The function used to perform custom reduction in a single
work-item (leader of the work-group sequentially).

It now does so cooperatively few iterations, and
processes remaining non-reduced elements sequentially
in the leading work-item.

The custom_reduce_over_group got sped up about a factor of 3x.

The following now shows timing of the reduction kernel

```
unitrace -d -v -i 20 python -c "import dpctl.tensor as dpt; dpt.min(dpt.ones(10**7, dtype=dpt.float32)).sycl_queue.wait()"
```

or par (less that 10%) slower than the int32 kernel, which uses
built-in sycl::reduce_over_group:

```
unitrace -d -v -i 20 python -c "import dpctl.tensor as dpt; dpt.min(dpt.ones(10**7, dtype=dpt.int32)).sycl_queue.wait()"
```

Doing so exactly recovers the behavior of sub_group::load<vec_sz>,
sub_group::store<vec_sz> and eliminates warnings with 2025.1 and SYCLOS.

With this change, enable use of group_load, group_store for DPC++
compiler with `__SYCL_MAJOR_VERSION >= 8u` which includes
oneAPI DPC++ 2025.0.x compiler and SYCLOS bundle.

Factor out bounds as constexpr values, reused between power-of-2
branch and not-power-of-two branch.

Lowered lower bounds from 32 to 8 based on pefrormance testing
on PVC and Iris Xe.