refactor: split attention kernel into collective mainloop, collective epilogue and kernel

src/kernels/attention/CMakeLists.txt

@@ -4,7 +4,7 @@ include(cc_library)
 include(cc_test)
 
 cc_library(
-  NAME 
+  NAME
     attention.template
   HDRS
     fast_math.h
@@ -15,9 +15,8 @@ cc_library(
     static_dispatch.h
     mha_params.h
     mha_tile.h
-    mha_traits_sm80.h
     mha_kernel_sm80.cuh
-    mha_dispatch_sm80.cuh
+    sm80_mha_dispatch.cuh
     mla_params.h
     mla_tile.h
     mla_traits_sm80.h
@@ -39,11 +38,11 @@ execute_process(
   WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/
   COMMAND_ERROR_IS_FATAL ANY
 )
-# globbing all generated files in sub directory "generated"
-file(GLOB GENERATED_SRC_FILES "${CMAKE_CURRENT_BINARY_DIR}/generated/*.cu")
+# globbing all generated files in sub directory "gensrc"
+file(GLOB GENERATED_SRC_FILES "${CMAKE_CURRENT_BINARY_DIR}/gensrc/*.cu")
 
 cc_library(
-  NAME 
+  NAME
     attention.kernels
   HDRS
     attn_api.h
@@ -62,9 +61,8 @@ cc_test(
     mha_kernel_test
   SRCS
     # mha_cpu_test.cpp
-    mha_traits_test.cpp
-    mha_kernel_sm80_test.cu
-    mha_kernel_sm80_pagedkv_test.cu
+    sm80_mha_test.cu
+    sm80_mha_pagedkv_test.cu
   DEPS
     :attention.template
     absl::random_random
@@ -99,31 +97,31 @@ cc_test(
 )
 
 nvbench_binary(
-  NAME 
-    mha_sm80_bench
-  SRCS 
-    mha_sm80_bench.cu
+  NAME
+    sm80_mha_bench
+  SRCS
+    sm80_mha_bench.cu
   DEPS
-    :attention.template 
+    :attention.template
 )
 
 nvbench_binary(
-  NAME 
-    mha_sm80_pagedkv_bench
-  SRCS 
-    mha_sm80_pagedkv_bench.cu
+  NAME
+    sm80_mha_pagedkv_bench
+  SRCS
+    sm80_mha_pagedkv_bench.cu
   DEPS
     absl::random_random
     :attention.template
 )
 
 nvbench_binary(
-  NAME 
+  NAME
     mla_sm80_bench
-  SRCS 
+  SRCS
     mla_sm80_bench.cu
   DEPS
-    :attention.template 
+    :attention.template
 )
 
-add_subdirectory(tools)
+add_subdirectory(tools)

src/kernels/attention/attn_api.cpp

@@ -3,8 +3,8 @@
 #include <ATen/cuda/CUDAContext.h>
 
 #include "cute/layout.hpp"
-#include "mha_dispatch_sm80.cuh"
 #include "mha_params.h"
+#include "sm80_mha_dispatch.cuh"
 #include "static_dispatch.h"
 
 namespace llm {
@@ -66,7 +66,7 @@ void paged_kv_varlen_mha(
   cudaStream_t stream = at::cuda::getCurrentCUDAStream().stream();
   DISPATCH_HEAD_DIM(head_dim, HEAD_DIM, [&] {
     DISPATCH_TORCH_DTYPE(query.scalar_type(), DTYPE, [&] {
-      run_mha_kernel_sm80<DTYPE, HEAD_DIM>(params, stream);
+      sm80_run_mha<DTYPE, HEAD_DIM>(params, stream);
     });
   });
 }

src/kernels/attention/generate_instantiation_cu.py

@@ -20,21 +20,21 @@
 
 
 MHA_KERNEL_TEMPLATE = """
-#include "mha_kernel_sm80.cuh"  // IWYU pragma: export
+#include "sm80_mha_launch.cuh"  // IWYU pragma: export
 #include "mha_params.h"         // IWYU pragma: export
 
 namespace llm {{
 
 using Params = MHAPagedKVParams;
 
-template void launch_mha_kernel_sm80</*DTYPE=*/{DTYPE},
+template void sm80_launch_mha_kernel</*DTYPE=*/{DTYPE},
                                      /*HEAD_DIM=*/{HEAD_DIM},
                                      /*EVEN_K=*/{EVEN_K},
                                      /*ALIBI=*/{ALIBI},
                                      /*SOFT_CAP=*/{SOFT_CAP},
                                      /*LOCAL=*/{LOCAL},
                                      Params>(const Params& params,
-                                                        cudaStream_t stream);
+                                             cudaStream_t stream);
 }}  // namespace llm
 """
 
@@ -79,7 +79,7 @@ def filename(self) -> str:
         def to_str(val: bool) -> str:
             return "1" if val else "0"
 
-        return f"mha_{self.dtype}_hd{self.head_dim}_ek{to_str(self.even_k)}_al{to_str(self.alibi)}_sc{to_str(self.soft_cap)}_lc{to_str(self.local)}_sm80.cu"
+        return f"sm80_mha_{self.dtype}_hd{self.head_dim}_ek{to_str(self.even_k)}_al{to_str(self.alibi)}_sc{to_str(self.soft_cap)}_lc{to_str(self.local)}.cu"
 
 
 @dataclass
@@ -164,7 +164,7 @@ def gen_mla_kernels() -> Iterator[MLAKernel]:
 
 
 if __name__ == "__main__":
-    output_dir = Path.cwd() / "generated"
+    output_dir = Path.cwd() / "gensrc"
     shutil.rmtree(output_dir, ignore_errors=True)
     output_dir.mkdir(parents=True, exist_ok=True)