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Adapt to GPUArrays v11 #237

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Adapt to GPUArrays v11 #237

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1 change: 1 addition & 0 deletions Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -19,4 +19,5 @@ StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
[compat]
LLVM = "9.1"
OpenCL_jll = "2024.5.8"
GPUArrays = "11"
julia = "1.10"
65 changes: 0 additions & 65 deletions src/gpuarrays.jl
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@@ -1,70 +1,5 @@
# GPUArrays.jl interface


#
# Device functionality
#


## execution

struct CLArrayBackend <: AbstractGPUBackend end

struct CLKernelContext <: AbstractKernelContext end

@inline function GPUArrays.launch_heuristic(::CLArrayBackend, f::F, args::Vararg{Any,N};
elements::Int, elements_per_thread::Int) where {F,N}
kernel = @opencl launch=false f(CLKernelContext(), args...)
wg_info = cl.work_group_info(kernel.fun, cl.device())

# XXX: how many groups is a good number? the API doesn't tell us.
# measured on a low-end IGP, 32 blocks seems like a good sweet spot.
# note that this only matters for grid-stride kernels, like broadcast.
return (threads=wg_info.size, blocks=32)
end

function GPUArrays.gpu_call(::CLArrayBackend, f, args, threads::Int, blocks::Int;
name::Union{String,Nothing})
@opencl global_size=blocks*threads local_size=threads name=name f(CLKernelContext(), args...)
end


## on-device

# indexing

GPUArrays.blockidx(ctx::CLKernelContext) = get_group_id(1)
GPUArrays.blockdim(ctx::CLKernelContext) = get_local_size(1)
GPUArrays.threadidx(ctx::CLKernelContext) = get_local_id(1)
GPUArrays.griddim(ctx::CLKernelContext) = get_num_groups(1)

# math

@inline GPUArrays.cos(ctx::CLKernelContext, x) = cos(x)
@inline GPUArrays.sin(ctx::CLKernelContext, x) = sin(x)
@inline GPUArrays.sqrt(ctx::CLKernelContext, x) = sqrt(x)
@inline GPUArrays.log(ctx::CLKernelContext, x) = log(x)

# memory

@inline function GPUArrays.LocalMemory(::CLKernelContext, ::Type{T}, ::Val{dims}, ::Val{id}
) where {T, dims, id}
ptr = SPIRVIntrinsics.emit_localmemory(Val(id), T, Val(prod(dims)))
oneDeviceArray(dims, LLVMPtr{T, onePI.AS.Local}(ptr))
end

# synchronization

@inline GPUArrays.synchronize_threads(::CLKernelContext) = barrier()



#
# Host abstractions
#

GPUArrays.backend(::Type{<:CLArray}) = CLArrayBackend()

function GPUArrays.derive(::Type{T}, a::CLArray, dims::Dims{N}, offset::Int) where {T,N}
ref = copy(a.data)
offset = (a.offset * Base.elsize(a)) ÷ sizeof(T) + offset
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