big cleanup: remove remaining pim many operations, simplify bufferization logic

src/PIM/Common/IR/AddressAnalysis.cpp

@@ -228,7 +228,7 @@ llvm::FailureOr<ResolvedContiguousAddress> resolveContiguousAddressImpl(mlir::Va
       continue;
     }
 
-    if (mlir::isa<onnx_mlir::pim::PimEmptyManyOp, mlir::memref::AllocOp, mlir::memref::GetGlobalOp>(definingOp))
+    if (mlir::isa<mlir::memref::AllocOp, mlir::memref::GetGlobalOp>(definingOp))
       return ResolvedContiguousAddress {value, byteOffset};
 
     return mlir::failure();

src/PIM/Compiler/PimCodeGen.cpp

@@ -42,6 +42,79 @@ static size_t getValueSizeInBytes(mlir::Value value) {
   return type.getNumElements() * type.getElementTypeBitWidth() / 8;
 }
 
+struct DenseWeightView {
+  DenseElementsAttr denseAttr;
+  SmallVector<int64_t> shape;
+  SmallVector<int64_t> strides;
+  int64_t offset = 0;
+};
+
+static SmallVector<int64_t> computeRowMajorStridesForShape(ArrayRef<int64_t> shape) {
+  SmallVector<int64_t> strides(shape.size(), 1);
+  for (int64_t index = static_cast<int64_t>(shape.size()) - 2; index >= 0; --index)
+    strides[index] = strides[index + 1] * shape[index + 1];
+  return strides;
+}
+
+static bool allStaticSubviewParts(memref::SubViewOp subview) {
+  return llvm::all_of(subview.getStaticOffsets(), [](int64_t value) { return !ShapedType::isDynamic(value); })
+      && llvm::all_of(subview.getStaticSizes(), [](int64_t value) { return !ShapedType::isDynamic(value); })
+      && llvm::all_of(subview.getStaticStrides(), [](int64_t value) { return !ShapedType::isDynamic(value); });
+}
+
+static FailureOr<DenseWeightView> resolveDenseWeightView(ModuleOp moduleOp, mlir::Value weight) {
+  SmallVector<memref::SubViewOp> subviews;
+  mlir::Value current = weight;
+  memref::GetGlobalOp getGlobalOp;
+
+  while (true) {
+    Operation* defOp = current.getDefiningOp();
+    if (!defOp)
+      return failure();
+    if ((getGlobalOp = dyn_cast<memref::GetGlobalOp>(defOp)))
+      break;
+    if (auto subview = dyn_cast<memref::SubViewOp>(defOp)) {
+      if (!allStaticSubviewParts(subview))
+        return failure();
+      subviews.push_back(subview);
+      current = subview.getSource();
+      continue;
+    }
+    if (auto cast = dyn_cast<memref::CastOp>(defOp)) {
+      current = cast.getSource();
+      continue;
+    }
+    return failure();
+  }
+
+  auto globalOp = lookupGlobalForGetGlobal(moduleOp, getGlobalOp);
+  if (!globalOp || !globalOp.getInitialValue())
+    return failure();
+
+  auto denseAttr = dyn_cast<DenseElementsAttr>(*globalOp.getInitialValue());
+  if (!denseAttr)
+    return failure();
+
+  DenseWeightView view;
+  view.denseAttr = denseAttr;
+  view.shape.assign(denseAttr.getType().getShape().begin(), denseAttr.getType().getShape().end());
+  view.strides = computeRowMajorStridesForShape(view.shape);
+
+  for (memref::SubViewOp subview : llvm::reverse(subviews)) {
+    SmallVector<int64_t> nextStrides;
+    nextStrides.reserve(subview.getStaticStrides().size());
+    for (auto [offset, stride, sourceStride] :
+         llvm::zip_equal(subview.getStaticOffsets(), subview.getStaticStrides(), view.strides)) {
+      view.offset += offset * sourceStride;
+      nextStrides.push_back(stride * sourceStride);
+    }
+    view.shape.assign(subview.getStaticSizes().begin(), subview.getStaticSizes().end());
+    view.strides = std::move(nextStrides);
+  }
+
+  return view;
+}
+
 MemEntry* PimMemory::gatherMemEntry(mlir::Value value) {
   auto type = cast<ShapedType>(value.getType());
   assert("Only static shape is supported" && type.hasStaticShape());
@@ -97,11 +170,6 @@ void PimMemory::allocateHost(ModuleOp moduleOp, func::FuncOp funcOp) {
     if (!allocOp->getParentOfType<pim::PimCoreOp>())
       gatherMemEntry(allocOp.getResult());
   });
-  funcOp.walk([&](pim::PimEmptyManyOp emptyManyOp) {
-    if (!emptyManyOp->getParentOfType<pim::PimCoreOp>() && !emptyManyOp->getParentOfType<pim::PimCoreBatchOp>())
-      for (mlir::Value output : emptyManyOp.getOutputs())
-        gatherMemEntry(output);
-  });
 
   allocateGatheredMemory();
 
@@ -111,10 +179,6 @@ void PimMemory::allocateHost(ModuleOp moduleOp, func::FuncOp funcOp) {
 
 void PimMemory::allocateCore(Operation* op) {
   op->walk([&](memref::AllocOp allocOp) { gatherMemEntry(allocOp); });
-  op->walk([&](pim::PimEmptyManyOp emptyManyOp) {
-    for (mlir::Value output : emptyManyOp.getOutputs())
-      gatherMemEntry(output);
-  });
 
   allocateGatheredMemory();
 }
@@ -369,13 +433,6 @@ void PimCodeGen::codeGenReceiveOp(pim::PimReceiveOp receiveOp, const StaticValue
     "recv", addressOf(receiveOp.getOutputBuffer(), knowledge), receiveOp.getSourceCoreId(), receiveOp.getSize());
 }
 
