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KernelAbstractions.jl Alternatives
Similar projects and alternatives to KernelAbstractions.jl
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ROCm
Discontinued AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
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GPUCompiler.jl
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StaticCompiler.jl
Compiles Julia code to a standalone library (experimental)
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WorkOS
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futhark
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KernelAbstractions.jl reviews and mentions
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Why is AMD leaving ML to nVidia?
For myself, I use Julia to write my own software (that is run on AMD supercomputer) on Fedora system, using 6800XT. For my experience, everything worked nicely. To install you need to install rocm-opencl package with dnf, AMD Julia package (AMDGPU.jl), add yourself to video group and you are good to go. Also, Julia's KernelAbstractions.jl is a good to have, when writing portable code.
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Generic GPU Kernels
>Higher level abstractions
like these?
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Cuda.jl v3.3: union types, debug info, graph APIs
For kernel programming, https://github.com/JuliaGPU/KernelAbstractions.jl (shortened to KA) is what the JuliaGPU team has been developing as a unified programming interface for GPUs of any flavor. It's not significantly different from the (basically identical) interfaces exposed by CUDA.jl and AMDGPU.jl, so it's easy to transition to. I think the event system in KA is also far superior to CUDA's native synchronization system, since it allows one to easily express graphs of dependencies between kernels and data transfers.
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A note from our sponsor - SaaSHub
www.saashub.com | 29 Mar 2024
Stats
JuliaGPU/KernelAbstractions.jl is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of KernelAbstractions.jl is Julia.
Popular Comparisons
- KernelAbstractions.jl VS GPUCompiler.jl
- KernelAbstractions.jl VS ROCm
- KernelAbstractions.jl VS StaticCompiler.jl
- KernelAbstractions.jl VS AMDGPU.jl
- KernelAbstractions.jl VS oneAPI.jl
- KernelAbstractions.jl VS Agents.jl
- KernelAbstractions.jl VS FoldsCUDA.jl
- KernelAbstractions.jl VS Halide
- KernelAbstractions.jl VS futhark
- KernelAbstractions.jl VS CUDA.jl