[mlir][mesh] Add all-slice operation

This op is the inverse of all-gather. It is useful to have an explicit
concise representation instead of having a blob of slicing logic.

Add lowering for the op that slices from the tensor based on the in-group
process index.

Make resharding generate an all-slice instead of inserting the slicing logic
directly.

Author: sogartar

mlir/include/mlir/Dialect/Affine/Utils.h

@@ -15,12 +15,14 @@
 
 #include "mlir/Dialect/Affine/Analysis/AffineAnalysis.h"
 #include "mlir/Dialect/Affine/IR/AffineOps.h"
+#include "mlir/IR/OpDefinition.h"
 #include <optional>
 
 namespace mlir {
 class DominanceInfo;
 class Operation;
 class PostDominanceInfo;
+class ImplicitLocOpBuilder;
 
 namespace func {
 class FuncOp;
@@ -309,6 +311,11 @@ DivModValue getDivMod(OpBuilder &b, Location loc, Value lhs, Value rhs);
 FailureOr<SmallVector<Value>> delinearizeIndex(OpBuilder &b, Location loc,
                                                Value linearIndex,
                                                ArrayRef<Value> basis);
+// Generate IR that extracts the linear index from a multi-index according to
+// a basis/shape.
+OpFoldResult linearizeIndex(ArrayRef<OpFoldResult> multiIndex,
+                            ArrayRef<OpFoldResult> basis,
+                            ImplicitLocOpBuilder &builder);
 
 /// Ensure that all operations that could be executed after `start`
 /// (noninclusive) and prior to `memOp` (e.g. on a control flow/op path

mlir/include/mlir/Dialect/Arith/Utils/Utils.h

@@ -20,6 +20,7 @@
 #include "mlir/IR/Matchers.h"
 #include "mlir/IR/PatternMatch.h"
 #include "mlir/IR/Value.h"
+#include "llvm/ADT/ArrayRef.h"
 
 namespace mlir {
 
@@ -81,6 +82,22 @@ struct ArithBuilder {
   OpBuilder &b;
   Location loc;
 };
+
+namespace arith {
+
+// Build the product of a sequence.
+// If values = (v0, v1, ..., vn) than the returned
+// value is v0 * v1 * ... * vn.
+// All values must have the same type.
+//
+// The version without `resultType` must contain at least one element in values.
+// Then the result will have the same type as the elements in `values`.
+// If `values` is empty in the version with `resultType` returns 1 with type
+// `resultType`.
+Value createProduct(OpBuilder &builder, Location loc, ArrayRef<Value> values);
+Value createProduct(OpBuilder &builder, Location loc, ArrayRef<Value> values,
+                    Type resultType);
+} // namespace arith
 } // namespace mlir
 
 #endif // MLIR_DIALECT_ARITH_UTILS_UTILS_H

mlir/include/mlir/Dialect/Mesh/IR/MeshOps.h

@@ -92,6 +92,12 @@ int64_t collectiveProcessGroupSize(MeshAxesRange &&meshAxes,
   return res;
 }
 
+template <typename MeshAxesRange>
+int64_t collectiveProcessGroupSize(MeshAxesRange &&meshAxes, MeshOp mesh) {
+  return collectiveProcessGroupSize(std::forward<MeshAxesRange>(meshAxes),
+                                    mesh.getShape());
+}
+
 // Get the size of a sharded dimension.
 inline int64_t shardDimension(int64_t dimSize, int64_t shardCount) {
   if (ShapedType::isDynamic(dimSize) || ShapedType::isDynamic(shardCount))

mlir/include/mlir/Dialect/Mesh/IR/MeshOps.td

@@ -96,6 +96,7 @@ def Mesh_MeshShapeOp : Mesh_Op<"mesh_shape", [
 
   let builders = [
     OpBuilder<(ins "::mlir::mesh::MeshOp":$mesh)>,
+    OpBuilder<(ins "::mlir::mesh::MeshOp":$mesh, "ArrayRef<MeshAxis>":$axes)>,
     OpBuilder<(ins "StringRef":$mesh, "ArrayRef<MeshAxis>":$axes)>
   ];
 }
@@ -341,6 +342,68 @@ def Mesh_AllReduceOp : Mesh_CollectiveCommunicationOpBase<"all_reduce", [
   let hasCanonicalizer = 1;
 }
 
