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.