[Mlir-commits] [mlir] [MLIR][XeGPU] Adding XeGPU 2d block operators (PR #84692)

[Mehdi Amini]

================
@@ -23,4 +26,227 @@ class XeGPU_Op<string mnemonic, list<Trait> traits = []>:
           Op<XeGPU_Dialect, mnemonic, traits>;
 
 
+def XeGPU_CreateNdDescOp: XeGPU_Op<"create_nd_tdesc", [Pure, ViewLikeOpInterface, 
+                        AttrSizedOperandSegments, OffsetSizeAndStrideOpInterface]> {
+
+  let summary = "create nd tensor descriptor operation";
+  let description = [{
+    The "create_nd_tdesc" operation creates a TensorDescType which represents
+    a sub-view of a 2D memory region (It can be extended to support n-D memory
+    region if needed in future). Elements in the subview continuous in each 
+    dimention. It encodes the following important information for supporting 
+    Intel hardware features:
+
+    * source: an object representing (starting address/pointer of) a 2D memory region. 
+        It can be either a 2D memref object, or simply a pointer represented by uint64_t type.
+        for the later case, the shape and layout information of the 2D memory region should 
+        be explicitly passed via `dynamic_shape` and `dynamic_strides` parameters.
+    * offsets: two index values represents offsets from the "source" at the each dimension 
+        at which the subview of the target memory will be created. It is encoded via two
+        variables, including "dynamic_offsets" and "static_offsets", such that it can
+        accept various forms, such as, operands (e.g., [%c0, %c]) and attributes (e.g., [2, 4])).
+    * shape: the shape information of the memory region pointed by the "source".  It is 
+        typically encoded via the MemRefType of the source, e.g., memref<4096x4096xf16>. 
+        But if "source" is simply a pointer represented as uint64_t type, or a memref 
+        type without shape information e.g., memref<?x?xf16>, the shape information has 
+        to be explicitly passed via the "dynamic_shape" argument. Currently "dynamic_shape" 
+        only accepts operands(e.g., [%c4096, %c4096]), not attributes(e.g., [4096, 4096]).
+    * strides: the strides of the memory region pointed by the "source". Similar to shape, 
+        it is typically encoded via the MemRefType of the source too. But if "source" is 
+        simply a pointer represented as uint64_t type, or a memref type without shape 
+        information e.g., memref<?x?xf16>, the strides information has to be explicitly 
+        passed via the "dynamic_strides" argument. And it currently only accepts operands two.
+
+    Example 1 (suppose the tensor shape inferred by the compiler is 8x16):
+    %0 = memref.alloc() : memref<1024x1024xf32>
+    %c0 = arith.constant 0 : index
+    %c1 = arith.constant 1 : index
+    %1 = xegpu.create_nd_tdesc %0[%c0, %c0]: memref<1024x1024xf32> -> TensorDesc<8x16xf32>
+
+    Example 2 (suppose the tensor shape inferred by the compiler is 8x16):
+    %0 = memref.alloc(%h, %w) : memref<?x?xf32>
+    %c0 = arith.constant 0 : index
+    %c1 = arith.constant 1 : index
+    %1 = xegpu.create_nd_tdesc %0[%c0, %c0], [%h, %w], [%w, %c1]: memref<?x?xf32> -> TensorDesc<8x16xf32>
+
+    Example 3 (suppose the tensor shape inferred by the compiler is 8x16):
+    %0 = ... : ui64
+    %c0 = arith.constant 0 : index
+    %c1 = arith.constant 1 : index
+    %1 = xegpu.create_nd_tdesc %0[%c0, %c0], [%h, %w], [%w, %c1]: ui64 -> TensorDesc<8x16xf32>
+  }];
+
+  let arguments = (ins 
+    XeGPU_BaseAddrType: $source, 
+    Variadic<Index>: $offsets, 
+    Variadic<Index>: $shape, 
+    Variadic<Index>: $strides,
+    DenseI64ArrayAttr: $static_offsets
+  );
+  let results = (outs XeGPU_TensorDesc: $TensorDesc);
+
+  let assemblyFormat = [{
+    $source ``
+    custom<DynamicIndexList>($offsets, $static_offsets)
+    (`,` `[` $shape^ `]` `,` `[` $strides `]`)?
+    attr-dict `:` type($source) `->` qualified(type($TensorDesc))
+  }];
+
+  let hasVerifier = 1;
+
+  let builders = [
+    OpBuilder<(ins "Type": $tdesc, "TypedValue<MemRefType>": $source, 
