Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Add usage example. #29

Open
wants to merge 2 commits into
base: master
Choose a base branch
from
Open

Add usage example. #29

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
b9f8063
Add usage example.
RomeoV Dec 13, 2023
da3bd1b
Fix: Matrix -> CuMatrix.
RomeoV Dec 13, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
17 changes: 16 additions & 1 deletion README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,22 @@

**GPU integrations for Dagger.jl**

DaggerGPU.jl makes use of the `Dagger.Processor` infrastructure to dispatch Dagger kernels to NVIDIA, AMD, and Apple GPUs, via CUDA.jl, AMDGPU.jl, and Metal.jl respectively. Usage is simple: `add` or `dev` DaggerGPU.jl and CUDA.jl/AMDGPU.jl/Metal.jl appropriately, load it with `using DaggerGPU`, and add `DaggerGPU.CuArrayDeviceProc`/`DaggerGPU.ROCArrayProc`/`DaggerGPU.MtlArrayDeviceProc` to your scheduler or thunk options (see Dagger.jl documentation for details on how to do this).
DaggerGPU.jl makes use of the `Dagger.Processor` infrastructure to dispatch Dagger kernels to NVIDIA, AMD, and Apple GPUs, via CUDA.jl, AMDGPU.jl, and Metal.jl respectively. Usage is simple: `add` or `dev` DaggerGPU.jl and CUDA.jl/AMDGPU.jl/Metal.jl appropriately, load it with `using DaggerGPU`, and add the appropriate GPU scope to the Dagger scope options, for example

``` julia
using CUDA, Dagger, DaggerGPU
sc = Dagger.scope(cuda_gpu=1)

# two large matrices
A = rand(1000, 1000); B = rand(1000, 1000)
# move them to gpu and multiply there
A_gpu = Dagger.@spawn scope=sc CUDA.CuMatrix(A); B_gpu = Dagger.@spawn scope=sc CUDA.CuMatrix(B)
C_gpu = Dagger.@spawn scope=sc A_gpu*B_gpu
# move back to cpu to use there.
C = Dagger.@spawn scope=sc Matrix(C_gpu)
```

and similarly for `rocm_gpu` and `metal_gpu`.

DaggerGPU.jl is still experimental, but we welcome GPU-owning users to try it out and report back on any issues or sharp edges that they encounter. When filing an issue about DaggerGPU.jl, please provide:
- The complete error message and backtrace
Expand Down