Merge OpenAI Triton commit 0173f75

include/triton/Tools/LayoutUtils.h

@@ -147,6 +147,41 @@ std::pair<int, ColumnAction>
 largestVectorisation(MLIRContext *ctx, const LinearLayout &cvt, int bitwidth,
                      std::optional<int> maybeMaxVecElems = std::nullopt);
 
+// Close cousin of doing zerosLike(tile) * divideLeft(cvt, tile)
+// This one is a tad more general in the sense that it allows to divide
+//  cvt:
+// - register=1 -> (0, 1)
+//   register=2 -> (8, 0)
+//   register=4 -> (0, 8)
+//   register=8 -> (0, 16)
+//   register=16 -> (0, 32)
+//   register=32 -> (0, 64)
+//   register=64 -> (16, 0)
+// - lane=1 -> (0, 2)
+//   lane=2 -> (0, 4)
+//   lane=4 -> (1, 0)
+//   lane=8 -> (2, 0)
+//   lane=16 -> (4, 0)
+// - warp=1 -> (32, 0)
+//   warp=2 -> (64, 0)
+// - block is a size 1 dimension
+// where out dims are: [row (size 128), col (size 128)]
+// tile:
+//  - register=1 -> (0, 1)
+//    register=2 -> (8, 0)
+//  - lane=1 -> (0, 2)
+//    lane=2 -> (0, 4)
+//    lane=4 -> (1, 0)
+//    lane=8 -> (2, 0)
+//    lane=16 -> (4, 0)
+//  - warp=1 -> (32, 0)
+//    warp=2 -> (64, 0)
+// where out dims are: [row (size 128), col (size 8)]
+// which would not be possible to lower via the divideLeft approach as we
+// cannot divide by the tile given the `register=64 -> (16, 0)` basis.
+std::optional<LinearLayout> getReps(const LinearLayout &cvt,
+                                    const LinearLayout &tile);
+
 } // namespace mlir::triton
 
 #endif // TRITON_TOOLS_LAYOUTUTILS_H

include/triton/Tools/Sys/GetEnv.hpp

@@ -43,6 +43,7 @@ inline const std::set<std::string> CACHE_INVALIDATING_ENV_VARS = {
     "ALLOW_LHS_TMEM_LAYOUT_CONVERSION",
     "TRITON_F32_DEFAULT",
     "TRITON_PREFER_TMEM_16x256_LAYOUT",
+    "TRITON_ENABLE_EXPERIMENTAL_CONSAN",
     "TRITON_INTEL_AGGRESSIVE_DPAS_REUSE",
     "TRITON_INTEL_ENABLE_BLOCK_IO_ALL_LAYOUTS",
     "TRITON_INTEL_ENABLE_DPAS_FOR_WARP_SIZE_32",

lib/Dialect/TritonGPU/IR/LinearLayoutConversions.cpp

@@ -477,23 +477,87 @@ AMDMfmaEncodingAttr::toLinearLayout(ArrayRef<int64_t> shape) const {
   return combineCtaCgaWithShape(tileLayout, getCTALayout(), shape);
 }
 
