KernelAbstractions.jl
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JuliaGPU
Heterogeneous programming in Julia
See https://github.com/LuxDL/LuxLib.jl/pull/136 for some background context. The main motivation for me is to avoid code duplication between CPU and GPU versions. However, if you take a look at the benchmark...
```julia julia> @time_imports using KernelAbstractions 9.8 ms UnsafeAtomics 6.4 ms Atomix ┌ 0.8 ms SuiteSparse_jll.__init__() 116.4 ms SuiteSparse_jll 96.92% compilation time ┌ 8.2 ms SparseArrays.CHOLMOD.__init__() 95.65% compilation time 156.1 ms...
Hi! First of all congratulations on the fantastic package :) Sometimes, seeing how the speed scales as a function of the number of threads is helpful. My understanding is that...
In https://github.com/JuliaGPU/KernelAbstractions.jl/pull/364 I added `adapt(backend, x)` as a natural extension for adapt, instead of having to use something like `adapt(default_array_type(backend), x)` which we don't currently have. This was inspired by...
For the recently added Enzyme support via EnzymeRules we will need to extend CI and support to more backends - [ ] AMDGPU -- should work - [ ] oneAPI...
[printall.log](https://github.com/user-attachments/files/16180105/printall.log) Getting this error ``` ERROR: BoundsError: attempt to access 0-element Vector{LLVM.LLVMType} at index [1] Stacktrace: [1] getindex @ ./essentials.jl:13 [inlined] [2] call!(builder::LLVM.IRBuilder, rt::GPUCompiler.Runtime.RuntimeMethodInstance, args::Vector{LLVM.ConstantExpr}) @ GPUCompiler /disk/mschanen/julia_depot/packages/GPUCompiler/Y4hSX/src/rtlib.jl:39 [3] emit_exception!(builder::LLVM.IRBuilder,...
Hello, I've encountered the error described in the title and would like to report it. To reproduce, please run following code with `julia --check-bonds=no` ``` using CUDA using KernelAbstractions N...
As requested by @vchuravy, this is a copy of my slack question: Hello, I'm running into an errors with KernelAbstractions.jl, atomic operations using Atomix.jl and complex numbers. Is it possible...
Running this code using the current versions of Enzyme, KA, and CUDA.jl: ``` using KernelAbstractions using CUDA using Enzyme function advanceTimeLevels!(field; backend=CUDABackend()) nthreads = 64 kernel2d! = advance_2d_array(backend, nthreads) kernel2d!(field,...
