[REFACTOR] cuda.parallel: Don't require passing input/output arrays to `reduce_into` and similar algorithms

Currently, `reduce_into` usage looks like:

```python
# construct the reduer:
reducer = cudax.reduce_into(d_in, d_out, op, h_init)

# allocate temp storage
temp_storage_bytes = reducer.reduce_into(None, d_in, d_out, op, h_init)
d_temp = cuda.device_array(temp_storage_bytes)
result = reducer.reduce_into(d_temp, d_in, d_out, op, h_init)
```

Note that the initial construction of `reducer` shouldn't strictly need the arguments `d_in`, `d_out`, `h_init`. In fact, passing any placeholder arrays of the same data type will serve the same purpose.

We should refactor such that only the required information is passed into the constructor.

## Additional Context

https://github.com/NVIDIA/cccl/pull/3001/#discussion_r1866733390