-void PimCodeGen::codeGenReceiveManyOp(pim::PimReceiveManyOp receiveManyOp,
-                                      const StaticValueKnowledge& knowledge) const {
-  for (auto [outputBuffer, sourceCoreId] :
-       llvm::zip(receiveManyOp.getOutputBuffers(), receiveManyOp.getSourceCoreIds()))
-    emitCommunicationOp("recv", addressOf(outputBuffer, knowledge), sourceCoreId, getValueSizeInBytes(outputBuffer));
-}
-
 void PimCodeGen::codeGenReceiveTensorOp(pim::PimReceiveTensorOp receiveTensorOp,
                                         const StaticValueKnowledge& knowledge) const {
   size_t outputAddr = addressOf(receiveTensorOp.getOutputBuffer(), knowledge);
@@ -388,11 +445,6 @@ void PimCodeGen::codeGenSendOp(pim::PimSendOp sendOp, const StaticValueKnowledge
   emitCommunicationOp("send", addressOf(sendOp.getInput(), knowledge), sendOp.getTargetCoreId(), sendOp.getSize());
 }
 
-void PimCodeGen::codeGenSendManyOp(pim::PimSendManyOp sendManyOp, const StaticValueKnowledge& knowledge) const {
-  for (auto [input, targetCoreId] : llvm::zip(sendManyOp.getInputs(), sendManyOp.getTargetCoreIds()))
-    emitCommunicationOp("send", addressOf(input, knowledge), targetCoreId, getValueSizeInBytes(input));
-}
-
 void PimCodeGen::codeGenSendTensorOp(pim::PimSendTensorOp sendTensorOp, const StaticValueKnowledge& knowledge) const {
   size_t inputAddr = addressOf(sendTensorOp.getInput(), knowledge);
   size_t chunkSize = getValueSizeInBytes(sendTensorOp.getInput()) / sendTensorOp.getTargetCoreIds().size();
@@ -400,20 +452,6 @@ void PimCodeGen::codeGenSendTensorOp(pim::PimSendTensorOp sendTensorOp, const St
     emitCommunicationOp("send", inputAddr + chunkIndex * chunkSize, targetCoreId, chunkSize);
 }
 
-void PimCodeGen::codeGenExtractRowsOp(pim::PimExtractRowsOp extractRowsOp,
-                                      const StaticValueKnowledge& knowledge) const {
-  auto inputType = cast<ShapedType>(extractRowsOp.getInput().getType());
-  assert(inputType.hasStaticShape() && inputType.getRank() == 2 && "extract_rows codegen requires static rank-2 input");
-
-  size_t elementSize = inputType.getElementTypeBitWidth() / 8;
-  size_t rowSizeInBytes = static_cast<size_t>(inputType.getDimSize(1)) * elementSize;
-  size_t inputAddr = addressOf(extractRowsOp.getInput(), knowledge);
-
-  for (auto [rowIndex, outputBuffer] : llvm::enumerate(extractRowsOp.getOutputBuffers()))
-    emitMemCopyOp(
-      "lmv", addressOf(outputBuffer, knowledge), 0, inputAddr, rowIndex * rowSizeInBytes, rowSizeInBytes, "len");
-}
-
 void PimCodeGen::codeGenConcatOp(pim::PimConcatOp concatOp, const StaticValueKnowledge& knowledge) const {
   auto outputType = cast<ShapedType>(concatOp.getOutputBuffer().getType());
   assert(outputType.hasStaticShape() && "concat codegen requires static output shape");
@@ -742,23 +780,6 @@ static pim::PimCoreOp materializeScalarCoreFromBatchLane(pim::PimCoreBatchOp cor
       continue;
     }
 
-    if (auto sendManyBatchOp = dyn_cast<pim::PimSendManyBatchOp>(op)) {
-      SmallVector<int32_t> laneTargetCoreIds;
-      laneTargetCoreIds.reserve(sendManyBatchOp.getInputs().size());
-      for (auto valueIndex : llvm::seq<size_t>(0, sendManyBatchOp.getInputs().size()))
-        laneTargetCoreIds.push_back(
-          sendManyBatchOp.getTargetCoreIds()[valueIndex * laneCount + static_cast<size_t>(lane)]);
-
-      SmallVector<mlir::Value> mappedInputs;
-      mappedInputs.reserve(sendManyBatchOp.getInputs().size());
-      for (mlir::Value input : sendManyBatchOp.getInputs())
-        mappedInputs.push_back(mapper.lookup(input));
-
-      pim::PimSendManyOp::create(
-        builder, sendManyBatchOp.getLoc(), builder.getDenseI32ArrayAttr(laneTargetCoreIds), ValueRange(mappedInputs));
-      continue;
-    }
-
     if (auto receiveBatchOp = dyn_cast<pim::PimReceiveBatchOp>(op)) {
       auto scalarReceive =
         pim::PimReceiveOp::create(builder,
@@ -771,29 +792,6 @@ static pim::PimCoreOp materializeScalarCoreFromBatchLane(pim::PimCoreBatchOp cor
       continue;
     }
 
