Skip to content

[MetaSchedule] Fix thread bindings of MultiLevelTilingTensorCore #13243

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
masahi merged 1 commit into from
Nov 1, 2022
Merged

[MetaSchedule] Fix thread bindings of MultiLevelTilingTensorCore #13243

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
5 changes: 5 additions & 0 deletions src/meta_schedule/schedule_rule/multi_level_tiling_tensor_core.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -556,6 +556,11 @@ ScheduleRule ScheduleRule::MultiLevelTilingTensorCore(
Optional<Integer> max_innermost_factor, Optional<Array<Integer>> vector_load_lens,
Optional<Map<String, ObjectRef>> reuse_read, Optional<Map<String, ObjectRef>> reuse_write,
bool use_software_pipeline) {
if (tile_binds.defined()) {
for (const String& tile_bind : tile_binds.value()) {
CHECK_NE(tile_bind, "threadIdx.x") << "Cannot bind to threadIdx.x when using tensor core.";
}
}
Comment on lines +559 to +563
Copy link
Contributor

@csullivan csullivan Oct 31, 2022

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Does this check (along with existing tests) now cover the regression this fixes? If not adding a test to protect against the regression in the future will surely save you and others time!

Copy link
Contributor

@csullivan csullivan Oct 31, 2022 •
edited
Loading

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Oops looks like @junrushao already asked my question, I trust your judgements :)

Copy link
Member Author

@vinx13 vinx13 Oct 31, 2022

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Yes this check covered the broken case that incorrectly using threadIdx.x. As a follow up, I'm thinking also adding some e2e search space generation test for the default config for each target.

auto node = MultiLevelTilingInitCommon<MultiLevelTilingTensorCoreNode>(
structure, tile_binds, max_innermost_factor, vector_load_lens, reuse_read, reuse_write);

Expand Down
2 changes: 1 addition & 1 deletion src/meta_schedule/schedule_rule/schedule_rule.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -139,7 +139,7 @@ Array<ScheduleRule> ScheduleRule::DefaultCUDATensorCore() {
Array<ScheduleRule> results{ScheduleRule::MultiLevelTilingTensorCore(
/*intrin_groups=*/intrin_groups,
/*structure=*/"SSSRRSRS",
/*tile_binds=*/Array<String>{"blockIdx.x", "vthread.x", "threadIdx.x"},
/*tile_binds=*/Array<String>{"blockIdx.y", "blockIdx.x", "threadIdx.y"},
/*max_innermost_factor=*/Integer(4),
/*vector_load_lens=*/Array<Integer>{1, 2, 3, 4, 8, 16},
/*reuse_read=*/
Expand Down