[BACKEND][NVIDIA] Add DotOp Hoisting Pass for WGMMA and Add Lowering for SMEM-to-MMAv3 DotOp Copy

include/triton/Dialect/TritonGPU/Transforms/Utility.h

@@ -195,7 +195,13 @@ int getNVIDIAComputeCapability(Operation *module);
 std::optional<mlir::triton::gpu::SharedEncodingAttr>
 getSharedEncIfAllUsersAreDotEnc(Value val, bool &incompatible);
 
-bool loadIsMMAv3(Operation *loadOp);
+enum class MMALoadType {
+  SharedV3,
+  Registers,     // may be v2 or v3
+  DoNotPipeline, // could be a valid shared/registers MMA operand, but skip
+                 // pipelining
+};
+MMALoadType getMMALoadType(Operation *loadOp);
 } // namespace mlir
 
 #endif // TRITON_DIALECT_TRITONGPU_TRANSFORMS_UTILITY_H_

lib/Dialect/TritonGPU/Transforms/LoopScheduling.cpp

@@ -145,11 +145,18 @@ filterPipelinedLoad(llvm::SmallVector<std::tuple<Operation *, int, Operation *>>
 
     bool hasSharedEncoding = false;
     if (use->hasTrait<OpTrait::DotLike>()) {
-      if (loadIsMMAv3(op)) {
+      auto mmaLoadType = getMMALoadType(op);
+      auto dot = dyn_cast<tt::DotOp>(use);
+      auto warpGroupDot = dyn_cast<ttng::WarpGroupDotOp>(use);
+      bool isMMAv3Shared = mmaLoadType == MMALoadType::SharedV3;
+      bool isMMAv3Registers =
+          (mmaLoadType == MMALoadType::Registers) && warpGroupDot;
+
+      if (isMMAv3Shared) {
         hasSharedEncoding = true;
       } else if (isa<tt::ExperimentalDescriptorLoadOp>(op)) {
         hasSharedEncoding = true;
-      } else if (auto dot = dyn_cast<tt::DotOp>(use)) {
+      } else if (isMMAv3Registers || dot) {
         // FIXME: if we have a better solution in handling incompatible shared
         // encoding, we can simplify the logic here by checking if all users are
         // dot encoding. Fow now, getSharedEncIfAllUsersAreDotEnc will be used

lib/Dialect/TritonGPU/Transforms/OptimizeDotOperands.cpp

@@ -1,9 +1,11 @@
+#include "mlir/IR/IRMapping.h"
 #include "mlir/IR/TypeUtilities.h"
 #include "mlir/Pass/PassManager.h"
 #include "mlir/Support/LogicalResult.h"
 #include "mlir/Transforms/GreedyPatternRewriteDriver.h"
 #include "mlir/Transforms/Passes.h"
 #include "triton/Analysis/Utility.h"
+#include "triton/Dialect/TritonGPU/IR/Attributes.h"
 #include "triton/Dialect/TritonGPU/IR/Dialect.h"
 #include "triton/Dialect/TritonGPU/Transforms/Passes.h"
 #include "triton/Dialect/TritonGPU/Transforms/Utility.h"
@@ -15,6 +17,125 @@ namespace gpu {
 