-    if (auto receiveManyBatchOp = dyn_cast<pim::PimReceiveManyBatchOp>(op)) {
-      SmallVector<int32_t> laneSourceCoreIds;
-      laneSourceCoreIds.reserve(receiveManyBatchOp.getOutputs().size());
-      for (auto valueIndex : llvm::seq<size_t>(0, receiveManyBatchOp.getOutputs().size()))
-        laneSourceCoreIds.push_back(
-          receiveManyBatchOp.getSourceCoreIds()[valueIndex * laneCount + static_cast<size_t>(lane)]);
-
-      SmallVector<mlir::Value> mappedOutputBuffers;
-      mappedOutputBuffers.reserve(receiveManyBatchOp.getOutputBuffers().size());
-      for (mlir::Value outputBuffer : receiveManyBatchOp.getOutputBuffers())
-        mappedOutputBuffers.push_back(mapper.lookup(outputBuffer));
-
-      auto scalarReceiveMany = pim::PimReceiveManyOp::create(builder,
-                                                             receiveManyBatchOp.getLoc(),
-                                                             receiveManyBatchOp->getResultTypes(),
-                                                             ValueRange(mappedOutputBuffers),
-                                                             builder.getDenseI32ArrayAttr(laneSourceCoreIds));
-      for (auto [originalOutput, scalarOutput] :
-           llvm::zip(receiveManyBatchOp.getOutputs(), scalarReceiveMany.getOutputs()))
-        mapper.map(originalOutput, scalarOutput);
-      continue;
-    }
-
     if (auto memcpBatchOp = dyn_cast<pim::PimMemCopyHostToDevBatchOp>(op)) {
       mlir::Value hostSource = mapper.lookupOrNull(memcpBatchOp.getHostSource());
       if (!hostSource)
@@ -912,18 +910,12 @@ static int64_t codeGenCoreOps(Block& block, PimCodeGen& coreCodeGen) {
         coreCodeGen.codeGenLmvOp(lmvOp, knowledge);
       else if (auto receiveOp = dyn_cast<pim::PimReceiveOp>(op))
         coreCodeGen.codeGenReceiveOp(receiveOp, knowledge);
-      else if (auto receiveManyOp = dyn_cast<pim::PimReceiveManyOp>(op))
-        coreCodeGen.codeGenReceiveManyOp(receiveManyOp, knowledge);
       else if (auto receiveTensorOp = dyn_cast<pim::PimReceiveTensorOp>(op))
         coreCodeGen.codeGenReceiveTensorOp(receiveTensorOp, knowledge);
       else if (auto sendOp = dyn_cast<pim::PimSendOp>(op))
         coreCodeGen.codeGenSendOp(sendOp, knowledge);
-      else if (auto sendManyOp = dyn_cast<pim::PimSendManyOp>(op))
-        coreCodeGen.codeGenSendManyOp(sendManyOp, knowledge);
       else if (auto sendTensorOp = dyn_cast<pim::PimSendTensorOp>(op))
         coreCodeGen.codeGenSendTensorOp(sendTensorOp, knowledge);
-      else if (auto extractRowsOp = dyn_cast<pim::PimExtractRowsOp>(op))
-        coreCodeGen.codeGenExtractRowsOp(extractRowsOp, knowledge);
       else if (auto concatOp = dyn_cast<pim::PimConcatOp>(op))
         coreCodeGen.codeGenConcatOp(concatOp, knowledge);
       else if (auto vmmOp = dyn_cast<pim::PimVMMOp>(op))
@@ -954,8 +946,6 @@ static int64_t codeGenCoreOps(Block& block, PimCodeGen& coreCodeGen) {
         coreCodeGen.codeGenVSoftmaxOp(vsoftmaxOp, knowledge);
       else if (auto getGlobalOp = dyn_cast<memref::GetGlobalOp>(op))
         coreCodeGen.codeGetGlobalOp(getGlobalOp, knowledge);
-      else if (isa<pim::PimEmptyManyOp>(op))
-        return success();
       else {
         op.emitError("Unsupported codegen for this operation");
         op.dump();
@@ -967,84 +957,6 @@ static int64_t codeGenCoreOps(Block& block, PimCodeGen& coreCodeGen) {
   return failed(result) ? -1 : static_cast<int64_t>(processedOperations);
 }
 
-/// Write crossbar weight matrices as padded binary files for a single core.
-static OnnxMlirCompilerErrorCodes writeCrossbarWeights(ModuleOp moduleOp,
-                                                       pim::PimCoreOp coreOp,
-                                                       StringRef coreWeightsDirPath,
-                                                       json::Array& xbarsPerGroup) {
-  int64_t xbarSize = crossbarSize.getValue();
-  std::error_code errorCode;
-  size_t weightIndex = 0;
-
-  for (auto weight : coreOp.getWeights()) {
-    xbarsPerGroup.push_back(weightIndex);
-
-    auto getGlobalOp = weight.getDefiningOp<memref::GetGlobalOp>();
-    if (!getGlobalOp) {
-      coreOp.emitWarning("Weight is not from a memref.get_global at index " + std::to_string(weightIndex));
-      weightIndex++;
-      continue;
-    }
-
-    auto globalOp = lookupGlobalForGetGlobal(moduleOp, getGlobalOp);
-    if (!globalOp) {
-      coreOp.emitWarning("Could not find memref.global for weight at index " + std::to_string(weightIndex));
-      weightIndex++;
-      continue;
-    }
-
-    auto initialValue = globalOp.getInitialValue();
-    if (!initialValue) {
-      coreOp.emitWarning("memref.global has no initial value at index " + std::to_string(weightIndex));
-      weightIndex++;
-      continue;
-    }
-
-    auto denseAttr = dyn_cast<DenseElementsAttr>(*initialValue);
-    if (!denseAttr) {
-      coreOp.emitWarning("memref.global initial value is not dense at index " + std::to_string(weightIndex));
-      weightIndex++;
-      continue;
-    }
-
-    auto type = denseAttr.getType();
-    auto shape = type.getShape();
-    assert(isMatrixShape(shape) && "Weight matrix must be 2-dimensional");
-    int64_t numRows = shape[0];
-    int64_t numCols = shape[1];
-    assert(numRows <= xbarSize && numCols <= xbarSize && "Weight dimensions must not exceed crossbar size");
-
-    size_t elementByteWidth = type.getElementType().getIntOrFloatBitWidth() / 8;
-
-    auto weightFilePath = (coreWeightsDirPath + "/crossbar_" + std::to_string(weightIndex) + ".bin").str();
-    raw_fd_ostream weightFileStream(weightFilePath, errorCode, sys::fs::OF_None);
-    if (errorCode) {
-      errs() << "Error while opening weight file `" << weightFilePath << "`: " << errorCode.message() << '\n';
-      return InvalidOutputFileAccess;
-    }
-
-    uint64_t zero = 0;
-    for (int64_t row = 0; row < xbarSize; row++) {
-      for (int64_t col = 0; col < xbarSize; col++) {
-        if (row < numRows && col < numCols) {
-          int64_t index = row * numCols + col;
-          APInt bits = denseAttr.getValues<APFloat>()[index].bitcastToAPInt();
-          uint64_t word = bits.getZExtValue();
-          weightFileStream.write(reinterpret_cast<const char*>(&word), elementByteWidth);
-        }
-        else {
-          weightFileStream.write(reinterpret_cast<const char*>(&zero), elementByteWidth);
-        }
-      }
-    }
-
-    weightFileStream.close();
-    weightIndex++;
-  }
-
-  return CompilerSuccess;
-}
-
 llvm::DenseMap<size_t, llvm::DenseMap<mlir::Value, std::string>>
 createAndPopulateWeightFolder(func::FuncOp funcOp, StringRef outputDirPath) {
   ModuleOp moduleOp = funcOp->getParentOfType<ModuleOp>();
@@ -1079,45 +991,31 @@ createAndPopulateWeightFolder(func::FuncOp funcOp, StringRef outputDirPath) {
         }
         mlir::Value weight = coreOp.getWeights()[index];
 
