JinjieLiu/triton-tvm-ffi
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enable optional for numwarps and numstages

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Signed-off-by: jinjieliu <jinjie.liu@usc.edu>
This commit is contained in:
jinjieliu
2026-02-05 01:01:49 +08:00
parent b7bf598fde
commit 8b8aa6cb84
3 changed files with 13 additions and 7 deletions
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3
examples/add/add.cc
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@@ -18,7 +18,8 @@ tvm::ffi::Tensor Add(tvm::ffi::Tensor x, tvm::ffi::Tensor y) {
int64_t numel = otorch.numel(); int64_t numel = otorch.numel();
tvm::ffi::Tensor output = tvm::ffi::Tensor::FromDLPack(at::toDLPack(otorch)); tvm::ffi::Tensor output = tvm::ffi::Tensor::FromDLPack(at::toDLPack(otorch));
tvm::ffi::Tuple<int32_t, int32_t, int32_t> grid{(numel + 1023) / 1024, 1, 1}; tvm::ffi::Tuple<int32_t, int32_t, int32_t> grid{(numel + 1023) / 1024, 1, 1};
size_t numWarps = 4, numStages = 3; // TODO: check the performance loss after enabling `Optional`
tvm::ffi::Optional<int32_t> numWarps = std::nullopt, numStages = std::nullopt;
DLDevice device = x.device(); DLDevice device = x.device();
void *stream = TVMFFIEnvGetStream(device.device_type, device.device_id); void *stream = TVMFFIEnvGetStream(device.device_type, device.device_id);
ADD_KERNEL_STUB(grid, stream, numWarps, numStages, x, y, output, numel, 1024); ADD_KERNEL_STUB(grid, stream, numWarps, numStages, x, y, output, numel, 1024);

14
python/triton_tvm_ffi/jit.py
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@@ -17,13 +17,14 @@ class TVMFFIJITFunction(object):
self.fn: Final[JITFunction] = fn self.fn: Final[JITFunction] = fn
self.ctypes: Optional[List[Optional[str]]] = None self.ctypes: Optional[List[Optional[str]]] = None
self.kernel: Optional[bytes] = None self.kernel: Optional[bytes] = None
self.num_warps: Optional[int] = None
@tvm_ffi.register_global_func(self.fullname) @tvm_ffi.register_global_func(self.fullname)
def _( def _(
grid: Tuple[int, int, int], grid: Tuple[int, int, int],
_: int, _: int,
num_warps: int, num_warps: Optional[int],
num_stages: int, num_stages: Optional[int],
*args, *args,
**kwargs, **kwargs,
): ):
@@ -31,9 +32,12 @@ class TVMFFIJITFunction(object):
kwargs: Dict[str, Any] = { kwargs: Dict[str, Any] = {
k: self.canonicalize(v) for k, v in kwargs.items() k: self.canonicalize(v) for k, v in kwargs.items()
} }
kernel: CompiledKernel = self.fn[grid]( if num_warps is not None:
*args, **kwargs, num_warps=num_warps, num_stages=num_stages kwargs["num_warps"] = num_warps
) if num_stages is not None:
kwargs["num_stages"] = num_stages
kernel: CompiledKernel = self.fn[grid](*args, **kwargs)
self.num_warps, _, _ = kernel.packed_metadata
self.ctypes = [type_canonicalize(v) for v in kernel.src.signature.values()] self.ctypes = [type_canonicalize(v) for v in kernel.src.signature.values()]
self.kernel = kernel.kernel self.kernel = kernel.kernel
return kernel return kernel

3
python/triton_tvm_ffi/wrap.py
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@@ -104,7 +104,7 @@ TVM_FFI_EMBED_CUBIN(triton_{fnname});
#define {}_STUB(__gtuple, __stream, __numWarps, __numStages, {}) do {{ \\ #define {}_STUB(__gtuple, __stream, __numWarps, __numStages, {}) do {{ \\
static auto __kernel = TVM_FFI_EMBED_CUBIN_GET_KERNEL(triton_{fnname}, "{fnname}"); \\ static auto __kernel = TVM_FFI_EMBED_CUBIN_GET_KERNEL(triton_{fnname}, "{fnname}"); \\
tvm::ffi::dim3 __grid(__gtuple.get<0>(), __gtuple.get<1>(), __gtuple.get<2>()); \\ tvm::ffi::dim3 __grid(__gtuple.get<0>(), __gtuple.get<1>(), __gtuple.get<2>()); \\
tvm::ffi::dim3 __block(__numWarps * 32, 1, 1); \\ tvm::ffi::dim3 __block({} * 32, 1, 1); \\
void *dummy = nullptr, {}; \\ void *dummy = nullptr, {}; \\
void *__params[] = {{{}, &dummy, &dummy}}; \\ void *__params[] = {{{}, &dummy, &dummy}}; \\
TVM_FFI_CHECK_CUBIN_LAUNCHER_CUDA_ERROR(__kernel.Launch(__params, __grid, __block, static_cast<tvm::ffi::cuda_api::StreamHandle>(__stream))); \\ TVM_FFI_CHECK_CUBIN_LAUNCHER_CUDA_ERROR(__kernel.Launch(__params, __grid, __block, static_cast<tvm::ffi::cuda_api::StreamHandle>(__stream))); \\
@@ -112,6 +112,7 @@ TVM_FFI_CHECK_CUBIN_LAUNCHER_CUDA_ERROR(__kernel.Launch(__params, __grid, __bloc
""".format( """.format(
fn.fnname.upper(), fn.fnname.upper(),
", ".join(arg for _, arg in ctype_arg_list), ", ".join(arg for _, arg in ctype_arg_list),
fn.num_warps if fn.num_warps is not None else "__numWarps",
", ".join( ", ".join(
f"*{arg}_ptr = {arg}.data_ptr()" f"*{arg}_ptr = {arg}.data_ptr()"
for ctype, arg in ctype_arg_list for ctype, arg in ctype_arg_list