Interface

gpu_call(kernel::Function, arg0, args...; kwargs...)

Executes kernel on the device that backs arg (see backend), passing along any arguments args. Additionally, the kernel will be passed the kernel execution context (see [AbstractKernelContext]), so its signature should be (ctx::AbstractKernelContext, arg0, args...).

The keyword arguments kwargs are not passed to the function, but are interpreted on the host to influence how the kernel is executed. The following keyword arguments are supported:

• target::AbstractArray: specify which array object to use for determining execution properties (defaults to the first argument arg0).
• elements::Int: how many elements will be processed by this kernel. In most circumstances, this will correspond to the total number of threads that needs to be launched, unless the kernel supports a variable number of elements to process per iteration. Defaults to the length of arg0 if no other keyword arguments that influence the launch configuration are specified.
• threads::Int and blocks::Int: configure exactly how many threads and blocks are launched. This cannot be used in combination with the elements argument.
• name::String: inform the back end about the name of the kernel to be executed. This can be used to emit better diagnostics, and is useful with anonymous kernels.

AbstractDeviceArray{T, N} <: DenseArray{T, N}

Supertype for N-dimensional GPU arrays (or array-like types) with elements of type T. Instances of this type are expected to live on the device, see AbstractGPUArray for host-side objects.

Creates a block local array pointer with T being the element type and N the length. Both T and N need to be static! C is a counter for approriately get the correct Local mem id in CUDAnative. This is an internal method which needs to be overloaded by the GPU Array backends

 synchronize_threads(ctx::AbstractKernelContext)

in CUDA terms __synchronize in OpenCL terms: barrier(CLK_LOCAL_MEM_FENCE)