 namespace {
 
+// Helpers
+
+// Returns whether we can hoist DotOp Encoding through `op`.
+// Roughly, whether op is elementwise and thus threads don't need
+// to exchange elements. But some ops are not currently supported even though
+// they meet that criterion.
+bool canHoistDotOpEncV2(Operation *op, DotOperandEncodingAttr &dotOpEnc) {
+  // Only consider custom conversions or arith ops.
+  // TODO(jlebar): Is this too restrictive?
+  if (!isa<FpToFpOp, BitcastOp>(op) && !isPureUnaryInlineAsm(op) &&
+      !isa<arith::ArithDialect>(op->getDialect()))
+    return false;
+
+  // Quick handling to fix loading issues when computing the original
+  // bitwidth is unable to realize that there is a mixed-precision dot
+  // (hence kWidth = 1) but wants to hoist through the type conversion.
+  if (isa<arith::ExtFOp>(op) && dotOpEnc.getKWidth() == 1)
+    return false;
+
+  // Currently, these instructions are not supported during lowering of
+  // shared -> dot_operand layout. Not all types and type conversions are
+  // supported.
+  if (isa<arith::TruncIOp, arith::TruncFOp, arith::SelectOp>(op))
+    return false;
+
+  // Don't hoist through u1 -> fp casts as they aren't supported in
+  // ElementwiseOpToLLVM::reorderValues().
+  if (isa<arith::UIToFPOp>(op)) {
+    Type opType = getElementTypeOrSelf(op->getOperand(0));
+    if (opType.isInteger(1))
+      return false;
+  }
+
+  return true;
+}
+
+// Analog of canHoistDotOpEncV2, but for MMAv3 (WGMMA where operand A
+// is in registers).
+bool canHoistDotOpEncV3(Operation *op) {
+  // Must have exactly one result and at least one operand
+  if (op->getNumOperands() == 0 || op->getNumResults() != 1)
+    return false;
+
+  auto isBlockedOrDotOpRankedTensor = [](Type ty) {
+    auto tensorTy = dyn_cast<RankedTensorType>(ty);
+    if (!tensorTy)
+      return false;
+    return isa<BlockedEncodingAttr, DotOperandEncodingAttr>(
+        tensorTy.getEncoding());
+  };
+
+  // Operands and results must be of RankedTensorType and Blocked or DotOp
+  if (!(all_of(op->getOperandTypes(), isBlockedOrDotOpRankedTensor) &&
+        all_of(op->getResultTypes(), isBlockedOrDotOpRankedTensor)))
+    return false;
+
+  // Only consider custom conversions or arith ops.
+  if (!isa<FpToFpOp, BitcastOp>(op) && !isPureUnaryInlineAsm(op) &&
+      !isa<arith::ArithDialect>(op->getDialect()))
+    return false;
+
+  // Currently, these instructions are not supported during lowering of
+  // shared -> dot_operand layout. Not all types and type conversions are
+  // supported.
+  if (isa<arith::SelectOp>(op))
+    return false;
+
+  // Downcasting not currently supported; it will likely require minor
+  // adjustments in sharedToDotOperandMMv2
+  auto oprType = getElementTypeOrSelf(op->getOperand(0));
+  auto resType = getElementTypeOrSelf(op->getResult(0));
+  if (oprType.getIntOrFloatBitWidth() > resType.getIntOrFloatBitWidth())
+    return false;
+
+  // Don't hoist through u1 -> fp casts as they aren't supported in
+  // ElementwiseOpToLLVM::reorderValues().
+  if (isa<arith::UIToFPOp>(op) && oprType.isInteger(1))
+    return false;
+
+  return true;
+}
+
+// Helper to perform a "deep" clone of the given slice (i.e., set of ops),
+// returning a tuple (newSlice, sliceMap), where newSlice is the cloned slice,
+// and sliceMap the IRMapping that maps the ops and result values of the
+// original slice to those in the cloned slice.
+auto cloneSlice(PatternRewriter &rewriter,
+                const SetVector<Operation *> &slice) {
+  IRMapping sliceMap;
+  SetVector<Operation *> newSlice;
+
+  // First pass: clone ops; the result values are cloned as well, but the
+  // operands still refer to the original result values
+  for (Operation *op : slice) {
+    rewriter.setInsertionPoint(op);
+    auto newOp = rewriter.clone(*op);
+    newSlice.insert(newOp);
+    sliceMap.map(op, newOp);
+    for (auto [result, newResult] :
+         llvm::zip(op->getResults(), newOp->getResults())) {
+      assert(result != newResult);
+      sliceMap.map(result, newResult);
+    }
+  }
+
+  // Second pass: replace operand references in cloned ops to point to cloned
+  // values
+  for (auto [op, newOp] : sliceMap.getOperationMap())
+    for (auto [oprIdx, operand] : llvm::enumerate(newOp->getOperands())) {
+      auto defOp = operand.getDefiningOp();
+      if (!slice.contains(defOp))
+        continue;
+
+      newOp->setOperand(oprIdx, sliceMap.lookup(operand));
+    }
+
+  return std::make_tuple(newSlice, sliceMap);
+}
+
 // Given
 //   convert(trans(src)) #dot_operand ->
 //   convert(local_load(trans(alloc(src))))
@@ -111,7 +232,8 @@ class HoistLayoutConversion : public OpRewritePattern<ConvertLayoutOp> {
                                 PatternRewriter &rewriter) const override {
     // Only consider conversions to dot operand.
     auto cvtTy = cast<RankedTensorType>(cvt.getType());
-    if (!isa<DotOperandEncodingAttr>(cvtTy.getEncoding()))
+    auto dotOpEnc = dyn_cast<DotOperandEncodingAttr>(cvtTy.getEncoding());
+    if (!dotOpEnc)
       return failure();
 
     auto src = cvt.getSrc().getDefiningOp();
@@ -126,16 +248,7 @@ class HoistLayoutConversion : public OpRewritePattern<ConvertLayoutOp> {
                 [](Type ty) { return isa<RankedTensorType>(ty); }))
       return failure();
 
