31 lines
1.3 KiB
Markdown
31 lines
1.3 KiB
Markdown
JuliaStream.jl
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==============
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This is an implementation of BabelStream in Julia which contains the following variants:
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* `PlainStream.jl` - Single threaded `for`
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* `ThreadedStream.jl` - Threaded implementation with `Threads.@threads` macros
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* `DistributedStream.jl` - Process based parallelism with `@distributed` macros
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* `CUDAStream.jl` - Direct port of BabelStream's native CUDA implementation using [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl)
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* `AMDGPUStream.jl` - Direct port of BabelStream's native HIP implementation using [AMDGPU.jl](https://github.com/JuliaGPU/AMDGPU.jl)
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### Build & Run
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Prerequisites
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* Julia 1.6+
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With Julia on path, run the benchmark with:
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```shell
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> cd JuliaStream.jl
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> julia --project -e 'import Pkg; Pkg.instantiate()' # only required on first run
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> julia --project src/<IMPL>Stream.jl
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```
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**Important:**
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* Julia is 1-indexed, so N > 1 in `--device N`
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* Thread count for `ThreadedStream` must be set via the `JULIA_NUM_THREADS` environment variable (e.g `export JULIA_NUM_THREADS=$(nproc)`) otherwise it defaults to 1
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* You must *prepend* the number of processes needed for `DistributedStream`, e.g `julia -p$(nproc) --project src/DistributedStream.jl`
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* Certain implementations such as CUDA and AMDGPU will do hardware detection at runtime and may download and/or compile further software packages for the platform.
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