Skip to content

Fix grid dimension overflow in fused Butina neighbor count kernel #194

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

Open
scal444 wants to merge 1 commit into
base: main
Choose a base branch
from
+13 −2
Open

Fix grid dimension overflow in fused Butina neighbor count kernel #194

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
15 changes: 13 additions & 2 deletions nvmolkit/_fusedButina.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,10 @@
import triton
import triton.language as tl

# CUDA caps gridDim.y and gridDim.z at 65535, while gridDim.x allows up to 2**31-1.
# Tiles are linearized across a 2D launch grid with the bounded axis kept here.
MAX_GRID_DIM = 65535


def get_cuda_autotune_config():
return [
Expand Down Expand Up @@ -121,9 +125,11 @@ def _update_neighbor_count_kernel(
Atomically adds (SUBTRACT=False) or subtracts (SUBTRACT=True) the per-row
neighbor counts into ``neighbors_ptr``.
"""
pid = tl.program_id(axis=0)
pid = tl.program_id(axis=0).to(tl.int64) + tl.program_id(axis=1).to(tl.int64) * tl.num_programs(axis=0).to(tl.int64)
num_pid_m = tl.cdiv(M, BLOCK_M)
num_pid_n = tl.cdiv(N, BLOCK_N)
if pid >= num_pid_m.to(tl.int64) * num_pid_n.to(tl.int64):
return
num_pid_in_group = GROUP_SIZE_M * num_pid_n
group_id = pid // num_pid_in_group
first_pid_m = group_id * GROUP_SIZE_M
Expand Down Expand Up @@ -271,7 +277,12 @@ def update_neighbor_counts(
M = x.shape[0]
N = y.shape[0]
K = x.shape[1]
grid = lambda META: (triton.cdiv(M, META["BLOCK_M"]) * triton.cdiv(N, META["BLOCK_N"]),)
def grid(meta):
num_tiles = triton.cdiv(M, meta["BLOCK_M"]) * triton.cdiv(N, meta["BLOCK_N"])
grid_y = min(num_tiles, MAX_GRID_DIM)
grid_x = triton.cdiv(num_tiles, grid_y)
return (grid_x, grid_y)

_update_neighbor_count_kernel[grid](
x,
y,
Expand Down
Loading