From da2993e1c75f930653cef5489e8b7bbd7dcb6ef3 Mon Sep 17 00:00:00 2001
From: Superjomn <yanchunwei@outlook.com>
Date: Wed, 2 Nov 2022 18:02:49 +0800
Subject: [PATCH] init code

---
 .../TritonGPUToLLVM/TritonGPUToLLVM.cpp       | 135 +++++++++++++++++-
 1 file changed, 131 insertions(+), 4 deletions(-)

diff --git a/lib/Conversion/TritonGPUToLLVM/TritonGPUToLLVM.cpp b/lib/Conversion/TritonGPUToLLVM/TritonGPUToLLVM.cpp
index a8da162a3..08b547468 100644
--- a/lib/Conversion/TritonGPUToLLVM/TritonGPUToLLVM.cpp
+++ b/lib/Conversion/TritonGPUToLLVM/TritonGPUToLLVM.cpp
@@ -2836,10 +2836,7 @@ private:
                               ConversionPatternRewriter &rewriter) const;
 
   LogicalResult convertFMADot(triton::DotOp op, OpAdaptor adaptor,
-                              ConversionPatternRewriter &rewriter) const {
-    assert(false && "Not implemented yet.");
-    return failure();
-  }
+                              ConversionPatternRewriter &rewriter) const;
 };
 
 // Helper for conversion of DotOp with mma<version=1>, that is sm<80
@@ -4095,6 +4092,136 @@ DotOpMmaV1ConversionHelper::extractLoadedOperand(
   return rcds;
 }
 