-        auto getGlobalOp = weight.getDefiningOp<memref::GetGlobalOp>();
-        if (!getGlobalOp) {
+        auto weightView = resolveDenseWeightView(moduleOp, weight);
+        if (failed(weightView)) {
           coreOp.emitWarning("Weight is not from a memref.get_global at index " + std::to_string(index));
-          assert(!getGlobalOp && "Weight is not from a memref.get_global");
+          assert(succeeded(weightView) && "Weight is not from a dense memref.global view");
         }
 
-        auto globalOp = lookupGlobalForGetGlobal(moduleOp, getGlobalOp);
-        if (!globalOp) {
-          coreOp.emitWarning("Could not find memref.global for weight at index " + std::to_string(index));
-          assert(!globalOp && "Could not find memref.global");
-        }
+        if (mapCoreWeightToFileName[coreId].contains(weight))
+          continue;
 
-        auto initialValue = globalOp.getInitialValue();
-        if (!initialValue) {
-          coreOp.emitWarning("memref.global has no initial value at index " + std::to_string(index));
-          assert(!initialValue && "memref.global has no initial value");
-        }
-
-        auto denseAttr = dyn_cast<DenseElementsAttr>(*initialValue);
-        if (!denseAttr) {
-          coreOp.emitWarning("memref.global initial value is not dense at index " + std::to_string(index));
-          assert(!denseAttr && "memref.global initial value is not dense");
-        }
-
-        if (mapGlobalOpToFileName.contains(globalOp)) {
+        auto getGlobalOp = weight.getDefiningOp<memref::GetGlobalOp>();
+        auto globalOp = getGlobalOp ? lookupGlobalForGetGlobal(moduleOp, getGlobalOp) : memref::GlobalOp {};
+        if (globalOp && mapGlobalOpToFileName.contains(globalOp)) {
           auto& fileName = mapGlobalOpToFileName[globalOp];
-          std::pair<mlir::Value, std::string> weightToFile = {weight, fileName};
-          mapCoreWeightToFileName[coreId].insert(weightToFile);
+          mapCoreWeightToFileName[coreId].insert({weight, fileName});
           continue;
         }
 
-        auto type = denseAttr.getType();
-        auto shape = type.getShape();
+        DenseElementsAttr denseAttr = weightView->denseAttr;
+        ArrayRef<int64_t> shape = weightView->shape;
         assert(isMatrixShape(shape) && "Weight matrix must be 2-dimensional");
         int64_t numRows = shape[0];
         int64_t numCols = shape[1];
         assert(numRows <= xbarSize && numCols <= xbarSize && "Weight dimensions must not exceed crossbar size");
 
-        size_t elementByteWidth = type.getElementType().getIntOrFloatBitWidth() / 8;
+        size_t elementByteWidth = denseAttr.getElementType().getIntOrFloatBitWidth() / 8;
 
         std::string newFileName = "crossbar_" + std::to_string(indexFileName++) + ".bin";
         auto weightFilePath = (coreWeightsDirPath + "/" + newFileName).str();
@@ -1132,8 +1030,8 @@ createAndPopulateWeightFolder(func::FuncOp funcOp, StringRef outputDirPath) {
         for (int64_t row = 0; row < xbarSize; row++) {
           for (int64_t col = 0; col < xbarSize; col++) {
             if (row < numRows && col < numCols) {
-              int64_t index = row * numCols + col;
-              APInt bits = denseAttr.getValues<APFloat>()[index].bitcastToAPInt();
+              int64_t elementIndex = weightView->offset + row * weightView->strides[0] + col * weightView->strides[1];
+              APInt bits = denseAttr.getValues<APFloat>()[elementIndex].bitcastToAPInt();
               uint64_t word = bits.getZExtValue();
               weightFileStream.write(reinterpret_cast<const char*>(&word), elementByteWidth);
             }
@@ -1144,6 +1042,7 @@ createAndPopulateWeightFolder(func::FuncOp funcOp, StringRef outputDirPath) {
         }
 
         weightFileStream.close();
+        if (globalOp)
           mapGlobalOpToFileName.insert({globalOp, newFileName});
         mapCoreWeightToFileName[coreId].insert({weight, newFileName});
       }

src/PIM/Compiler/PimCodeGen.hpp

@@ -24,8 +24,6 @@ class PimMemory {
   llvm::SmallVector<std::pair<MemEntry, mlir::Value>, 32> memEntries;
   llvm::SmallDenseMap<mlir::Value, MemEntry, 32>& globalMemEntriesMap;
 
-  size_t maxSize = 0; // 0 for unbounded memory
-  size_t startAddress = 0;
   size_t minAlignment = 4;
   size_t firstAvailableAddress = 0;
 
@@ -117,12 +115,9 @@ public:
   void codeGenLmvOp(pim::PimMemCopyOp lmvOp, const StaticValueKnowledge& knowledge) const;
 
   void codeGenReceiveOp(pim::PimReceiveOp receiveOp, const StaticValueKnowledge& knowledge) const;
-  void codeGenReceiveManyOp(pim::PimReceiveManyOp receiveManyOp, const StaticValueKnowledge& knowledge) const;
   void codeGenReceiveTensorOp(pim::PimReceiveTensorOp receiveTensorOp, const StaticValueKnowledge& knowledge) const;
   void codeGenSendOp(pim::PimSendOp sendOp, const StaticValueKnowledge& knowledge) const;
-  void codeGenSendManyOp(pim::PimSendManyOp sendManyOp, const StaticValueKnowledge& knowledge) const;
   void codeGenSendTensorOp(pim::PimSendTensorOp sendTensorOp, const StaticValueKnowledge& knowledge) const;
-  void codeGenExtractRowsOp(pim::PimExtractRowsOp extractRowsOp, const StaticValueKnowledge& knowledge) const;
   void codeGenConcatOp(pim::PimConcatOp concatOp, const StaticValueKnowledge& knowledge) const;
 
   template <typename MVMTy>

src/PIM/Conversion/SpatialToPim/SpatialToPimPass.cpp

@@ -116,7 +116,7 @@ static SmallVector<int32_t> getPimCoreIdsForBatchOp(spatial::SpatComputeBatch co
 
