Remove annoying warnings in sgl kernel build (#9905)

sgl-kernel/CMakeLists.txt

@@ -3,6 +3,7 @@ project(sgl-kernel LANGUAGES CXX CUDA)
 
 # CMake
 cmake_policy(SET CMP0169 OLD)
+cmake_policy(SET CMP0177 NEW)
 include(${CMAKE_CURRENT_LIST_DIR}/cmake/utils.cmake)
 set(CMAKE_COLOR_DIAGNOSTICS ON)
 set(CMAKE_VERBOSE_MAKEFILE ON CACHE BOOL "ON")
@@ -50,14 +51,7 @@ FetchContent_Declare(
 )
 FetchContent_Populate(repo-cutlass)
 
-FetchContent_Declare(
-    repo-fmt
-    GIT_REPOSITORY https://github.com/fmtlib/fmt
-    GIT_TAG        553ec11ec06fbe0beebfbb45f9dc3c9eabd83d28
-    GIT_SHALLOW    OFF
-)
-FetchContent_Populate(repo-fmt)
-
+# DeepGEMM
 FetchContent_Declare(
     repo-deepgemm
     GIT_REPOSITORY https://github.com/sgl-project/DeepGEMM
@@ -66,6 +60,14 @@ FetchContent_Declare(
 )
 FetchContent_Populate(repo-deepgemm)
 
+FetchContent_Declare(
+    repo-fmt
+    GIT_REPOSITORY https://github.com/fmtlib/fmt
+    GIT_TAG        553ec11ec06fbe0beebfbb45f9dc3c9eabd83d28
+    GIT_SHALLOW    OFF
+)
+FetchContent_Populate(repo-fmt)
+
 # Triton
 FetchContent_Declare(
     repo-triton
@@ -148,21 +150,40 @@ set(SGL_KERNEL_CUDA_FLAGS
     "--expt-extended-lambda"
     "--threads=32"
 
-    # Suppress warnings
-    "-Xcompiler=-Wconversion"
-    "-Xcompiler=-fno-strict-aliasing"
+    # Supress warnings
+    "-Xcompiler=-Wno-clang-format-violations"
+    "-Xcompiler=-Wno-conversion"
+    "-Xcompiler=-Wno-deprecated-declarations"
+    "-Xcompiler=-Wno-terminate"
+    "-Xcompiler=-Wfatal-errors"
+    "-Xcompiler=-ftemplate-backtrace-limit=1"
+    "-Xcudafe=--diag_suppress=177"  # variable was declared but never referenced
 
     # uncomment to debug
     # "--ptxas-options=-v"
     # "--ptxas-options=--verbose,--register-usage-level=10,--warn-on-local-memory-usage"
 )
 
-option(SGL_KERNEL_ENABLE_SM100A           "Enable SM100A"           OFF)
-option(SGL_KERNEL_ENABLE_SM90A            "Enable SM90A"            OFF)
 option(SGL_KERNEL_ENABLE_BF16             "Enable BF16"             ON)
 option(SGL_KERNEL_ENABLE_FP8              "Enable FP8"              ON)
 option(SGL_KERNEL_ENABLE_FP4              "Enable FP4"              OFF)
 option(SGL_KERNEL_ENABLE_FA3              "Enable FA3"              OFF)
+option(SGL_KERNEL_ENABLE_SM90A            "Enable SM90A"            OFF)
+option(SGL_KERNEL_ENABLE_SM100A           "Enable SM100A"           OFF)
+
+if (SGL_KERNEL_ENABLE_BF16)
+    list(APPEND SGL_KERNEL_CUDA_FLAGS
+        "-DFLASHINFER_ENABLE_BF16"
+    )
+endif()
+
+if (SGL_KERNEL_ENABLE_FP8)
+    list(APPEND SGL_KERNEL_CUDA_FLAGS
+        "-DFLASHINFER_ENABLE_FP8"
+        "-DFLASHINFER_ENABLE_FP8_E4M3"
+        "-DFLASHINFER_ENABLE_FP8_E5M2"
+    )
+endif()
 
 if (ENABLE_BELOW_SM90)
     list(APPEND SGL_KERNEL_CUDA_FLAGS
@@ -210,31 +231,12 @@ if ("${CUDA_VERSION}" VERSION_GREATER_EQUAL "12.4" OR SGL_KERNEL_ENABLE_SM90A)
     )
 endif()
 