+LogicalResult
+DotOpConversion::convertFMADot(triton::DotOp op, OpAdaptor adaptor,
+                               ConversionPatternRewriter &rewriter) const {
+  auto *ctx = rewriter.getContext();
+  auto loc = op.getLoc();
+  auto threadId = getThreadId(rewriter, loc);
+
+  auto A = op.a();
+  auto B = op.b();
+  auto C = op.c();
+  auto D = op.getResult();
+
+  auto aTensorTy = A.getType().cast<RankedTensorType>();
+  auto bTensorTy = B.getType().cast<RankedTensorType>();
+  auto cTensorTy = C.getType().cast<RankedTensorType>();
+  auto dTensorTy = D.getType().cast<RankedTensorType>();
+
+  auto aShape = aTensorTy.getShape();
+  auto bShape = bTensorTy.getShape();
+  auto cShape = cTensorTy.getShape();
+
+  auto aLayout = aTensorTy.getEncoding().cast<SharedEncodingAttr>();
+  auto bLayout = bTensorTy.getEncoding().cast<SharedEncodingAttr>();
+  auto cLayout = cTensorTy.getEncoding().cast<MmaEncodingAttr>();
+  auto dLayout = dTensorTy.getEncoding().cast<MmaEncodingAttr>();
+
+  auto aOrder = aLayout.getOrder();
+  auto bOrder = bLayout.getOrder();
+
+  // According to the original logic, if target.sm < 80, get a {0,1} or get a
+  // {1,0}
+  SmallVector<int> order(2);
+  if (dLayout.getVersion() == 1)
+    order = {0, 1};
+  else
+    order = {1, 0};
+
+  bool isARow = aOrder[0] == 1;
+  bool isBRow = bOrder[0] == 1;
+
+  int strideAM = isARow ? aShape[1] : 1;
+  int strideAK = isARow ? 1 : aShape[0];
+  int strideBN = isBRow ? 1 : aShape[0];
+  int strideBK = isBRow ? bShape[1] : 1;
+  int strideA0 = isARow ? strideAK : strideAM;
+  int strideA1 = isARow ? strideAM : strideAK;
+  int strideB0 = isBRow ? strideBN : strideBK;
+  int strideB1 = isBRow ? strideBK : strideBN;
+  int lda = isARow ? strideAM : strideAK;
+  int ldb = isBRow ? strideBK : strideBN;
+  int aPerPhase = aLayout.getPerPhase();
+  int aMaxPhase = aLayout.getMaxPhase();
+  int bPerPhase = bLayout.getPerPhase();
+  int bMaxPhase = bLayout.getMaxPhase();
+  int aNumPtr = 8;
+  int bNumPtr = 8;
+  int aVec = 2;
+  int bVec = 4;
+  int NK = aShape[isARow ? 1 : 0];
+
+  auto cShapePerCTA = getShapePerCTA(cLayout);
+  auto sizePerThread = getSizePerThread(dLayout);
+
+  Value _0 = i32_val(0);
+  Value _1 = i32_val(1);
+
+  Value mContig = _1;
+  Value nContig = _1;
+
+  Value offA0 = isARow ? _0 : mul(threadId, mContig);
+  Value offA1 = isARow ? mul(threadId, mContig) : _0;
+  SmallVector<Value> aOff(aNumPtr);
+  for (int i = 0; i < aNumPtr; ++i) {
+    aOff[i] = add(mul(offA0, i32_val(strideA0)), mul(offA1, i32_val(strideA1)));
+  }
+
+  Value offB0 = isBRow ? mul(threadId, nContig) : _0;
+  Value offB1 = isBRow ? _0 : mul(threadId, nContig);
+  SmallVector<Value> bOff(bNumPtr);
+  for (int i = 0; i < bNumPtr; ++i) {
+    bOff[i] = add(mul(offB0, i32_val(strideB0)), mul(offB1, i32_val(strideB1)));
+  }
+
+  Type f32PtrTy = ptr_ty(f32_ty);
+  SmallVector<Value> aPtrs(aNumPtr);
+  for (int i = 0; i < aNumPtr; ++i)
+    aPtrs[i] = gep(f32PtrTy, adaptor.a(), aOff[i]);
+
+  SmallVector<Value> bPtrs(bNumPtr);
+  for (int i = 0; i < bNumPtr; ++i)
+    bPtrs[i] = gep(f32PtrTy, adaptor.b(), bOff[i]);
+
+  std::map<std::pair<int, int>, Value> has, hbs;
+  // TODO initialize ret with zeros.
+  SmallVector<Value> ret(NK);
+  for (unsigned k = 0; k < NK; k++) {
+    int z = 0;
+    for (unsigned i = 0; i < cShape[order[1]]; i += cShapePerCTA[order[1]])
+      for (unsigned j = 0; j < cShape[order[0]]; j += cShapePerCTA[order[0]])
+        for (unsigned ii = 0; ii < sizePerThread[order[1]]; ++ii)
+          for (unsigned jj = 0; jj < sizePerThread[order[0]]; ++jj) {
+            unsigned m = order[0] == 1 ? i : j;
+            unsigned n = order[0] == 1 ? j : i;
+            unsigned mm = order[0] == 1 ? ii : jj;
+            unsigned nn = order[0] == 1 ? jj : ii;
+            if (!has.count({m + mm, k})) {
+              Value pa = gep(f32PtrTy, aPtrs[0],
+                             i32_val((m + mm) * strideAM + k * strideAK));
+              Value va = load(pa);
+              has[{m + mm, k}] = va;
+            }
+            if (!has.count({n + nn, k})) {
+              Value pb = gep(f32PtrTy, bPtrs[0],
+                             i32_val((n + nn) * strideBN + k * strideBK));
+              Value vb = load(pb);
+              has[{n + nn, k}] = vb;
+            }
+            ret[z++] = rewriter.create<LLVM::FMulAddOp>(
+                loc, has[{m + mm, k}], hbs[{n + nn, k}], ret[z]);
+          }
+  }
+
+  auto res = getStructFromElements(
+      loc, ret, rewriter,
+      struct_ty(SmallVector<Type>(ret.size(), ret[0].getType())));
+  rewriter.replaceOp(op, res);
+
+  return success();
+}
+
 /// ====================== mma codegen end ============================
 
 Value convertSplatLikeOpWithMmaLayout(const MmaEncodingAttr &layout,