[FEA]: cccl.c and cuda.parallel should support indirect_iterator_t which can be advance on both host and device to support streaming algorithms

[oleksandr-pavlyk]

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Area

cuda.parallel (Python)

Is your feature request related to a problem? Please describe.

To attain optimal performance kernels for some algorithms must use 32-bit types to store problem size arguments.

Supporting these algorithms for problem sizes in excess of INT_MAX can be done with streaming approach with streaming logic encoded in algorithm's dispatcher. Dispatcher needs to increment iterators on the host.

This is presently not supported by cccl.c.parallel, since indirect_arg_t does not implement increment operator.

Since indirect_arg_t is used to represent cccl_value_t, cccl_operation_t and cccl_iterator_t, and incrementing only makes sense for iterators, a dedicated type indirect_iterator_t must be introduced, which may implement the operator+=.

If the entirety of iterator state is user-defined, cuda.parallel must provide host function pointer to increment iterator's state by compiling advance function for the host.

If we define the state of a struct that contains size_t linear_id in addition to user-defined state, we could get rid of user-defined advance function altogether, but would need to provide access to linear_id to the dereference function.

Approached need to be prototyped and compared.

Describe the solution you'd like

The solution should unblock #3764

Additional context

#3764 (comment)