You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Is this a new feature, an improvement, or a change to existing functionality?
Improvement
How would you describe the priority of this feature request
Medium
Please provide a clear description of problem you would like to solve.
There are dependencies between st_distance kernels, as shown in the following diagram:
The current implementation of st_distance kernels are siloed and lackes reusing overlapping logics. A refactor should happen to facilitate these dependencies.
Second, several implementation in kernels are not load balanced if the input is skewed. This can lead to unwanted performance degradation. As experimented in #1011, it is possible to create a perfectly load balanced kernel for any input geometries. It should be adopted for other distance API too.
Describe any alternatives you have considered
No response
Additional context
No response
The content you are editing has changed. Please copy your edits and refresh the page.
Originally, #1061 is considered part of this milestone issue. However, #1061 is mainly about optimization on existing distance kernel performance, while this issue requests architecture wise improvement. I decided that they are unrelated issues. Thus removing 1061 from the list above.
Since all underlying issue for this milestone is closed, closing this milestone.
Is this a new feature, an improvement, or a change to existing functionality?
Improvement
How would you describe the priority of this feature request
Medium
Please provide a clear description of problem you would like to solve.
There are dependencies between st_distance kernels, as shown in the following diagram:
The current implementation of st_distance kernels are siloed and lackes reusing overlapping logics. A refactor should happen to facilitate these dependencies.
Second, several implementation in kernels are not load balanced if the input is skewed. This can lead to unwanted performance degradation. As experimented in #1011, it is possible to create a perfectly load balanced kernel for any input geometries. It should be adopted for other distance API too.
Describe any alternatives you have considered
No response
Additional context
No response
Tasks
The text was updated successfully, but these errors were encountered: