BitzFlex
Hi!,
I have the Mac Studio and I want to use the GPU on it with EXLA.
I made the project that has config like below.
import Config
config :nx, :default_backend, EXLA.Backend
with iex ,
Nx.tensor [1,2,3,4] ,
it show
[info] TfrtCpuClient created.
#Nx.Tensor<
s64[4]
EXLA.Backend<host:0, 0.1189406505.872022046.161358>
[1, 2, 3, 4]
it seems not use GPU.
And, with below code (to make long Nx calculation) ----
url =
“https://pix4free.org/assets/library/2021-01-12/originals/san_francisco_california_golden_gate_bridge_water.jpg”
%{body: raw_image} = Req.get!(url)
imageNx = StbImage.read_binary!(raw_image)
|> StbImage.to_nx()
|> Nx.reshape({:auto,3})
IO.puts "Started --------"
start_ts =DateTime.utc_now() |> DateTime.to_unix(:second)
KMeans.fit(imageNx,
num_clusters: 10,
num_runs: 10,
max_iterations: 200,
key: Nx.Random.key(42)
)
end_ts =DateTime.utc_now() |> DateTime.to_unix(:second)
IO.puts "DONE -- ellapse : #{end_ts - start_ts}"
It takes about 230 seconds, and the Mac Activity Monitor show 0 GPU usage of beam_smp.
Does the EXLA support Apple Silicon GPU ?
Any suggestion will be appreciated..
Thanks,
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polvalente
We don’t currently support mac GPUs unfortunately.
There’s ongoing work on migrating EXLA to an MLIR-based implementation that will in the future enable support, though.
Torchx is closer to that, altough Pytorch still has a few issues to go on the ways of API coverage for Apple Metal.
polvalente
Ah, there’s something else you should also configure, the default defn compiler!
config :nx, :default_defn_options, compiler: EXLAshould make your code quite a bit faster tooBitzFlex
Thank you so much!
Following your advice, adding the “config :nx, :default_defn_options, compiler: EXLA” setting dramatically reduced the computation time.
It went down from 220 seconds to 13 seconds. That’s really amazing.
Thank you once again.
polvalente
Awesome!