   SmallVector<int32_t> coreIds;
   coreIds.reserve(static_cast<size_t>(computeBatchOp.getLaneCount()));
-  for (int32_t lane = 0; lane < computeBatchOp.getLaneCount(); ++lane)
+  for (uint32_t lane = 0; lane < computeBatchOp.getLaneCount(); ++lane)
     coreIds.push_back(static_cast<int32_t>(fallbackCoreId++));
   return coreIds;
 }
@@ -150,40 +150,33 @@ static void lowerChannelReceive(spatial::SpatChannelReceiveOp receiveOp, IRRewri
 
 static void lowerChannelSendMany(spatial::SpatChannelSendManyOp sendManyOp, IRRewriter& rewriter) {
   rewriter.setInsertionPoint(sendManyOp);
-  SmallVector<int32_t> targetCoreIds;
-  targetCoreIds.reserve(sendManyOp.getTargetCoreIds().size());
-  for (int32_t targetCoreId : sendManyOp.getTargetCoreIds())
-    targetCoreIds.push_back(translateSpatialCoreIdToPimCoreId(targetCoreId));
-  PimSendManyOp::create(
-    rewriter, sendManyOp.getLoc(), rewriter.getDenseI32ArrayAttr(targetCoreIds), sendManyOp.getInputs());
-  rewriter.eraseOp(sendManyOp);
+  for (auto [input, targetCoreId] : llvm::zip(sendManyOp.getInputs(), sendManyOp.getTargetCoreIds())) {
+    PimSendOp::create(rewriter,
+                      sendManyOp.getLoc(),
+                      input,
+                      getTensorSizeInBytesAttr(rewriter, input),
+                      rewriter.getI32IntegerAttr(translateSpatialCoreIdToPimCoreId(targetCoreId)));
   }
-
-static SmallVector<Value> createManyEmptyTensorsLike(IRRewriter& rewriter, Location loc, TypeRange outputTypes) {
-  SmallVector<Type> tensorTypes;
-  tensorTypes.reserve(outputTypes.size());
-  for (Type outputType : outputTypes)
-    tensorTypes.push_back(outputType);
-
-  auto emptyMany = pim::PimEmptyManyOp::create(rewriter, loc, TypeRange(tensorTypes));
-  return SmallVector<Value>(emptyMany.getOutputs().begin(), emptyMany.getOutputs().end());
+  rewriter.eraseOp(sendManyOp);
 }
 
 static void lowerChannelReceiveMany(spatial::SpatChannelReceiveManyOp receiveManyOp, IRRewriter& rewriter) {
   rewriter.setInsertionPoint(receiveManyOp);
-  SmallVector<int32_t> sourceCoreIds;
-  sourceCoreIds.reserve(receiveManyOp.getSourceCoreIds().size());
-  for (int32_t sourceCoreId : receiveManyOp.getSourceCoreIds())
-    sourceCoreIds.push_back(translateSpatialCoreIdToPimCoreId(sourceCoreId));
-  SmallVector<Value> outputBuffers =
-    createManyEmptyTensorsLike(rewriter, receiveManyOp.getLoc(), receiveManyOp.getResultTypes());
-
-  auto receiveMany = PimReceiveManyOp::create(rewriter,
+  SmallVector<Value> replacements;
+  replacements.reserve(receiveManyOp.getNumResults());
+  for (auto [output, sourceCoreId] : llvm::zip(receiveManyOp.getOutputs(), receiveManyOp.getSourceCoreIds())) {
+    auto outputType = cast<ShapedType>(output.getType());
+    Value outputBuffer = createEmptyTensorFromShaped(rewriter, receiveManyOp.getLoc(), outputType).getResult();
+    replacements.push_back(
+      PimReceiveOp::create(rewriter,
                            receiveManyOp.getLoc(),
-                                              receiveManyOp.getResultTypes(),
-                                              ValueRange(outputBuffers),
-                                              rewriter.getDenseI32ArrayAttr(sourceCoreIds));
-  rewriter.replaceOp(receiveManyOp, receiveMany.getOutputs());
+                           output.getType(),
+                           outputBuffer,
+                           getTensorSizeInBytesAttr(rewriter, output),
+                           rewriter.getI32IntegerAttr(translateSpatialCoreIdToPimCoreId(sourceCoreId)))
+        .getOutput());
+  }
+  rewriter.replaceOp(receiveManyOp, replacements);
 }
 
 static void lowerChannelSendManyBatch(spatial::SpatChannelSendManyBatchOp sendManyBatchOp,
@@ -198,8 +191,17 @@ static void lowerChannelSendManyBatch(spatial::SpatChannelSendManyBatchOp sendMa
   mappedInputs.reserve(sendManyBatchOp.getInputs().size());
   for (Value input : sendManyBatchOp.getInputs())
     mappedInputs.push_back(mapper.lookup(input));
-  pim::PimSendManyBatchOp::create(
-    rewriter, sendManyBatchOp.getLoc(), rewriter.getDenseI32ArrayAttr(targetCoreIds), ValueRange(mappedInputs));
+  for (auto [valueIndex, input] : llvm::enumerate(mappedInputs)) {
+    SmallVector<int32_t> laneTargetCoreIds;
+    laneTargetCoreIds.reserve(laneCount);
+    for (int32_t lane = 0; lane < laneCount; ++lane)
+      laneTargetCoreIds.push_back(targetCoreIds[valueIndex * laneCount + lane]);
+    pim::PimSendBatchOp::create(rewriter,
+                                sendManyBatchOp.getLoc(),
+                                input,
+                                getTensorSizeInBytesAttr(rewriter, input),
+                                rewriter.getDenseI32ArrayAttr(laneTargetCoreIds));
+  }
 }
 
 static void lowerChannelReceiveManyBatch(spatial::SpatChannelReceiveManyBatchOp receiveManyBatchOp,
@@ -210,29 +212,44 @@ static void lowerChannelReceiveManyBatch(spatial::SpatChannelReceiveManyBatchOp
   sourceCoreIds.reserve(receiveManyBatchOp.getSourceCoreIds().size());
   for (int32_t sourceCoreId : receiveManyBatchOp.getSourceCoreIds())
     sourceCoreIds.push_back(translateSpatialCoreIdToPimCoreId(sourceCoreId));
-  SmallVector<Value> outputBuffers =
-    createManyEmptyTensorsLike(rewriter, receiveManyBatchOp.getLoc(), receiveManyBatchOp.getResultTypes());
 