+LinearLayout chooseLLDsReadB64TrLayout(Attribute enc, ArrayRef<int64_t> shape,
+                                       int32_t elemBitWidth) {
+  using BaseTy = std::vector<std::vector<int32_t>>;
+  // This function will derive the layout for the ds_read_b64_tr instruction
+  // based on the input layout (LL/DotLayout/...)
+  // The ds_read_b64_tr works on 64 bits per lane and in groups of 16 lanes.
+
+  // Using M-continuous 16-bit input tensor A as an example. Each lane will
+  // load 4 consecutive elements (64-bit in total) along M. There are 4
+  // consecutive lanes in total along M. Then the loaded elements are exchanged
+  // withthin the MxK=16x4 "base unit".
+  //        K0  K1  K2  K3
+  //      +---+---+---+---+
+  //  M0  |   |   |   |   |       M0, K[0-3]:  T0
+  //  M1  | T | T | T | T |       M1, K[0-3]:  T1
+  //  M2  | 0 | 4 | 8 |12 |       M2, K[0-3]:  T2
+  //  M3  |   |   |   |   |       M3, K[0-3]:  T3
+  //      +---+---+---+---+
+  //  M4  |   |   |   |   |       M4, K[0-3]:  T4
+  //  M5  | T | T | T | T |       M5, K[0-3]:  T5
+  //  M6  | 1 | 5 | 9 |13 |       M6, K[0-3]:  T6
+  //  M7  |   |   |   |   |       M7, K[0-3]:  T7
+  //      +---+---+---+---+  ==>
+  //  M8  |   |   |   |   |       M8, K[0-3]:  T8
+  //  M9  | T | T | T | T |       M9, K[0-3]:  T9
+  // M10  | 2 | 6 |10 |14 |      M10, K[0-3]: T10
+  // M11  |   |   |   |   |      M11, K[0-3]: T11
+  //      +---+---+---+---+
+  // M12  |   |   |   |   |      M12, K[0-3]: T12
+  // M13  | T | T | T | T |      M13, K[0-3]: T13
+  // M14  | 3 | 7 |11 |15 |      M14, K[0-3]: T14
+  // M15  |   |   |   |   |      M15, K[0-3]: T15
+  //      +---+---+---+---+
+
+  // Given the layout represented by `enc` and shape, we can derive the layout
+  // that ds_read_b64_tr need to have in order to perform a vectorized load of
+  // the elements. This can be done by rearranging the inner 4x16 element base
+  // unit in the LL by rearranging the first numReg register bases and the
+  // first numLane lane bases.
+  auto rotatePrefixes = [](BaseTy &regBase, std::size_t numReg,
+                           BaseTy &laneBase, std::size_t numLane) {
+    // Concatenate prefixes of the two vectors. Lane first and then regs.
+    // C D E F | A B
+    // Then copy over numReg to the regBase and numLane to laneBase
+    // C D | E F A B
+    BaseTy baseUnit(laneBase.begin(), laneBase.begin() + numLane);
+    llvm::append_range(
+        baseUnit, llvm::make_range(regBase.begin(), regBase.begin() + numReg));
+
+    std::copy(baseUnit.begin(), baseUnit.begin() + numReg, regBase.begin());
+    std::copy(baseUnit.begin() + numReg, baseUnit.end(), laneBase.begin());
+  };
+
+  auto ctx = enc.getContext();
+  assert(elemBitWidth == 8 || elemBitWidth == 16);
+  // Get how many reg bases the ds_read_tr tile spans
+  unsigned numRegBases = llvm::Log2_32(64 / elemBitWidth);
+  // 4 lane bases describe 16 lanes.
+  unsigned numLaneBases = 4;
+
+  auto ldsTransLayout = triton::gpu::toLinearLayout(shape, enc);
+  auto bases = ldsTransLayout.getBases();
+  auto kRegister = S("register");
+  auto kLane = S("lane");
+  rotatePrefixes(bases[kRegister], numRegBases, bases[kLane], numLaneBases);
+
+  return LinearLayout(bases, ldsTransLayout.getOutDims(), false);
+}
+
 LinearLayout chooseDotDsReadB64TrLayout(DotOperandEncodingAttr dotMfmaLayout,
                                         ArrayRef<int64_t> shape,
                                         int32_t elemBitWidth) {
   auto mfmaLayout = llvm::cast<AMDMfmaEncodingAttr>(dotMfmaLayout.getParent());
   auto mDim = mfmaLayout.getInstrShape()[0];
   assert(mDim == 16 || mDim == 32);
 
-  bool isFP4 = false;
-  if (elemBitWidth == 4) {
-    // When doing ds_read_tr4 we actually write the LL as if it were on i8
-    // elements this is becasue LL needs to be described for the i8 tensor
-    // elements.
-    elemBitWidth = 8;
-    isFP4 = true;
-  }
-
-  assert(elemBitWidth == 16 || elemBitWidth == 8);
+  assert(elemBitWidth == 4);
+  // When doing ds_read_tr4 we actually write the LL as if it were on i8
+  // elements this is becasue LL needs to be described for the i8 tensor
+  // elements.
+  elemBitWidth = 8;
 
   auto rank = shape.size();
   bool hasBatchDim = rank == 3;
@@ -520,143 +584,39 @@ LinearLayout chooseDotDsReadB64TrLayout(DotOperandEncodingAttr dotMfmaLayout,
 