+                   "llvm::ArrayRef<OpFoldResult>": $offsets)>,
+
+    OpBuilder<(ins "Type": $tdesc, "TypedValue<IntegerType> ": $source, 
+                   "llvm::ArrayRef<OpFoldResult>": $offsets,
+                   "ValueRange": $shape, "ValueRange": $stride)>
+  ];
+
+  let extraClassDeclaration = [{
+    /// Returns the type of the source memref operand.
+    Type getSourceType() {
+      return getSource().getType();
+    }
+
+    /// Returns the type of the result TensorDesc.
+    xegpu::TensorDescType getType() {
+      return getTensorDesc().getType();
+    }
+
+    /// Return the element type of the TensorDesc
+    Type getElementType() {
+      return getType().getElementType();
+    }
+
+    /// Return the shape of the TensorDesc
+    llvm::ArrayRef<int64_t> getTensorDescShape() {
+      return getType().getShape();
+    }
+
+    /// wrapper for matching with OffsetSizeAndStrideOpInterface
+    OperandRange getSizes() {
+      return getShape();
+    }
+
+    /// wrapper for matching with OffsetSizeAndStrideOpInterface
+    /// If source is IntegerType and `shape` is filled, it will 
+    /// return an array of ShapedType::kDynamic representing dynamic 
+    /// shape encoded in the `shape` argument will be used. Presence
+    /// of `shape` overides static shape from source memref type.
+    SmallVector<int64_t> getStaticSizes() {
+      if (getSourceType().isa<IntegerType>() || getShape().size()) {
+        auto dims = getMixedOffsets().size();
+        return SmallVector<int64_t>(dims, ShapedType::kDynamic);
+      }
+      auto memrefType = getSourceType().dyn_cast<MemRefType>();
+      return SmallVector<int64_t>(memrefType.getShape());
+    }
+
+    /// wrapper for matching with OffsetSizeAndStrideOpInterface
+    /// If source is IntegerType or `strides` is filled, it will 
+    /// return an array of ShapedType::kDynamic representing dynamic 
+    /// strides encoded in the `strides` argument will be used. Presence
+    /// of `strides` overides static strides from source memref type.
+    SmallVector<int64_t> getStaticStrides() {
+      if (getSourceType().isa<IntegerType>() || getStrides().size()) {
+        auto dims = getMixedOffsets().size();
+        return SmallVector<int64_t>(dims, ShapedType::kDynamic);
+      }
+      auto memrefType = getSourceType().dyn_cast<MemRefType>();
+      auto [strides, offset] = getStridesAndOffset(memrefType);
+      return strides;
+    }
+
+    /// Return the expected rank of each of the`static_offsets`, 
+    /// `static_shape` and `static_strides` attributes.
+    std::array<unsigned, 3> getArrayAttrMaxRanks() {
+      unsigned rank;
+      if (auto ty = getSourceType().dyn_cast<MemRefType>()) {
+        rank = ty.getRank();
+      } else {
+        rank = (unsigned)getMixedOffsets().size();
+      }
+      return {rank, rank, rank};
+    }
+    
+    /// Return the number of leading operands before the `offsets`, 
+    /// `shape` and `strides` operands.
+    static unsigned getOffsetSizeAndStrideStartOperandIndex() { return 1; }
+
+    mlir::Value getViewSource() { return getSource(); }
+  }];
+}
+
+def XeGPU_PrefetchNdOp : XeGPU_Op<"prefetch_nd", []> {
+  let summary = "prefetches a nD block to cache";
+  let arguments = (ins XeGPU_TensorDesc: $TensorDesc,
+                       OptionalAttr<XeGPU_CacheHintAttr>: $l1_hint,
+                       OptionalAttr<XeGPU_CacheHintAttr>: $l2_hint,
+                       OptionalAttr<XeGPU_CacheHintAttr>: $l3_hint);
+
+  // Format: xegpu.prefetch_nd %tdesc {l1_hint = #xegpu.cache_hint<cached>, 
+  //                                   l2_hint = #xegpu.cache_hint<cached>, 
+  //                                   l3_hint = #xegpu.cache_hint<cached>}
+  //         : !xegpu.tensor_desc<8x16xf16>
+  let assemblyFormat = "$TensorDesc attr-dict `:` qualified(type($TensorDesc))";
----------------
joker-eph wrote:

Can you always split `prop-dict` out of `attr-dict`? We're trying to deprecate merging the two (it's a slow progress...)

https://github.com/llvm/llvm-project/pull/84692