-if (SGL_KERNEL_ENABLE_BF16)
-    list(APPEND SGL_KERNEL_CUDA_FLAGS
-        "-DFLASHINFER_ENABLE_BF16"
-    )
-endif()
-
-if (SGL_KERNEL_ENABLE_FP8)
-    list(APPEND SGL_KERNEL_CUDA_FLAGS
-        "-DFLASHINFER_ENABLE_FP8"
-        "-DFLASHINFER_ENABLE_FP8_E4M3"
-        "-DFLASHINFER_ENABLE_FP8_E5M2"
-    )
-endif()
-
 if ("${CUDA_VERSION}" VERSION_GREATER_EQUAL "12.8" OR SGL_KERNEL_ENABLE_FP4)
     list(APPEND SGL_KERNEL_CUDA_FLAGS
         "-DENABLE_NVFP4=1"
     )
 endif()
 
-string(REPLACE "-D__CUDA_NO_HALF_OPERATORS__"       "" CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS}")
-string(REPLACE "-D__CUDA_NO_HALF_CONVERSIONS__"     "" CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS}")
-string(REPLACE "-D__CUDA_NO_BFLOAT16_CONVERSIONS__" "" CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS}")
-string(REPLACE "-D__CUDA_NO_HALF2_OPERATORS__"      "" CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS}")
-
 set(SOURCES
     "csrc/allreduce/custom_all_reduce.cu"
     "csrc/allreduce/mscclpp_allreduce.cu"

sgl-kernel/Makefile

@@ -21,12 +21,11 @@ submodule: ## Initialize and update git submodules
 ln: submodule ## Create compilation database
 	@rm -rf build && mkdir build && cd build && cmake .. -DCMAKE_EXPORT_COMPILE_COMMANDS=YES -DCMAKE_POLICY_VERSION_MINIMUM=3.5
 
-
 install: submodule ## Install package in development mode
 	@pip install -e . --no-build-isolation
 
 build: install-deps submodule ## Build and install wheel package
-	@rm -rf dist/* || true && export MAX_JOBS=$(nproc) && CMAKE_POLICY_VERSION_MINIMUM=3.5 CMAKE_BUILD_PARALLEL_LEVEL=$(nproc) uv build --wheel -Cbuild-dir=build . --verbose --color=always --no-build-isolation && pip3 install dist/*whl --force-reinstall --no-deps
+	@rm -rf dist/* || true && CMAKE_POLICY_VERSION_MINIMUM=3.5 MAX_JOBS=$(nproc) CMAKE_BUILD_PARALLEL_LEVEL=$(nproc) uv build --wheel -Cbuild-dir=build . --verbose --color=always --no-build-isolation && pip3 install dist/*whl --force-reinstall --no-deps
 
 clean: ## Remove build artifacts
 	@rm -rf build dist *.egg-info

sgl-kernel/csrc/attention/cutlass_mla_kernel.cu

@@ -162,7 +162,7 @@ typename T::Fmha::Arguments args_from_options(
       // TODO(trevor-m): Change split_kv back to -1 when
       // https://github.com/NVIDIA/cutlass/issues/2274 is fixed. Split_kv=1 will
       // perform worse with larger context length and smaller batch sizes.
-      num_kv_splits, // split_kv
+      static_cast<int>(num_kv_splits), // split_kv
       nullptr,       // is_var_split_kv
   };
   // TODO(kaixih@nvidia): When split_kv=-1 and is_var_split_kv=false, we compute
@@ -259,7 +259,7 @@ int64_t cutlass_mla_get_workspace_size(int64_t max_seq_len, int64_t num_batches,
   // Assumes device 0 when getting sm_count.
   arguments.hw_info.sm_count =
       sm_count <= 0 ? cutlass::KernelHardwareInfo::query_device_multiprocessor_count(/*device_id=*/0) : sm_count;
-  arguments.split_kv = num_kv_splits;
+  arguments.split_kv = static_cast<int>(num_kv_splits);
   MlaSm100Type::Fmha::set_split_kv(arguments);
 
   return MlaSm100Type::Fmha::get_workspace_size(arguments);

sgl-kernel/csrc/gemm/dsv3_fused_a_gemm.cu

@@ -131,6 +131,7 @@ __device__ bool try_wait_barrier(uint64_t* smem_ptr, int phase_bit) {
       : "r"(smem_int_ptr), "r"(phase_bit));
   return static_cast<bool>(wait_complete);
 #endif
+  return false;
 }
 
 // Barrier arrive

sgl-kernel/csrc/gemm/nvfp4_expert_quant.cu

@@ -541,6 +541,11 @@ void quant_impl(
   }
 }
 
+// Avoid redefinition warnings
+#undef CHECK_CONTIGUOUS
+#undef CHECK_TH_CUDA
+#undef CHECK_INPUT
+
 /*Quantization entry for fp4 experts quantization*/
 #define CHECK_TH_CUDA(x, m) TORCH_CHECK(x.is_cuda(), m, "must be a CUDA tensor")
 #define CHECK_CONTIGUOUS(x, m) TORCH_CHECK(x.is_contiguous(), m, "must be contiguous")