice can't be passed to transfer because it's not
>>> transferable (but this seemed like the wrong thing to do anyhow).
>>>
>>> So mainly what I'm trying to understand is whether sharing a single
>>> device instance with multiple workers is meant to be supported somehow from
>>> a webgpu perspective.
>>>
>>> Thanks,
>>> Rob Conde
>>>
>>