Skip to content

[FPSan] explicit lowerings for fmin/fmax #10039

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
apgoucher merged 2 commits into from
Apr 16, 2026
Merged

[FPSan] explicit lowerings for fmin/fmax #10039

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
913d47e
[FPSan] explicit lowerings for fmin/fmax
apgoucher Apr 15, 2026
34221de
Merge branch 'main' into fpsan_minmax
Apr 15, 2026
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
4 changes: 4 additions & 0 deletions lib/Dialect/TritonInstrument/Transforms/FpSanitizer.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2234,6 +2234,10 @@ class FpSanitizerPass
patterns.add<BinaryFloatToIntPattern<arith::AddFOp, arith::AddIOp>,
BinaryFloatToIntPattern<arith::SubFOp, arith::SubIOp>,
BinaryFloatToIntPattern<arith::MulFOp, arith::MulIOp>,
BinaryFloatToIntPattern<arith::MinimumFOp, arith::MinSIOp>,
BinaryFloatToIntPattern<arith::MaximumFOp, arith::MaxSIOp>,
BinaryFloatToIntPattern<arith::MinNumFOp, arith::MinSIOp>,
BinaryFloatToIntPattern<arith::MaxNumFOp, arith::MaxSIOp>,
DivFOpPattern, PreciseDivFOpPattern, RemFOpPattern, FmaPattern,
ExpOpPattern, Exp2OpPattern, CosOpPattern, SinOpPattern,
ExtFOpPattern, TruncFOpPattern, FpToFpPattern, Fp4ToFpPattern,
Expand Down
18 changes: 18 additions & 0 deletions python/test/gluon/test_fpsan.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -149,6 +149,18 @@ def _expected_mul_i32(x_i32: np.ndarray, y_i32: np.ndarray) -> np.ndarray:
return _payload_u32_to_f32_bits_i32(x_u32 * y_u32)


def _expected_min_i32(x_i32: np.ndarray, y_i32: np.ndarray) -> np.ndarray:
x = _u32_to_i32(_mix_f32_bits_to_payload_u32(x_i32))
y = _u32_to_i32(_mix_f32_bits_to_payload_u32(y_i32))
return _unmix_payload_u32_to_f32_bits_i32(np.minimum(x, y).astype(np.int32).view(np.uint32))


def _expected_max_i32(x_i32: np.ndarray, y_i32: np.ndarray) -> np.ndarray:
x = _u32_to_i32(_mix_f32_bits_to_payload_u32(x_i32))
y = _u32_to_i32(_mix_f32_bits_to_payload_u32(y_i32))
return _unmix_payload_u32_to_f32_bits_i32(np.maximum(x, y).astype(np.int32).view(np.uint32))


def _expected_srem_i32(x_i32: np.ndarray, y_i32: np.ndarray) -> np.ndarray:
# Match LLVM srem semantics: remainder after trunc-toward-zero division.
# NOTE: Python/NumPy '%' uses floor division for negatives, so we implement explicitly.
Expand Down Expand Up @@ -410,6 +422,10 @@ def _binop_kernel(x_ptr, y_ptr, out_ptr, n_elements, OP: gl.constexpr, BLOCK: gl
z = x - y
elif OP == "mul":
z = x * y
elif OP == "min":
z = gl.minimum(x, y)
elif OP == "max":
z = gl.maximum(x, y)
elif OP == "truediv":
z = x / y
elif OP == "fdiv":
Expand Down Expand Up @@ -512,6 +528,8 @@ def test_reciprocal_involution(device, fresh_knobs):
("add", _expected_add_i32),
("sub", _expected_sub_i32),
("mul", _expected_mul_i32),
("min", _expected_min_i32),
("max", _expected_max_i32),
("truediv", _expected_div_payload_i32),
("fdiv", _expected_div_payload_i32),
("mod", _expected_srem_i32),
Expand Down
Loading