I believe you need to use an initialized device.
See https://github.com/JuliaGPU/CUDArt.jl#gpu-initialization
For example:
devices(dev->true) do devlist
C = CUDArt.CudaArray(Float64, (10,10))
fill!(C, 2.0)
println(to_host(C))
end
On Monday, October 26, 2015 at 2:30:40 PM UTC+1, Matthew Pearce wrote:
>
> I'm not having much luck filling a CUDArt.CudaArray matrix with a value.
>
> julia> C = CUDArt.CudaArray(Float64, (10,10))
> CUDArt.CudaArray{Float64,2}(CUDArt.CudaPtr{Float64}(Ptr{Float64} @
> 0x0000000b034a0e00),(10,10),0)
>
> julia> fill!(C, 2.0)
> ERROR: KeyError: (0,"fill_contiguous",Float64) not found
> [inlined code] from essentials.jl:58
> in getindex at dict.jl:719
> in fill! at /home/mcp50/.julia/v0.5/CUDArt/src/arrays.jl:158
>
> The fill! code works when matrix C is created by copying data to the gpu.
> This suggested to me the problem was one of memory allocation. However,
> I've tried variations on this which haven't worked, such as taking some of
> the source code:
>
> julia> function NewCudaArray(T::Type, dims::Dims)
> n = prod(dims)
> p = CUDArt.malloc(T, n)
> CudaArray{T,length(dims)}(p, dims, device())
> end
> NewCudaArray (generic function with 1 method)
>
> julia> C = NewCudaArray(Float64, (10,10))
> CUDArt.CudaArray{Float64,2}(CUDArt.CudaPtr{Float64}(Ptr{Float64} @
> 0x0000000b034a1200),(10,10),0)
>
> julia> fill!(C, 2.0)
> ERROR: KeyError: (0,"fill_contiguous",Float64) not found
> [inlined code] from essentials.jl:58
> in getindex at dict.jl:719
> in fill! at /home/mcp50/.julia/v0.5/CUDArt/src/arrays.jl:158
>
> Copying things across unnecessarily sounds slow, so thoughts appreciated.
>
