atomic min, max for Float32 and Float64

[ArturPrzybysz]

Is your feature request related to a problem? Please describe.
Not described to a specific problem. I just think that atomic min and max are very common operations and it would be convenient for developers to have it out of the box. Currently only integers are supported.

Describe the solution you'd like
Including atomic min, max for Float32 and Float64 in CUDA.jl interface.

[maleadt]

The low level atomic operations, i.e. those prefixed by atomic_, only provide what the hardware implements. For a wider set of operations, potentially falling back to a slow CAS loop, you can use the CUDA.@atomic macro, which supports min just fine:

julia> function kernel(a)
           CUDA.@atomic a[1] = min(a[1], 1)
           return
       end
kernel (generic function with 1 method)

julia> a = cu([42])
1-element CuArray{Int64, 1, CUDA.Mem.DeviceBuffer}:
 42

julia> @cuda kernel(a)
CUDA.HostKernel for kernel(CuDeviceVector{Int64, 1})

julia> a
1-element CuArray{Int64, 1, CUDA.Mem.DeviceBuffer}:
 1