+def Mesh_AllSliceOp : Mesh_CollectiveCommunicationOpBase<"all_slice", [
+    Pure,
+    SameOperandsAndResultElementType,
+    SameOperandsAndResultRank
+  ]> {
+  let summary = "All-slice over a device mesh. This is the inverse of all-gather.";
+  let description = [{
+    Slice along the `slice_axis` tensor axis.
+    This operation can be thought of as the inverse of all-gather.
+    Technically, it is not required that all processes have the same input tensor.
+    Each process will slice a piece of its local tensor based on its in-group device index.
+    The operation does not communicate data between devices. 
+
+    Example:
+    ```mlir
+    mesh.mesh @mesh0(shape = 2x2)
+    ...
+    %1 = mesh.all_slice %0 on @mesh0 mesh_axes = [1] slice_axis = 1
+      : tensor<2x4xi8> -> tensor<2x2xi8>
+    ```
+    Input:
+    ```
+    +-------------+
+    |  1  2  5  6 | <- devices (0, 0) and (0, 1)
+    |  3  4  7  8 |
+    +-------------+
+    |  9 10 13 14 | <- devices (1, 0) and (1, 1)
+    | 11 12 15 16 |
+    +-------------+
+    ```
+    Result:
+    ```
+    gather tensor
+    axis 1
+    ------------>
+                     +-------+-------+
+    device (0, 0) -> |  1  2 |  5  6 | <- device (0, 1)
+                     |  3  4 |  7  8 |
+                     +-------+-------+
+    device (1, 0) -> |  9 10 | 13 14 | <- device (1, 1)
+                     | 11 12 | 15 16 |
+                     +-------+-------+
+    ```
+  }];
+  let arguments = !con(commonArgs, (ins
+    AnyNon0RankedTensor:$input,
+    IndexAttr:$slice_axis
+  ));
+  let results = (outs
+    AnyNon0RankedTensor:$result
+  );
+  let assemblyFormat = [{
+    $input `on` $mesh (`mesh_axes` `=` $mesh_axes^)? `slice_axis` `=` $slice_axis
+    attr-dict `:` type($input) `->` type($result)
+  }];
+  let hasCanonicalizer = 1;
+  let builders = [
+    OpBuilder<(ins "Value":$input, "MeshOp":$mesh, "ArrayRef<MeshAxis>":$meshAxes, "int64_t":$sliceAxis)>,
+    OpBuilder<(ins "Type":$result_type, "Value":$input, "StringRef":$mesh, "ArrayRef<MeshAxis>":$meshAxes, "int64_t":$sliceAxis)>
+  ];
+}
+
 def Mesh_AllToAllOp : Mesh_CollectiveCommunicationOpBase<"all_to_all", [
     Pure,
     SameOperandsAndResultElementType,

mlir/include/mlir/Dialect/Mesh/Transforms/Transforms.h

@@ -9,16 +9,33 @@
 #ifndef MLIR_DIALECT_MESH_TRANSFORMS_TRANSFORMS_H
 #define MLIR_DIALECT_MESH_TRANSFORMS_TRANSFORMS_H
 
+#include "mlir/Dialect/Mesh/IR/MeshOps.h"
+#include "mlir/IR/BuiltinTypes.h"
+#include "mlir/IR/Value.h"
+#include "mlir/Support/LLVM.h"
+
 namespace mlir {
 class RewritePatternSet;
 class SymbolTableCollection;
 class DialectRegistry;
+class ImplicitLocOpBuilder;
 namespace mesh {
 
-void processMultiIndexOpLoweringPopulatePatterns(
+void populateProcessMultiIndexOpLoweringPatterns(
+    RewritePatternSet &patterns, SymbolTableCollection &symbolTableCollection);
+void registerProcessMultiIndexOpLoweringDialects(DialectRegistry &registry);
+
+void populateAllSliceOpLoweringPatterns(
+    RewritePatternSet &patterns, SymbolTableCollection &symbolTableCollection);
+void registerAllSliceOpLoweringDialects(DialectRegistry &registry);
+
+void populateAllOpLoweringPatterns(
     RewritePatternSet &patterns, SymbolTableCollection &symbolTableCollection);
+void registerAllOpLoweringDialects(DialectRegistry &registry);
 
-void processMultiIndexOpLoweringRegisterDialects(DialectRegistry &registry);
+TypedValue<IndexType>
+createCollectiveProcessGroupSize(MeshOp mesh, ArrayRef<MeshAxis> axes,
+                                 ImplicitLocOpBuilder &builder);
 
