Support for CUDA

[albertomercurio]

Hello,

I tried to use CuArrays to fit some data. The model(x, p) function works great if p is a CPU Array. However the fitting procedure doesn't work.

I could be a great extension, increasing the performances.

[pkofod]

Could you supply an example?

[albertomercurio]

using LsqFit

@. model(x, p) = p[1]*exp(-x*p[2])

xdata = collect(range(0, stop=10, length=20))
ydata = model(xdata, [1.0 2.0]) + 0.01*randn(length(xdata))
p0 = [0.5, 0.5]

fit = curve_fit(model, xdata, ydata, p0)

and for the CUDA GPU

using CUDA

xdata_gpu = cu(xdata)
ydata_gpu = cu(ydata)

fit = curve_fit(model, xdata_gpu, ydata_gpu, p0)

but fails

GPU compilation of kernel #broadcast_kernel#17(CUDA.CuKernelContext, CuDeviceMatrix{Float64, 1}, Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{2}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}, typeof(*), Tuple{Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1}, Nothing, typeof(*), Tuple{Float64, Base.Broadcast.Extruded{CuDeviceVector{Float64, 1}, Tuple{Bool}, Tuple{Int64}}}}, Base.Broadcast.Extruded{LinearAlgebra.Adjoint{Float64, Vector{Float64}}, Tuple{Bool, Bool}, Tuple{Int64, Int64}}}}, Int64) failed
KernelError: passing and using non-bitstype argument

Argument 4 to your kernel function is of type Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{2}, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}}, typeof(*), Tuple{Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1}, Nothing, typeof(*), Tuple{Float64, Base.Broadcast.Extruded{CuDeviceVector{Float64, 1}, Tuple{Bool}, Tuple{Int64}}}}, Base.Broadcast.Extruded{LinearAlgebra.Adjoint{Float64, Vector{Float64}}, Tuple{Bool, Bool}, Tuple{Int64, Int64}}}}, which is not isbits:
  .args is of type Tuple{Base.Broadcast.Broadcasted{CUDA.CuArrayStyle{1}, Nothing, typeof(*), Tuple{Float64, Base.Broadcast.Extruded{CuDeviceVector{Float64, 1}, Tuple{Bool}, Tuple{Int64}}}}, Base.Broadcast.Extruded{LinearAlgebra.Adjoint{Float64, Vector{Float64}}, Tuple{Bool, Bool}, Tuple{Int64, Int64}}} which is not isbits.
    .2 is of type Base.Broadcast.Extruded{LinearAlgebra.Adjoint{Float64, Vector{Float64}}, Tuple{Bool, Bool}, Tuple{Int64, Int64}} which is not isbits.
      .x is of type LinearAlgebra.Adjoint{Float64, Vector{Float64}} which is not isbits.
        .parent is of type Vector{Float64} which is not isbits.

[pkofod]

Okay, I can have a look.

[albertomercurio]

Hi @pkofod

I created a pull request that makes this package compatible with CUDA arrays.