[mlir][arith] Add andi, ori, and xori support to WIE

[kuhar]

Fix naming

[kuhar]

Fix formatting in tests

[kuhar]

Drop redundant extractions and insertions

[kuhar]

Switch back to the elementwise implementation. I checked some real inputs and this is cleaner because sequences of i64 ops will be kept as ops over 2 scalars.

[ThomasRaoux]

LGTM

[Mogball]

mlir/lib/Dialect/Arith/Transforms/EmulateWideInt.cpp

308

[kuhar]

mlir/lib/Dialect/Arith/Transforms/EmulateWideInt.cpp

308

This won't work because notifyMatchFailure returns LogicalResult. I think we would have to pass in a callback that appends to the Diagnostic

[jpienaar]

mlir/lib/Dialect/Arith/Transforms/EmulateWideInt.cpp

308

I think here formatv would probably be easiest.

mlir/lib/Dialect/Arith/Transforms/EmulateWideInt.cpp

matchAndRewrite(arith::AddIOp op, OpAdaptor adaptor,
     Value resultVec =
         constructResultVector(rewriter, loc, newTy, {lowSum.getSum(), high});
     rewriter.replaceOp(op, resultVec);
     return success();
   }
 };
 
 //===----------------------------------------------------------------------===//
+// ConvertBitwiseBinary
+//===----------------------------------------------------------------------===//
+
+/// Conversion pattern template for bitwise binary ops, e.g., `arith.andi`.
+template <typename BinaryOp>
+struct ConvertBitwiseBinary final : OpConversionPattern<BinaryOp> {
+  using OpConversionPattern<BinaryOp>::OpConversionPattern;
+  using OpAdaptor = typename OpConversionPattern<BinaryOp>::OpAdaptor;
+
+  LogicalResult
+  matchAndRewrite(BinaryOp op, OpAdaptor adaptor,
+                  ConversionPatternRewriter &rewriter) const override {
+    Location loc = op->getLoc();
+    auto newTy = this->getTypeConverter()
+                     ->convertType(op.getType())
+                     .template dyn_cast_or_null<VectorType>();
+    if (!newTy)
+      return rewriter.notifyMatchFailure(loc, "unsupported type");
+
+    rewriter.replaceOpWithNewOp<BinaryOp>(op, adaptor.getLhs(),
+                                          adaptor.getRhs());
+    return success();
+  }
+};
+
+//===----------------------------------------------------------------------===//
 // ConvertMulI
 //===----------------------------------------------------------------------===//
 
 struct ConvertMulI final : OpConversionPattern<arith::MulIOp> {
   using OpConversionPattern::OpConversionPattern;
 
   LogicalResult
   matchAndRewrite(arith::MulIOp op, OpAdaptor adaptor,
void arith::populateWideIntEmulationPatterns(
   populateReturnOpTypeConversionPattern(patterns, typeConverter);
 
   // Populate `arith.*` conversion patterns.
   patterns.add<
       // Misc ops.
       ConvertConstant, ConvertVectorPrint,
       // Binary ops.
       ConvertAddI, ConvertMulI, ConvertShRUI,
+      // Bitwise binary ops.
+      ConvertBitwiseBinary<arith::AndIOp>, ConvertBitwiseBinary<arith::OrIOp>,
+      ConvertBitwiseBinary<arith::XOrIOp>,
       // Extension and truncation ops.
       ConvertExtSI, ConvertExtUI, ConvertTruncI>(typeConverter,
                                                  patterns.getContext());
 }