-    // Only consider custom conversions or arith ops.
-    // TODO(jlebar): Is this too restrictive?
-    if (!isa<FpToFpOp, BitcastOp>(src) && !isPureUnaryInlineAsm(src) &&
-        src->getDialect()->getTypeID() != TypeID::get<arith::ArithDialect>())
-      return failure();
-
-    // Currently, these instructions are not supported during lowering of
-    // shared -> dot_operand layout. Not all types and type conversions are
-    // supported.
-    if (isa<arith::TruncIOp, arith::TruncFOp, arith::SelectOp>(src))
+    if (!canHoistDotOpEncV2(src, dotOpEnc))
       return failure();
 
     // Check that the conversion is transitively dependent on a load, and all
@@ -165,12 +278,7 @@ class HoistLayoutConversion : public OpRewritePattern<ConvertLayoutOp> {
       if (isa<LoadOp>(currOp)) {
         foundLoad = true;
       } else if (foundLoad) {
-        // Bail out if there exists an op after Load that is not FpToFp,
-        // Bitcast, or Arith.
-        if (!isa<FpToFpOp, BitcastOp>(currOp) &&
-            !isPureUnaryInlineAsm(currOp) &&
-            currOp->getDialect()->getTypeID() !=
-                TypeID::get<arith::ArithDialect>())
+        if (!canHoistDotOpEncV2(currOp, dotOpEnc))
           return failure();
       }
     }
@@ -301,6 +409,150 @@ struct MMAV3UseRegOperand
   }
 };
 