 } // namespace mesh
 } // namespace mlir

mlir/include/mlir/IR/Builders.h

@@ -118,6 +118,9 @@ class Builder {
   // supports boolean, integer, and 16-/32-/64-bit float types, and vector or
   // ranked tensor of them. Returns null attribute otherwise.
   TypedAttr getZeroAttr(Type type);
+  // Returns a 1-valued attribute of the given `type`.
+  // Type constraints are the same as `getZeroAttr`.
+  TypedAttr getOneAttr(Type type);
 
   // Convenience methods for fixed types.
   FloatAttr getF16FloatAttr(float value);

mlir/lib/Dialect/Affine/Utils/Utils.cpp

@@ -20,9 +20,11 @@
 #include "mlir/Dialect/Arith/Utils/Utils.h"
 #include "mlir/Dialect/Func/IR/FuncOps.h"
 #include "mlir/Dialect/MemRef/IR/MemRef.h"
+#include "mlir/Dialect/Utils/IndexingUtils.h"
 #include "mlir/IR/AffineExprVisitor.h"
 #include "mlir/IR/Dominance.h"
 #include "mlir/IR/IRMapping.h"
+#include "mlir/IR/ImplicitLocOpBuilder.h"
 #include "mlir/IR/IntegerSet.h"
 #include "mlir/Transforms/GreedyPatternRewriteDriver.h"
 #include <optional>
@@ -1869,3 +1871,27 @@ mlir::affine::delinearizeIndex(OpBuilder &b, Location loc, Value linearIndex,
   results.push_back(residual);
   return results;
 }
+
+OpFoldResult mlir::affine::linearizeIndex(ArrayRef<OpFoldResult> multiIndex,
+                                          ArrayRef<OpFoldResult> basis,
+                                          ImplicitLocOpBuilder &builder) {
+  assert(multiIndex.size() == basis.size());
+  SmallVector<AffineExpr> basisAffine;
+  for (size_t i = 0; i < basis.size(); ++i) {
+    basisAffine.push_back(getAffineSymbolExpr(i, builder.getContext()));
+  }
+
+  SmallVector<AffineExpr> stridesAffine = computeStrides(basisAffine);
+  SmallVector<OpFoldResult> strides;
+  strides.reserve(stridesAffine.size());
+  llvm::transform(stridesAffine, std::back_inserter(strides),
+                  [&builder, &basis](AffineExpr strideExpr) {
+                    return affine::makeComposedFoldedAffineApply(
+                        builder, builder.getLoc(), strideExpr, basis);
+                  });
+
+  auto &&[linearIndexExpr, multiIndexAndStrides] = computeLinearIndex(
+      OpFoldResult(builder.getIndexAttr(0)), strides, multiIndex);
+  return affine::makeComposedFoldedAffineApply(
+      builder, builder.getLoc(), linearIndexExpr, multiIndexAndStrides);
+}

mlir/lib/Dialect/Arith/Utils/Utils.cpp

@@ -15,6 +15,7 @@
 #include "mlir/Dialect/Complex/IR/Complex.h"
 #include "mlir/IR/ImplicitLocOpBuilder.h"
 #include "llvm/ADT/SmallBitVector.h"
+#include <numeric>
 
 using namespace mlir;
 
@@ -262,3 +263,21 @@ Value ArithBuilder::slt(Value lhs, Value rhs) {
 Value ArithBuilder::select(Value cmp, Value lhs, Value rhs) {
   return b.create<arith::SelectOp>(loc, cmp, lhs, rhs);
 }
+
+namespace mlir::arith {
+
+Value createProduct(OpBuilder &builder, Location loc, ArrayRef<Value> values) {
+  return createProduct(builder, loc, values, values.front().getType());
+}
+
+Value createProduct(OpBuilder &builder, Location loc, ArrayRef<Value> values,
+                    Type resultType) {
+  Value one = builder.create<ConstantOp>(loc, resultType,
+                                         builder.getOneAttr(resultType));
+  ArithBuilder arithBuilder(builder, loc);
+  return std::accumulate(
+      values.begin(), values.end(), one,
+      [&arithBuilder](Value acc, Value v) { return arithBuilder.mul(acc, v); });
+}
+
+} // namespace mlir::arith