Hi Nick,

I'm not sure why you believe gem5-vega should be in /usr/local/bin? It's
been a few months since I last looked at this codespace, but looking at the
instructions here:
https://github.com/gem5bootcamp/gem5-bootcamp-env/blob/51590ae00b0e451c9b6a8854addbb94128ab4cac/materials/developing-gem5-models/11-gpu/README.md#to-run-square-in-gem5-static-register-allocator,
they do not seem to assume /usr/local/bin.  Instead, they are setting up
the volume for docker for other folders.  Have you tried this command?  Of
course, it's possible I'm wrong though about /usr/local/bin -- but Bobby or
Jason would have to answer that.

Setting that aside, it looks like the instructions you have done are
basically bypassing the prebuilt gem5-vega and building it yourself -- this
is ultimately fine, and what my students do in my research group, but of
course takes a bit longer.

What is the issue with the stats file exactly?  I guess you wrote your own
CPU version of square and that version is not behaving as expected?  I am
not an expert at the CPU part of gem5, but I'd need more information about
how you disabled the CPU part to understand or try to look into this.
Likewise, what stats are you looking at for the CPU?

Thanks,
Matt

On Sun, Mar 2, 2025 at 2:54 PM Beser, Nicholas D. via gem5-users <
gem5-users@gem5.org> wrote:

> Based on the discussion, It seems that docker can’t find the gem5-vega
> that is in the /usr/local/bin. I noticed that the instructions also had us
> building the VEGA_X86/gem5.opt binary with the following command:
>
>                           I.               docker run --volume
> $(pwd):$(pwd) -w $(pwd) ghcr.io/gem5/gcn-gpu:v24-0 scons
> build/VEGA_X86/gem5.opt -j# (# is the number of cores on your X86 system)
>
> I build VEGA_X86 in codespace. The following command afterwards was able
> to run the GPU square binary:
>
>  docker run --volume $(pwd):$(pwd) -w $(pwd) ghcr.io/gem5/gcn-gpu:v24-0
> gem5/build/VEGA_X86/gem5.opt gem5/configs/example/apu_se.py -n 3 -c
> gem5-resources/src/gpu/square/bin/square
>
> The program exsecuted correctly and create a stats.txt file. I have sent
> this instruction to my class so they could proceed with the experiments
> using the GPU.
>
> I do have a question about the results in the stats.txt file. We noticed
> that the program computed the square operation using the GPU, and then
> compared the result using a CPU only code. When one of my students disabled
> the CPU only code, he did not see a drop in the cpu instructions that would
> have corresponded to that loop. I have them looking at the stats.txt file
> for indications about what resources the GPU had used to perform the
> operation.
>
>
>
> Nick
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