   std::vector<std::vector<int32_t>> registerBase;
   std::vector<std::vector<int32_t>> laneBase;
-  auto populateFP4LL = [&registerBase, &laneBase](int kSize, int mDim) {
-    const bool isMfma32 = (mDim == 32);
-    // ds_read_b64_tr4 operates on FP4 values swapping the packing of them. Look
-    // at i8 values for the ownership of register/lane since it's the data type
-    // of the tensor. Register dimension: what i8 in the tile are held by thread
-    // 0? Lane dimension: what i8 in the tile are held in register 0 of each
-    // thread?
-    registerBase.push_back({1, 0});
-    registerBase.push_back({2, 0});
-    registerBase.push_back({4, 0});
-    registerBase.push_back({0, 16});
-
-    // If more than one tile needs to be loaded, populate registerBase
-    // dimension for the other tiles
-    const int kTileSize = isMfma32 ? 64 : 128;
-    for (int reg = kTileSize; reg < kSize; reg *= 2) {
-      registerBase.push_back({0, reg});
-    }
-
-    // When mDim == 16 we have 16x128 mfma, otherwise it's 16x64
-    // The LL for the two is different
-    laneBase.push_back({0, 1});
-    laneBase.push_back({0, 2});
-    laneBase.push_back({0, 4});
-    laneBase.push_back({0, 8});
-    if (mDim == 16) {
-      laneBase.push_back({0, 32});
-      laneBase.push_back({0, 64});
-    } else {
-      assert(mDim == 32);
-      laneBase.push_back({8, 0});
-      laneBase.push_back({0, 32});
-    }
-  };
-  auto populateLL = [&registerBase, &laneBase](int elemBitWidth, int kSize,
-                                               int kWidthDot, int mDim) {
-    // Number of bits loaded by an LDS read. ds_read_tr primarily supports
-    // 64-bit loads for most element sizes (16b, 8b, 4b).
-    const int32_t ldsReadWidth = 64;
-    int32_t kWidthTransRead = ldsReadWidth / elemBitWidth;
-    const int elemByteWidth = elemBitWidth / 8;
-    const bool isMfma32 = (mDim == 32);
-
-    // For ds_read_b64_tr_* instructions, each thread accesses 64 bits (8 bytes)
-    // of data. The smallest unit for transposition is a
-    // [non-K, K] = {16, kWidthTransRead} sub-tile of elements,
-    // where each thread reads kWidthTransRead elements along the non-K
-    // dimension. Due to the transposition mechanism, each thread ends up with
-    // kWidthTransRead elements along the K dimension.
-    //
-    // The MFMA selection logic prioritizes double-rate MFMA instructions
-    // whenever possible:
-    //
-    // - For MFMA operations where M = N = 16, when blockK > k, mfma16x16x2*k
-    //   is selected; otherwise (blockK ≤ k), mfma16x16xk remains the choice.
-    //
-    // - For MFMA operations where M = N = 32, when blockK > k, mfma32x32x2*k is
-    //   selected; otherwise (blockK ≤ k), mfma32x32xk is used.
-    //
-    // NOTE: For fp8 and fp4, "double-rate" results in 4*k since scaled MFMA
-    // instructions are used.
-    //
-    // In "double-rate" MFMA instructions, each thread holds 2*kWidthTransRead
-    // elements along the K dimension:
-    // - The first kWidthTransRead elements belong to the first sub-tile.
-    // - The next kWidthTransRead elements belong to the second sub-tile.
-    //
-    // These elements are then grouped into larger tiles, each consisting of
-    // 8 {16, kWidthTransRead} sub-tiles. These tiles correspond to the data
-    // for one MFMA instruction. The shape of these tiles depends on the MFMA
-    // instruction used.
-    //
-    // For single-rate MFMA instructions, each thread holds kWidthTransRead
-    // elements along the K dimension. This means that the larger tile
-    // (corresponding to one MFMA instruction) consists of 4 {16,
-    // kWidthTransRead} sub-tiles.
-
-    // Populate register base for first subtile
-    for (int i = 1; i < kWidthTransRead; i *= 2) {
-      registerBase.push_back({i, 0});
-    }
-
-    const int threadsPerSubtileNonK = 16 / kWidthTransRead;
-    const int threadsPerSubtileK = kWidthTransRead;
-
-    // Populate lane base for first subtile
-    for (int i = 1; i < threadsPerSubtileNonK; i *= 2) {
-      laneBase.push_back({i * kWidthTransRead, 0});
-    }
-    for (int i = 1; i < threadsPerSubtileK; i *= 2) {
-      laneBase.push_back({0, i});
-    }
-
-    // Function to extend register base for multiple tiles K dim.
-    auto extendRegisterBaseForKDim = [&](int kTileSize,
-                                         int numSubtilesPerTile) {
-      const int regsPerTile = kWidthTransRead * numSubtilesPerTile;
-      int totalRegs = (kSize / kTileSize) * regsPerTile;
-
-      for (int reg = regsPerTile; reg < totalRegs; reg *= 2) {
-        registerBase.push_back({0, (reg / regsPerTile) * kTileSize});
-      }
-    };
-
-    // kDoubleTileSize is the k dimension of a tile when double rated
-    // mfma instructions are used.
-    const int kDoubleTileSize =
-        isMfma32 ? 32 / elemByteWidth : 64 / elemByteWidth;
-    // kTileSize is the actually k dimention of a tile, which is
-    // determined by kWidthDot.
-    const int kTileSize = kWidthDot * 64 / mDim;
-    // We use kDoubleTileSize as a reference to check whether the given
-    // kWidthDot leads to double or single sub-tiles in each tile.
-    const int numSubtilesPerTile = (kTileSize == kDoubleTileSize) ? 2 : 1;
-
-    // Extend register base for large K sizes.
-    if (numSubtilesPerTile == 2)
-      registerBase.push_back({0, threadsPerSubtileK}); // Second subtile
-
-    extendRegisterBaseForKDim(kTileSize, numSubtilesPerTile);
-
-    // Extend lane base based on MFMA size.
-    std::vector<std::vector<int32_t>> laneBaseExt;
-
-    if (isMfma32) {
-      laneBaseExt = {{16, 0}, {0, numSubtilesPerTile * threadsPerSubtileK}};
-    } else {
-      laneBaseExt = {{0, numSubtilesPerTile * threadsPerSubtileK},
-                     {0, 2 * numSubtilesPerTile * threadsPerSubtileK}};
-    }
-    laneBase.insert(laneBase.end(), laneBaseExt.begin(), laneBaseExt.end());
-  };
 