-  auto receiveMany = pim::PimReceiveManyBatchOp::create(rewriter,
+  for (auto [valueIndex, output] : llvm::enumerate(receiveManyBatchOp.getOutputs())) {
+    auto outputType = cast<ShapedType>(output.getType());
+    Value outputBuffer = createEmptyTensorFromShaped(rewriter, receiveManyBatchOp.getLoc(), outputType).getResult();
+    SmallVector<int32_t> laneSourceCoreIds;
+    laneSourceCoreIds.reserve(laneCount);
+    for (int32_t lane = 0; lane < laneCount; ++lane)
+      laneSourceCoreIds.push_back(sourceCoreIds[valueIndex * laneCount + lane]);
+
+    auto received = pim::PimReceiveBatchOp::create(rewriter,
                                                    receiveManyBatchOp.getLoc(),
-                                                        receiveManyBatchOp.getResultTypes(),
-                                                        ValueRange(outputBuffers),
-                                                        rewriter.getDenseI32ArrayAttr(sourceCoreIds));
-  for (auto [output, received] : llvm::zip(receiveManyBatchOp.getOutputs(), receiveMany.getOutputs()))
+                                                   output.getType(),
+                                                   outputBuffer,
+                                                   getTensorSizeInBytesAttr(rewriter, output),
+                                                   rewriter.getDenseI32ArrayAttr(laneSourceCoreIds))
+                      .getOutput();
     mapper.map(output, received);
   }
+}
 
 static void lowerExtractRows(spatial::SpatExtractRowsOp extractRowsOp, IRRewriter& rewriter) {
   rewriter.setInsertionPoint(extractRowsOp);
-  SmallVector<Value> outputBuffers =
-    createManyEmptyTensorsLike(rewriter, extractRowsOp.getLoc(), extractRowsOp.getResultTypes());
-
-  auto extractRows = pim::PimExtractRowsOp::create(rewriter,
-                                                   extractRowsOp.getLoc(),
-                                                   extractRowsOp.getResultTypes(),
-                                                   extractRowsOp.getInput(),
-                                                   ValueRange(outputBuffers));
-  rewriter.replaceOp(extractRowsOp, extractRows.getOutputs());
+  auto inputType = cast<RankedTensorType>(extractRowsOp.getInput().getType());
+  SmallVector<Value> replacements;
+  replacements.reserve(extractRowsOp.getNumResults());
+  for (auto [rowIndex, output] : llvm::enumerate(extractRowsOp.getOutputs())) {
+    auto outputType = cast<RankedTensorType>(output.getType());
+    SmallVector<OpFoldResult> offsets = {
+      rewriter.getIndexAttr(static_cast<int64_t>(rowIndex) * outputType.getDimSize(0)), rewriter.getIndexAttr(0)};
+    SmallVector<OpFoldResult> sizes = {rewriter.getIndexAttr(outputType.getDimSize(0)),
+                                       rewriter.getIndexAttr(inputType.getDimSize(1))};
+    SmallVector<OpFoldResult> strides = {rewriter.getIndexAttr(1), rewriter.getIndexAttr(1)};
+    replacements.push_back(
+      tensor::ExtractSliceOp::create(
+        rewriter, extractRowsOp.getLoc(), outputType, extractRowsOp.getInput(), offsets, sizes, strides)
+        .getResult());
+  }
+  rewriter.replaceOp(extractRowsOp, replacements);
 }
 
 static void lowerConcat(spatial::SpatConcatOp concatOp, IRRewriter& rewriter) {
@@ -258,14 +275,26 @@ static void lowerMapOps(func::FuncOp funcOp, IRRewriter& rewriter) {
 
   for (auto mapOp : mapOps) {
     Block& body = mapOp.getBody().front();
-    rewriter.setInsertionPoint(mapOp);
-    auto pimMap = pim::PimMapOp::create(rewriter, mapOp.getLoc(), mapOp.getResultTypes(), mapOp.getInputs());
-    rewriter.inlineRegionBefore(mapOp.getBody(), pimMap.getBody(), pimMap.getBody().begin());
-
     auto yieldOp = cast<spatial::SpatYieldOp>(body.getTerminator());
-    rewriter.setInsertionPoint(yieldOp);
-    rewriter.replaceOpWithNewOp<pim::PimYieldOp>(yieldOp, yieldOp.getOutputs());
-    rewriter.replaceOp(mapOp, pimMap.getOutputs());
+    SmallVector<Value> replacements;
+    replacements.reserve(mapOp.getInputs().size());
+    rewriter.setInsertionPoint(mapOp);
+
+    for (Value input : mapOp.getInputs()) {
+      IRMapping mapping;
+      mapping.map(body.getArgument(0), input);
+
+      for (Operation& bodyOp : body.without_terminator()) {
+        Operation* cloned = rewriter.clone(bodyOp, mapping);
+        for (auto [originalResult, clonedResult] : llvm::zip(bodyOp.getResults(), cloned->getResults()))
+          mapping.map(originalResult, clonedResult);
+        rewriter.setInsertionPointAfter(cloned);
+      }
+
+      replacements.push_back(mapping.lookupOrDefault(yieldOp.getOperand(0)));
+    }
+
+    rewriter.replaceOp(mapOp, replacements);
   }
 }
 
@@ -295,7 +324,7 @@ static bool getContiguousOpResults(ValueRange values, Operation*& owner, unsigne
 }
 
 static Value createPackedExtractRowsSlice(
-  pim::PimExtractRowsOp extractRowsOp, unsigned startIndex, unsigned count, IRRewriter& rewriter, Location loc) {
+  spatial::SpatExtractRowsOp extractRowsOp, unsigned startIndex, unsigned count, IRRewriter& rewriter, Location loc) {
   auto rowType = dyn_cast<RankedTensorType>(extractRowsOp.getOutputs()[startIndex].getType());
   auto inputType = dyn_cast<RankedTensorType>(extractRowsOp.getInput().getType());
   if (!rowType || !inputType || !rowType.hasStaticShape() || !inputType.hasStaticShape() || rowType.getRank() == 0)
@@ -332,14 +361,17 @@ static Value createPackedTensorForValues(ValueRange values, IRRewriter& rewriter
   if (!getContiguousOpResults(values, owner, startIndex))
     return {};
 
