On 04/08/18 09:59, Jakub Narebski wrote:
>> 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.

Konstantin Ryabitsev
Director, IT Infrastructure Security
The Linux Foundation

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