Visualizing MLIR codes to generate DFGs through graphviz

lib/NeuraDialect/NeuraPasses.cpp

@@ -1,13 +1,19 @@
 #include "mlir/Pass/PassManager.h"
 #include "mlir/Pass/PassRegistry.h"
 #include "mlir/Transforms/Passes.h"
+#include "llvm/Support/FileSystem.h"
+#include "llvm/Support/raw_ostream.h"
 
 #include "Conversion/ConversionPasses.h"
 #include "NeuraDialect/NeuraDialect.h"
 #include "NeuraDialect/NeuraOps.h"
 #include "NeuraDialect/NeuraPasses.h"
 #include "NeuraDialect/NeuraTypes.h"
 
+std::string filename = "opgraph.dot";
+std::error_code EC;
+llvm::raw_fd_ostream os(filename, EC, llvm::sys::fs::OF_Text);
+
 // This pass pipeline can convert all the other dialects into the Neura dialect
 void mlir::neura::registerNeuraConversionPassPipeline() {
   PassPipelineRegistration<>(
@@ -17,5 +23,17 @@ void mlir::neura::registerNeuraConversionPassPipeline() {
         // Convert all the other dialects into the Neura dialect
         pm.addPass(mlir::createLowerArithToNeuraPass());
         pm.addPass(mlir::createLowerLlvmToNeuraPass());
+        pm.addPass(mlir::createPrintOpGraphPass(os));
+
+        pm.addPass(mlir::neura::createCanonicalizeCastPass());
+        pm.addPass(mlir::neura::createCanonicalizeLiveInPass());
+        pm.addPass(mlir::neura::createLeveragePredicatedValuePass());
+        pm.addPass(mlir::createPrintOpGraphPass(os));
+
+        pm.addPass(mlir::neura::createTransformCtrlToDataFlowPass());
+        pm.addPass(mlir::neura::createFoldConstantPass());
+        pm.addPass(mlir::neura::createFusePatternPass());
+        pm.addPass(mlir::neura::createInsertDataMovPass());
+        pm.addPass(mlir::createPrintOpGraphPass(os));
       });
-}
+}

test/visualize/README.md

@@ -0,0 +1,28 @@
+# MLIR Code Visualization Guide
+
+This guide explains how to visualize MLIR (Multi-Level Intermediate Representation) code using various tools and techniques.
+
+## Usage
+
+First, run `apt install graphviz` to install Graphviz. For an MLIR file, use the option `--view-op-graph` to generate a Graphviz visualization of a function. Then, use the `dot` command to create an image file from the visualization.
+
+Example:
+
+```bash
+mlir-neura-opt --assign-accelerator --lower-arith-to-neura --fuse-pattern --view-op-graph test.mlir 2> test.dot 
+dot -Tpng test.dot -o test.png
+```
+
+It will generate a `test.png` file in the current directory, as shown below:
+
+![test](test.png)
+
+If there are multiple graphs in one dot file, you can use the option `-O` to generate multiple DFGs from one dot file.
+
+Example:
+
+```bash
+dot -Tpng test.dot -O
+```
+
+It will generate `test.dot.png`, `test.dot.1.png`, `test.dot.2.png`, etc.

test/visualize/test.mlir

@@ -0,0 +1,12 @@
+// Test 1: Verify dot generation for fused operations
+// RUN: mlir-neura-opt --assign-accelerator --lower-arith-to-neura --fuse-pattern --view-op-graph %s 2>&1 | FileCheck %s --check-prefix=CHECK-DOT-GENERATION
+
+func.func @test_dot_generation(%a: f32, %b: f32, %c: f32) -> f32 {
+  %temp = arith.addf %a, %b : f32
+  %res = arith.addf %temp, %c : f32
+  // CHECK-DOT-GENERATION: digraph G
+  // CHECK-DOT-GENERATION: label = "func.func : ()\n\naccelerator: \"neura\"\nfunction_type: (f32, f32, f32) -> f...\nsym_name: \"test_dot_generation...";
+  // CHECK-DOT-GENERATION: label = "neura.fadd_fadd : (f32)\n"
+  return %res : f32
+}
+

test/visualize/test2.mlir

@@ -0,0 +1,25 @@
+// Test PrintOpGraphPass in neura-compiler
+// RUN: neura-compiler --neura-conversion %s
+// RUN: FileCheck %s --input-file=%S/opgraph.dot -check-prefix=CHECK-GRAPH
+
+func.func @test_print_op_graph(%a: f32, %b: f32) -> f32 {
+  %c = arith.constant 1.0 : f32
+  %d = arith.addf %a, %b : f32
+  %e = arith.mulf %d, %c : f32
+  return %e : f32
+}
+
+// CHECK-GRAPH: digraph G
+// CHECK-GRAPH: compound = true;
+// CHECK-GRAPH: label = "func.func : ()\n\naccelerator: \"neura\"\nfunction_type: (f32, f32) -> f32\nsym_name: \"test_print_op_graph...";
+// CHECK-GRAPH: label = "neura.fadd : (f32)\n"
+// CHECK-GRAPH: label = "neura.return : ()\n"
+// CHECK-GRAPH: digraph G
+// CHECK-GRAPH: label = "func.func : ()\n\naccelerator: \"neura\"\nfunction_type: (f32, f32) -> f32\nsym_name: \"test_print_op_graph...";
+// CHECK-GRAPH: label = "neura.constant : (!neura.data<f32, i1>)
+// CHECK-GRAPH: label = "neura.fadd : (!neura.data<f32, i1>)\n"
+// CHECK-GRAPH: digraph G
+// CHECK-GRAPH: label = "func.func : ()\n\naccelerator: \"neura\"\nfunction_type: (f32, f32) -> f32\nsym_name: \"test_print_op_graph...";
+// CHECK-GRAPH: label = "neura.constant : (!neura.data<f32, i1>)
+// CHECK-GRAPH: label = "neura.data_mov : (!neura.data<f32, i1>)
+// CHECK-GRAPH: label = "neura.fadd : (!neura.data<f32, i1>)\n"

test/visualize/visualize.sh

@@ -0,0 +1,2 @@
+mlir-neura-opt --assign-accelerator --lower-arith-to-neura --fuse-pattern --view-op-graph test.mlir 2> test.dot 
+dot -Tpng test.dot -o test.png

tools/mlir-neura-opt/mlir-neura-opt.cpp

@@ -24,6 +24,7 @@ int main(int argc, char **argv) {
 
   mlir::neura::registerPasses();
   mlir::registerPasses();
+  mlir::registerViewOpGraphPass();
 
   // Runs the MLIR optimizer.
   return mlir::asMainReturnCode(