-  if (auto extractRowsOp = dyn_cast<pim::PimExtractRowsOp>(owner))
+  if (auto extractRowsOp = dyn_cast<spatial::SpatExtractRowsOp>(owner))
     return createPackedExtractRowsSlice(extractRowsOp, startIndex, static_cast<unsigned>(values.size()), rewriter, loc);
 
   return {};
 }
 
-static Value createPackedReceiveTensor(
-  pim::PimReceiveManyOp receiveManyOp, unsigned startIndex, unsigned count, IRRewriter& rewriter, Location loc) {
+static Value createPackedReceiveTensor(spatial::SpatChannelReceiveManyOp receiveManyOp,
+                                       unsigned startIndex,
+                                       unsigned count,
+                                       IRRewriter& rewriter,
+                                       Location loc) {
   auto rowType = dyn_cast<RankedTensorType>(receiveManyOp.getOutputs()[startIndex].getType());
   if (!rowType || !rowType.hasStaticShape() || rowType.getRank() == 0)
     return {};
@@ -351,15 +383,15 @@ static Value createPackedReceiveTensor(
   sourceCoreIds.reserve(count);
   ArrayRef<int32_t> allSourceCoreIds = receiveManyOp.getSourceCoreIds();
   for (unsigned index = 0; index < count; ++index)
-    sourceCoreIds.push_back(allSourceCoreIds[startIndex + index]);
+    sourceCoreIds.push_back(translateSpatialCoreIdToPimCoreId(allSourceCoreIds[startIndex + index]));
 
   return pim::PimReceiveTensorOp::create(
            rewriter, loc, packedType, outputBuffer.getResult(), rewriter.getDenseI32ArrayAttr(sourceCoreIds))
     .getOutput();
 }
 
-static Value
-createPackedMapTensor(pim::PimMapOp mapOp, unsigned startIndex, unsigned count, IRRewriter& rewriter, Location loc) {
+static Value createPackedMapTensor(
+  spatial::SpatMapOp mapOp, unsigned startIndex, unsigned count, IRRewriter& rewriter, Location loc) {
   Value packedInput = createPackedTensorForValues(mapOp.getInputs().slice(startIndex, count), rewriter, loc);
   if (!packedInput)
     return {};
@@ -416,7 +448,7 @@ createPackedMapTensor(pim::PimMapOp mapOp, unsigned startIndex, unsigned count,
       rewriter.setInsertionPointAfter(cloned);
     }
 
-    auto yieldOp = cast<pim::PimYieldOp>(body.getTerminator());
+    auto yieldOp = cast<spatial::SpatYieldOp>(body.getTerminator());
     Value mappedOutput = mapping.lookupOrDefault(yieldOp.getOperand(0));
 
     int64_t outputRowsPerValue = outputType.getDimSize(0);
@@ -446,9 +478,9 @@ createPackedMapTensor(pim::PimMapOp mapOp, unsigned startIndex, unsigned count,
   return loop.getResult(0);
 }
 
-static void compactPimTensorGroups(func::FuncOp funcOp, IRRewriter& rewriter) {
-  SmallVector<pim::PimSendManyOp> sendManyOps;
-  funcOp.walk([&](pim::PimSendManyOp sendManyOp) { sendManyOps.push_back(sendManyOp); });
+static void compactSpatialTensorGroups(func::FuncOp funcOp, IRRewriter& rewriter) {
+  SmallVector<spatial::SpatChannelSendManyOp> sendManyOps;
+  funcOp.walk([&](spatial::SpatChannelSendManyOp sendManyOp) { sendManyOps.push_back(sendManyOp); });
   for (auto sendManyOp : sendManyOps) {
     if (sendManyOp.getInputs().empty())
       continue;
@@ -458,12 +490,17 @@ static void compactPimTensorGroups(func::FuncOp funcOp, IRRewriter& rewriter) {
     if (!packedInput)
       continue;
 
-    pim::PimSendTensorOp::create(rewriter, sendManyOp.getLoc(), packedInput, sendManyOp.getTargetCoreIdsAttr());
+    SmallVector<int32_t> targetCoreIds;
+    targetCoreIds.reserve(sendManyOp.getTargetCoreIds().size());
+    for (int32_t targetCoreId : sendManyOp.getTargetCoreIds())
+      targetCoreIds.push_back(translateSpatialCoreIdToPimCoreId(targetCoreId));
+    pim::PimSendTensorOp::create(
+      rewriter, sendManyOp.getLoc(), packedInput, rewriter.getDenseI32ArrayAttr(targetCoreIds));
     rewriter.eraseOp(sendManyOp);
   }
 
-  SmallVector<pim::PimConcatOp> concatOps;
-  funcOp.walk([&](pim::PimConcatOp concatOp) { concatOps.push_back(concatOp); });
+  SmallVector<spatial::SpatConcatOp> concatOps;
+  funcOp.walk([&](spatial::SpatConcatOp concatOp) { concatOps.push_back(concatOp); });
   for (auto concatOp : concatOps) {
     if (concatOp.getAxis() != 0 || concatOp.getInputs().empty())
       continue;
@@ -494,11 +531,11 @@ static void compactPimTensorGroups(func::FuncOp funcOp, IRRewriter& rewriter) {
 
       unsigned count = endIndex - index;
       Value packedInput;
-      if (auto mapOp = dyn_cast<pim::PimMapOp>(owner))
+      if (auto mapOp = dyn_cast<spatial::SpatMapOp>(owner))
         packedInput = createPackedMapTensor(mapOp, startIndex, count, rewriter, concatOp.getLoc());
-      else if (auto receiveManyOp = dyn_cast<pim::PimReceiveManyOp>(owner))
+      else if (auto receiveManyOp = dyn_cast<spatial::SpatChannelReceiveManyOp>(owner))
         packedInput = createPackedReceiveTensor(receiveManyOp, startIndex, count, rewriter, concatOp.getLoc());
-      else if (auto extractRowsOp = dyn_cast<pim::PimExtractRowsOp>(owner))
+      else if (auto extractRowsOp = dyn_cast<spatial::SpatExtractRowsOp>(owner))
         packedInput = createPackedExtractRowsSlice(extractRowsOp, startIndex, count, rewriter, concatOp.getLoc());
 
       if (packedInput) {
@@ -516,12 +553,14 @@ static void compactPimTensorGroups(func::FuncOp funcOp, IRRewriter& rewriter) {
     if (!changed)
       continue;
 