+// MMAV3's analog of HoistLayoutConversion, for operand A only; will make
+// WarpGroupDot accept operand A in registers instead of shmem.
+//
+// Before: load #blocked; (elementwise #blocked)+; local_alloc; warp_group_dot
+// After:  load #blocked; convert_layout #dot_op; (elementwise #dot_op)+;
+// warp_group_dot
+//
+// Whereas (MMAV2) HoistLayoutConversion hoists thru one elementwise op at a
+// time and requires multiple passes, this pattern will directly hoist the
+// convert to the right place in one pass.
+//
+// Or, to be more precise, this pattern deletes the local_alloc op and inserts a
+// convert_layout op after each load that warp_group_dot uses; so this is not
+// simply hoisting a convert_layout op up as in V2, but can be considered as
+// first changing local_alloc to convert_layout and then hoisting, which results
+// in WGMMA now accepting operand A in DotOp layout rather than Shared.
+struct MMAV3HoistLayoutConversion
+    : public OpRewritePattern<triton::nvidia_gpu::WarpGroupDotOp> {
+  using OpRewritePattern::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(triton::nvidia_gpu::WarpGroupDotOp dotOp,
+                                PatternRewriter &rewriter) const override {
+    // Can only hoist operand 0
+    auto alloc = dotOp.getOperand(0).getDefiningOp<LocalAllocOp>();
+    if (!alloc || !alloc.getSrc())
+      return rewriter.notifyMatchFailure(
+          dotOp, "operand A must be produced by local_alloc");
+
+    auto getEncoding = [](Value v) {
+      return cast<TensorOrMemDesc>(v.getType()).getEncoding();
+    };
+
+    if (!isa<SharedEncodingAttr>(getEncoding(dotOp.getOperand(0))))
+      return rewriter.notifyMatchFailure(
+          dotOp, "requires Shared encoding for operand A");
+
+    // Step 1: Performs checks for early stop
+    auto srcEnc = dyn_cast<BlockedEncodingAttr>(getEncoding(alloc.getSrc()));
+    if (!srcEnc)
+      return rewriter.notifyMatchFailure(
+          alloc, "requires src to have Blocked encoding");
+
+    auto dstEnc =
+        dyn_cast<NvidiaMmaEncodingAttr>(getEncoding(dotOp.getResult()));
+    if (!dstEnc || dstEnc.getVersionMajor() != 3)
+      return rewriter.notifyMatchFailure(
+          dotOp, "requires result in NvidiaMma encoding");
+
+    // Step 2: Obtain slice of ops between load/constant and local_alloc
+    SetVector<Operation *> slice;
+    BackwardSliceOptions opt;
+    opt.omitBlockArguments = true;
+    opt.filter = [&](Operation *op) {
+      // Stop before Load, ConstantOp, or LocalLoad
+      return (op->getParentRegion() == alloc->getParentRegion()) &&
+             !isa<LoadOp, arith::ConstantOp, LocalLoadOp>(op) &&
+             (op->getNumOperands() != 0);
+    };
+    getBackwardSlice(alloc.getOperation(), &slice, opt);
+
+    // Step 3: Verify slice can be hoisted through
+    if (slice.empty())
+      return rewriter.notifyMatchFailure(dotOp, "nothing to hoist through");
+
+    // We define frontierOp as an op outside this slice whose result is used by
+    // an op in this slice. We must eventually convert the result of all
+    // frontierOps to DotOperandEncoding. This is done via the insertion of
+    // ConvertLayout after each frontierOp. We currently support frontierOp to
+    // be load or constant.
+    for (Operation *currOp : slice) {
+      if (!canHoistDotOpEncV3(currOp))
+        return rewriter.notifyMatchFailure(currOp, "cannot hoist through");
+
+      // We previously ensured that all ops in slice have at least one operand
+      for (auto operand : currOp->getOperands()) {
+        auto defOp = operand.getDefiningOp();
+        if (!slice.contains(defOp)) {
+          // ensure frontierOp is load or constant
+          if (!isa<LoadOp, arith::ConstantOp>(defOp))
+            return rewriter.notifyMatchFailure(defOp,
+                                               "must be load or constant");
+        }
+      }
+    }
+
+    // Step 4: Clone slice
+    auto [newSlice, sliceMap] = cloneSlice(rewriter, slice);
+
+    // Step 5: Modify the cloned slice to have dotOp encoding.
+    // Before: load #blocked; (elementwise #blocked)+; local_alloc;
+    // warp_group_dot After:  load #blocked; convert_layout #dot_op;
+    // (elementwise #dot_op)+; warp_group_dot
+    //
+    // Specifically, this step will change all value types from #blocked to
+    // #dot_op encoding in the cloned slice, and for those values produced by
+    // frontierOps (i.e., outside the slice), we will insert convert_layout's
+    // after the frontierOp.
+    auto srcTy = cast<RankedTensorType>(alloc.getSrc().getType());
+    Type inputEltTy = srcTy.getElementType();
+    auto dotOperandEnc = DotOperandEncodingAttr::get(
+        dotOp.getContext(), /*opIdx=*/0, dstEnc, inputEltTy);
+
+    for (auto op : newSlice) {
+      // Step 5a: If any operand is defined by a frontierOp, we must insert a
+      // convert_layout(#dot_op) after the frontierOp and before currOp
+      for (auto [oprIdx, operand] : llvm::enumerate(op->getOperands())) {
+
+        auto defOp = operand.getDefiningOp();
+
+        // defOp is not frontier (i.e. it's within slice); no need to convert
+        // the layout of its result
+        if (newSlice.contains(defOp))
+          continue;
+
+        // We checked earlier that all operands are ranked tensors
+        auto operandTy = cast<RankedTensorType>(operand.getType());
+        auto operandEltTy = operandTy.getElementType();
+
+        Type cvtTy = RankedTensorType::get(
+            operandTy.getShape(), operandTy.getElementType(), dotOperandEnc);
+        rewriter.setInsertionPoint(op);
+        auto cvt =
+            rewriter.create<ConvertLayoutOp>(defOp->getLoc(), cvtTy, operand);
+
+        op->setOperand(oprIdx, cvt);
+      }
+
+      // Step 5b: Change the result to have DotOp rather than Blocked encoding
+      auto resTy = cast<RankedTensorType>(op->getResult(0).getType());
+      op->getResult(0).setType(RankedTensorType::get(
+          resTy.getShape(), resTy.getElementType(), dotOperandEnc));
+    }
+
+    // Step 6: replace LHS operand with alloc's parent in the cloned slice
+    // This changes the warpGroupDot to accept a DotOp tensor as operand A
+    // instead of a Shared memdesc.
+    auto newDotOperand = sliceMap.lookup(alloc.getSrc());
+    rewriter.modifyOpInPlace(dotOp,
+                             [&]() { dotOp.setOperand(0, newDotOperand); });
+
+    return success();
+  }
+};
+
 } // namespace
 
 #define GEN_PASS_DEF_TRITONGPUOPTIMIZEDOTOPERANDS
@@ -322,6 +574,7 @@ class TritonGPUOptimizeDotOperandsPass
     auto ret = pm.run(m);
 
     mlir::RewritePatternSet patterns(context);
+    patterns.add<MMAV3HoistLayoutConversion>(context);
     patterns.add<SwizzleShmemConvert>(context);
     if (this->hoistLayoutConversion.getValue())
       patterns.add<HoistLayoutConversion>(context);