[PyTorchPipeline] Rename from scalehls-pipeline to scalehls-pytorch-pipeline; [QoREstimation] Remove the depAnalysis option, always set to true

README.md

@@ -73,7 +73,7 @@ $ python3 export_resnet18_mlir.py | torch-mlir-opt \
 $ # Optimize the model and emit C++ code.
 $ # This may take several minutes to compile due to the large amount of weights.
 $ scalehls-opt resnet18.mlir \
-    -scalehls-pipeline="top-func=forward opt-level=2 frontend=torch" \
+    -scalehls-pytorch-pipeline="top-func=forward opt-level=2 frontend=torch" \
     | scalehls-translate -emit-hlscpp > resnet18.cpp
 ```
 

include/scalehls/Transforms/Passes.h

@@ -75,7 +75,7 @@ std::unique_ptr<Pass> createLoopPipeliningPass();
 std::unique_ptr<Pass> createArrayPartitionPass();
 std::unique_ptr<Pass> createCreateHLSCppPrimitivePass();
 
-void registerScaleHLSPassPipeline();
+void registerScaleHLSPyTorchPipeline();
 void registerTransformsPasses();
 
 #define GEN_PASS_CLASSES

include/scalehls/Transforms/Passes.td

@@ -27,10 +27,7 @@ def QoREstimation : Pass<"qor-estimation", "ModuleOp"> {
   let options = [
     Option<"targetSpec", "target-spec", "std::string",
            /*default=*/"\"./target-spec.ini\"",
-           "File path: target backend specifications and configurations">,
-
-    Option<"depAnalysis", "dep-analysis", "bool", /*default=*/"true",
-           "Whether a comprehensive dependency analysis is conducted">
+           "File path: target backend specifications and configurations">
   ];
 }
 
@@ -58,10 +55,7 @@ def MultipleLevelDSE : Pass<"dse", "ModuleOp"> {
 
     Option<"targetSpec", "target-spec", "std::string",
            /*default=*/"\"./target-spec.ini\"",
-           "File path: target backend specifications and configurations">,
-
-    Option<"depAnalysis", "dep-analysis", "bool", /*default=*/"true",
-           "Whether a comprehensive dependency analysis is conducted">
+           "File path: target backend specifications and configurations">
   ];
 }
 

lib/Transforms/MultipleLevelDSE.cpp

@@ -888,7 +888,7 @@ struct MultipleLevelDSE : public MultipleLevelDSEBase<MultipleLevelDSE> {
       maxDspNum = UINT_MAX;
 
     // Initialize an performance and resource estimator.
-    auto estimator = ScaleHLSEstimator(latencyMap, dspUsageMap, depAnalysis);
+    auto estimator = ScaleHLSEstimator(latencyMap, dspUsageMap, true);
     auto optimizer = ScaleHLSOptimizer(
         estimator, outputNum, maxDspNum, maxInitParallel, maxExplParallel,
         maxLoopParallel, maxIterNum, maxDistance);

lib/Transforms/Passes.cpp

@@ -22,9 +22,9 @@ namespace {
 #include "scalehls/Transforms/Passes.h.inc"
 } // namespace
 
-void scalehls::registerScaleHLSPassPipeline() {
+void scalehls::registerScaleHLSPyTorchPipeline() {
   PassPipelineRegistration<ScaleHLSOptions>(
-      "scalehls-pipeline", "Compile to HLS C++",
+      "scalehls-pytorch-pipeline", "Compile TOSA (from Torch-MLIR) to HLS C++",
       [](OpPassManager &pm, const ScaleHLSOptions &opts) {
         unsigned dataflowGran = 0;
         unsigned loopUnrollSize = 0;

lib/Transforms/QoREstimation.cpp

@@ -983,8 +983,7 @@ struct QoREstimation : public scalehls::QoREstimationBase<QoREstimation> {
     for (auto func : module.getOps<FuncOp>())
       if (auto funcDirect = getFuncDirective(func))
         if (funcDirect.getTopFunc())
-          ScaleHLSEstimator(latencyMap, dspUsageMap, depAnalysis)
-              .estimateFunc(func);
+          ScaleHLSEstimator(latencyMap, dspUsageMap, true).estimateFunc(func);
   }
 };
 } // namespace