AMDGPU.jl

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AMDGPU.jlProgramming AMD GPUs with Julia

Getting Started
API
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AMDGPU.jl

Install ​

Simply add the AMDGPU.jl package to your Julia environment:

julia
using Pkg
Pkg.add("AMDGPU")

Requirements ​

  • Julia 1.10+

  • MI300X requires Julia 1.12+

  • 64-bit Linux or Windows

  • ROCm 6.0+

Required software ​

LinuxWindows
ROCmROCm
-AMD Software: Adrenalin Edition

On Windows AMD Software

Adrenalin Edition contains HIP library itself, while ROCm provides support for other functionality.

On Fedora ROCm packages

Although not included in the AMD's list of supported Linux distributions, Fedora provides its own ROCM packages.

sudo dnf install rocminfo rccl-devel rocblas-devel rocfft-devel rocsparse-devel rocsolver-devel rocrand-devel roctracer-devel miopen-devel rocm-hip-devel

However, the libraries are not installed in the usual location (under /opt/rocm) so for AMDGPU to find them you must set an environment variable.

export ROCM_PATH=/usr/lib64

Test ​

To ensure that everything works, you can run the test suite:

julia
using AMDGPU
using Pkg
Pkg.test("AMDGPU")

Example ​

Element-wise addition via high-level interface & low-level kernel:

julia
using AMDGPU

function vadd!(c, a, b)
   i = workitemIdx().x + (workgroupIdx().x - 1) * workgroupDim().x
   if i ≤ length(a)
       c[i] = a[i] + b[i]
   end
   return
end

a = AMDGPU.ones(Int, 1024)
b = AMDGPU.ones(Int, 1024)
c = AMDGPU.zeros(Int, 1024)

groupsize = 256
gridsize = cld(length(c), groupsize)
@roc groupsize=groupsize gridsize=gridsize vadd!(c, a, b)

@assert (a .+ b) ≈ c

Questions and Contributions ​

Usage questions can be posted on the Julia Discourse forum under the GPU domain and/or in the #gpu channel of the Julia Slack.

Contributions are very welcome, as are feature requests and suggestions. Please open an issue if you encounter any problems.

Acknowledgment ​

AMDGPU.jl would not have been possible without the work by Tim Besard and contributors to CUDA.jl and LLVM.jl.

License ​

AMDGPU.jl is licensed under the MIT License.