-  if (isFP4)
-    populateFP4LL(kSize, mDim);
-  else
-    populateLL(elemBitWidth, kSize, kWidthDot, mDim);
+  const bool isMfma32 = (mDim == 32);
+  // ds_read_b64_tr4 operates on FP4 values swapping the packing of them. Look
+  // at i8 values for the ownership of register/lane since it's the data type
+  // of the tensor. Register dimension: what i8 in the tile are held by thread
+  // 0? Lane dimension: what i8 in the tile are held in register 0 of each
+  // thread?
+  registerBase.push_back({1, 0});
+  registerBase.push_back({2, 0});
+  registerBase.push_back({4, 0});
+  registerBase.push_back({0, 16});
+
+  // If more than one tile needs to be loaded, populate registerBase
+  // dimension for the other tiles
+  const int kTileSize = isMfma32 ? 64 : 128;
+  for (int reg = kTileSize; reg < kSize; reg *= 2) {
+    registerBase.push_back({0, reg});
+  }
+
+  // When mDim == 16 we have 16x128 mfma, otherwise it's 16x64
+  // The LL for the two is different
+  laneBase.push_back({0, 1});
+  laneBase.push_back({0, 2});
+  laneBase.push_back({0, 4});
+  laneBase.push_back({0, 8});
+  if (mDim == 16) {
+    laneBase.push_back({0, 32});
+    laneBase.push_back({0, 64});
+  } else {
+    assert(mDim == 32);
+    laneBase.push_back({8, 0});
+    laneBase.push_back({0, 32});
+  }
 
   // Base vectors above are defined in a fixed order [non-k-dim, k-dim].
   // To assign them to actual matrix dimensions we associate with register
@@ -1444,8 +1404,12 @@ LinearLayout chooseShemLayoutForRegToRegConversion(
 
 LinearLayout chooseDsReadB64TrLayout(Attribute enc, ArrayRef<int64_t> shape,
                                      int32_t elemBitWidth) {
-  auto dot = cast<DotOperandEncodingAttr>(enc);
-  return chooseDotDsReadB64TrLayout(dot, shape, elemBitWidth);
+  if (elemBitWidth == 4) {
+    auto dot = cast<DotOperandEncodingAttr>(enc);
+    return chooseDotDsReadB64TrLayout(dot, shape, elemBitWidth);
+  } else {
+    return chooseLLDsReadB64TrLayout(enc, shape, elemBitWidth);
+  }
 }
 
 LinearLayout chooseScaledWmmaScaleLayout(