Re: Is offloading to GPU a worthwhile feature?

>>> This is an entirely idle pondering kind of question, but I wanted to
>>> ask. I recently discovered that some edge providers are starting to
>>> offer systems with GPU cards in them -- primarily for clients that need
>>> to provide streaming video content, I guess. As someone who needs to run
>>> a distributed network of edge nodes for a fairly popular git server, I
>>> wondered if git could at all benefit from utilizing a GPU card for
>>> something like delta calculations or compression offload, or if benefits
>>> would be negligible.
>> 
>> The problem is that you need to transfer the data from the main memory
>> (host memory) geared towards low-latency thanks to cache hierarchy, to
>> the GPU memory (device memory) geared towards bandwidth and parallel
>> access, and back again.  So to make sense the time for copying data plus
>> the time to perform calculations on GPU (and not all kinds of
>> computations can be speed up on GPU -- you need fine-grained massively
>> data-parallel task) must be less than time to perform calculations on
>> CPU (with multi-threading).
>
> Would something like this be well-suited for tasks like routine fsck,
> repacking and bitmap generation? That's the kind of workloads I was
> imagining it would be most well-suited for.

>> Also you would need to keep non-GPU and GPGPU code in sync.  Some parts
>> of code do not change much; and there also solutions to generate dual
>> code from one source.
>> 
>> Still, it might be good idea,
>
> I'm still totally the wrong person to be implementing this, but I do
> have access to Packet.net's edge systems which carry powerful GPUs for
> projects that might be needing these for video streaming services. It
> seems a shame to have them sitting idle if I can offload some of the
> RAM- and CPU-hungry tasks like repacking to be running there.