In many CUDA kernels, the conventional pattern for thread iteration looks like
this:
```cuda
for (int i = thread_idx; i < numel; i += num_threads)
out[i] = 0;
```
However, in TileLang we currently have to write:
```python
for i in T.serial(0, T.ceildiv(numel - thread_idx, num_threads)):
j = thread_idx + i * num_threads
out[j] = -1
```
This is not only cumbersome — since it requires manually computing the range
and performing index transformations — but it also introduces additional
register usage and reduces index computation efficiency.
Introducing a `step` attribute to `ForNode` could simplify such patterns and
improve both readability and performance but I guess there's a lot of
challenges about this part.
---
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