optionally enable epilog schedule (for now)

Author: shmsong

torch/csrc/jit/codegen/cuda/scheduler/matmul.cpp

@@ -311,8 +311,12 @@ void scheduleMatmul(
   // Setup accumulator register.
   auto cc = c->cacheBefore();
 
-  // Setup output smem buffer
-  auto c_smem = c->cacheBefore();
+  TensorView* c_smem = nullptr;
+
+  if (params.has_epilog) {
+    // Setup output smem buffer
+    c_smem = c->cacheBefore();
+  }
 
   // Get the input to the mma op.
   auto mma = dynamic_cast<MmaOp*>(cc->definition());
@@ -483,7 +487,10 @@ void scheduleMatmul(
   // Set memory type:
   acw_smem->setMemoryType(MemoryType::Shared);
   bcw_smem->setMemoryType(MemoryType::Shared);
-  c_smem->setMemoryType(MemoryType::Shared);
+
+  if (params.has_epilog) {
+    c_smem->setMemoryType(MemoryType::Shared);
+  }
 
   // Set parallelization:
   //   TODO: this section goes to a separate matmul util,
@@ -534,37 +541,44 @@ void scheduleMatmul(
     bcr->skewDoubleBuffer();
   }
 
+  auto output_buffer = params.has_epilog ? c_smem : c;
+
   scheduler_utils::BoundedDirectionalTransformPropagator::forward(
       cc,
       -1,
-      {c_smem},
-      scheduler_utils::BoundedDirectionalTransformPropagator::Options()
-          .propagateParallelType()
-          .propagateToBoundary());
-
-  // Epilog schedule:
-  scheduler_utils::BoundedDirectionalTransformPropagator::forward(
-      c_smem,
-      3,
-      {c},
+      {output_buffer},
       scheduler_utils::BoundedDirectionalTransformPropagator::Options()
           .propagateParallelType()
           .propagateToBoundary());
 
-  c_smem->computeAt(c, 3);
-  c->reorder({{-1, -2}, {-2, -1}});
-  // 16 x 128, with half of the warps:
-
-  // Output vectorize by 4:
-  c->split(-2, 2);
-  c->split(-1, 4);
-
-  // [8, 2, 32, 4]
-  c->axis(-3)->parallelize(ParallelType::TIDy);
-  c->axis(-2)->parallelize(ParallelType::TIDx);
-  c->axis(-1)->parallelize(ParallelType::Vectorize);
-  c_smem->axis(-1)->parallelize(ParallelType::Vectorize);
-  c_smem->doubleBuffer();
+  // Epilog schedule (To be built out):
+  if (params.has_epilog) {
+    scheduler_utils::BoundedDirectionalTransformPropagator::forward(
+        c_smem,
+        3,
+        {c},
+        scheduler_utils::BoundedDirectionalTransformPropagator::Options()
+            .propagateParallelType()
+            .propagateToBoundary());
+
+    c_smem->computeAt(c, 3);
+    c->reorder({{-1, -2}, {-2, -1}});
+    // 16 x 128, with half of the warps:
+
+    // Output vectorize by 4:
+    c->split(-2, 2);
+    c->split(-1, 4);
+
+    // [8, 2, 32, 4]
+    c->axis(-3)->parallelize(ParallelType::TIDy);
+    c->axis(-2)->parallelize(ParallelType::TIDx);
+    c->axis(-1)->parallelize(ParallelType::Vectorize);
+    c_smem->axis(-1)->parallelize(ParallelType::Vectorize);
+    c_smem->doubleBuffer();
+  } else {
+    // Always vector
+    c->axis(-1)->parallelize(ParallelType::Vectorize);
+  }
 
   if (params.index_lift_options.lift_gmem_read_address) {
     a->liftReadAddress();

torch/csrc/jit/codegen/cuda/scheduler/matmul.h

@@ -51,6 +51,9 @@ class MatmulParam {
 
   //! Enables predicate peeling mainloop:
   bool peel_main_loop = true;
+
+  //! Enables an epilog schedule
+  bool has_epilog = false;
 };
 
 //! Prototype auto scheduling function.