mlir/test/Dialect/Arith/emulate-wide-int.mlir

 
 // CHECK-LABEL: func.func @shrui_vector
 // CHECK-SAME:    ({{%.+}}: vector<3x2xi32>, {{%.+}}: vector<3x2xi32>) -> vector<3x2xi32>
 // CHECK:       return {{%.+}} : vector<3x2xi32>
 func.func @shrui_vector(%a : vector<3xi64>, %b : vector<3xi64>) -> vector<3xi64> {
     %m = arith.shrui %a, %b : vector<3xi64>
     return %m : vector<3xi64>
 }
+
+// CHECK-LABEL: func @andi_scalar_a_b
+// CHECK-SAME:    ([[ARG0:%.+]]: vector<2xi32>, [[ARG1:%.+]]: vector<2xi32>) -> vector<2xi32>
+// CHECK-NEXT:    [[RES:%.+]]   = arith.andi [[ARG0]], [[ARG1]] : vector<2xi32>
+// CHECK-NEXT:    return [[RES]] : vector<2xi32>
+func.func @andi_scalar_a_b(%a : i64, %b : i64) -> i64 {
+    %x = arith.andi %a, %b : i64
+    return %x : i64
+}
+
+// CHECK-LABEL: func @andi_vector_a_b
+// CHECK-SAME:   ([[ARG0:%.+]]: vector<3x2xi32>, [[ARG1:%.+]]: vector<3x2xi32>) -> vector<3x2xi32>
+// CHECK-NEXT:    [[RES:%.+]] = arith.andi [[ARG0]], [[ARG1]] : vector<3x2xi32>
+// CHECK:         return [[RES]] : vector<3x2xi32>
+func.func @andi_vector_a_b(%a : vector<3xi64>, %b : vector<3xi64>) -> vector<3xi64> {
+    %x = arith.andi %a, %b : vector<3xi64>
+    return %x : vector<3xi64>
+}
+
+// CHECK-LABEL: func @ori_scalar_a_b
+// CHECK-SAME:    ([[ARG0:%.+]]: vector<2xi32>, [[ARG1:%.+]]: vector<2xi32>) -> vector<2xi32>
+// CHECK-NEXT:    [[RES:%.+]] = arith.ori [[ARG0]], [[ARG1]] : vector<2xi32>
+// CHECK-NEXT:    return [[RES]] : vector<2xi32>
+func.func @ori_scalar_a_b(%a : i64, %b : i64) -> i64 {
+    %x = arith.ori %a, %b : i64
+    return %x : i64
+}
+
+// CHECK-LABEL: func @ori_vector_a_b
+// CHECK-SAME:   ([[ARG0:%.+]]: vector<3x2xi32>, [[ARG1:%.+]]: vector<3x2xi32>) -> vector<3x2xi32>
+// CHECK-NEXT:    [[RES:%.+]] = arith.ori [[ARG0]], [[ARG1]] : vector<3x2xi32>
+// CHECK:         return [[RES]] : vector<3x2xi32>
+func.func @ori_vector_a_b(%a : vector<3xi64>, %b : vector<3xi64>) -> vector<3xi64> {
+    %x = arith.ori %a, %b : vector<3xi64>
+    return %x : vector<3xi64>
+}
+
+// CHECK-LABEL: func @xori_scalar_a_b
+// CHECK-SAME:    ([[ARG0:%.+]]: vector<2xi32>, [[ARG1:%.+]]: vector<2xi32>) -> vector<2xi32>
+// CHECK-NEXT:    [[RES:%.+]] = arith.xori [[ARG0]], [[ARG1]] : vector<2xi32>
+// CHECK-NEXT:    return [[RES]] : vector<2xi32>
+func.func @xori_scalar_a_b(%a : i64, %b : i64) -> i64 {
+    %x = arith.xori %a, %b : i64
+    return %x : i64
+}
+
+// CHECK-LABEL: func @xori_vector_a_b
+// CHECK-SAME:   ([[ARG0:%.+]]: vector<3x2xi32>, [[ARG1:%.+]]: vector<3x2xi32>) -> vector<3x2xi32>
+// CHECK-NEXT:    [[RES:%.+]] = arith.xori [[ARG0]], [[ARG1]] : vector<3x2xi32>
+// CHECK:         return [[RES]] : vector<3x2xi32>
+func.func @xori_vector_a_b(%a : vector<3xi64>, %b : vector<3xi64>) -> vector<3xi64> {
+    %x = arith.xori %a, %b : vector<3xi64>
+    return %x : vector<3xi64>
+}