-    auto newConcat = pim::PimConcatOp::create(rewriter,
+    auto newConcat = pim::PimConcatOp::create(
+      rewriter,
       concatOp.getLoc(),
       concatOp.getOutput().getType(),
       concatOp.getAxisAttr(),
       ValueRange(packedInputs),
-                                              concatOp.getOutputBuffer());
+      createEmptyTensorFromShaped(rewriter, concatOp.getLoc(), cast<ShapedType>(concatOp.getOutput().getType()))
+        .getResult());
     rewriter.replaceOp(concatOp, newConcat.getOutput());
   }
 
@@ -533,10 +572,9 @@ static void compactPimTensorGroups(func::FuncOp funcOp, IRRewriter& rewriter) {
       if (op->use_empty())
         rewriter.eraseOp(op);
   };
-  eraseUnusedOps(pim::PimMapOp {});
-  eraseUnusedOps(pim::PimReceiveManyOp {});
-  eraseUnusedOps(pim::PimExtractRowsOp {});
-  eraseUnusedOps(pim::PimEmptyManyOp {});
+  eraseUnusedOps(spatial::SpatMapOp {});
+  eraseUnusedOps(spatial::SpatChannelReceiveManyOp {});
+  eraseUnusedOps(spatial::SpatExtractRowsOp {});
 }
 
 static LogicalResult collectHelperComputeChain(spatial::SpatCompute computeOp,
@@ -617,6 +655,7 @@ struct ConcatReturnUseInfo {
   size_t returnIndex;
   SmallVector<int64_t> sliceOffsets;
   SmallVector<int64_t> concatShape;
+  SmallVector<Operation*> concatChain;
   SmallVector<Operation*> helperChain;
 };
 
@@ -669,6 +708,8 @@ static std::optional<ConcatReturnUseInfo> analyzeConcatReturnUse(Value value) {
   auto getConcatResult = [](Operation* op) -> Value {
     if (auto tensorConcat = dyn_cast<tensor::ConcatOp>(op))
       return tensorConcat.getResult();
+    if (auto spatialConcat = dyn_cast<spatial::SpatConcatOp>(op))
+      return spatialConcat.getOutput();
     if (auto pimConcat = dyn_cast<pim::PimConcatOp>(op))
       return pimConcat.getOutput();
     return {};
@@ -676,6 +717,8 @@ static std::optional<ConcatReturnUseInfo> analyzeConcatReturnUse(Value value) {
   auto getConcatAxis = [](Operation* op) -> std::optional<int64_t> {
     if (auto tensorConcat = dyn_cast<tensor::ConcatOp>(op))
       return tensorConcat.getDim();
+    if (auto spatialConcat = dyn_cast<spatial::SpatConcatOp>(op))
+      return spatialConcat.getAxis();
     if (auto pimConcat = dyn_cast<pim::PimConcatOp>(op))
       return pimConcat.getAxis();
     return std::nullopt;
@@ -683,11 +726,14 @@ static std::optional<ConcatReturnUseInfo> analyzeConcatReturnUse(Value value) {
   auto getConcatOperands = [](Operation* op) -> OperandRange {
     if (auto tensorConcat = dyn_cast<tensor::ConcatOp>(op))
       return tensorConcat.getOperands();
+    if (auto spatialConcat = dyn_cast<spatial::SpatConcatOp>(op))
+      return spatialConcat.getInputs();
     return cast<pim::PimConcatOp>(op).getInputs();
   };
 
   auto uses = value.getUses();
-  if (rangeLength(uses) != 1 || !isa<tensor::ConcatOp, pim::PimConcatOp>(uses.begin()->getOwner()))
+  if (rangeLength(uses) != 1
+      || !isa<tensor::ConcatOp, spatial::SpatConcatOp, pim::PimConcatOp>(uses.begin()->getOwner()))
     return std::nullopt;
 
   auto valueType = dyn_cast<ShapedType>(value.getType());
@@ -696,10 +742,12 @@ static std::optional<ConcatReturnUseInfo> analyzeConcatReturnUse(Value value) {
 
   SmallVector<int64_t> sliceOffsets(valueType.getRank(), 0);
   SmallVector<int64_t> concatShape(valueType.getShape().begin(), valueType.getShape().end());
+  SmallVector<Operation*> concatChain;
   Value currentValue = value;
   Operation* currentUser = uses.begin()->getOwner();
 
-  while (isa<tensor::ConcatOp, pim::PimConcatOp>(currentUser)) {
+  while (isa<tensor::ConcatOp, spatial::SpatConcatOp, pim::PimConcatOp>(currentUser)) {
+    concatChain.push_back(currentUser);
     size_t operandIndex = currentValue.getUses().begin()->getOperandNumber();
     int64_t axis = *getConcatAxis(currentUser);
     for (Value operand : getConcatOperands(currentUser).take_front(operandIndex))
@@ -749,6 +797,7 @@ static std::optional<ConcatReturnUseInfo> analyzeConcatReturnUse(Value value) {
     currentValue.getUses().begin()->getOperandNumber(),
     std::move(sliceOffsets),
     std::move(concatShape),
+    std::move(concatChain),
     std::move(helperChain),
   };
 }
@@ -918,11 +967,6 @@ void SpatialToPimPass::runOnOperation() {
     return;
   }
 
-  SmallVector<spatial::SpatConcatOp> concatOps;
-  funcOp.walk([&](spatial::SpatConcatOp op) { concatOps.push_back(op); });
-  for (auto concatOp : concatOps)
-    lowerConcat(concatOp, rewriter);
-
   for (auto computeOp : funcOp.getOps<spatial::SpatCompute>()) {
     markOpToRemove(computeOp);
     runOnComputeOp(computeOp, rewriter);
@@ -933,6 +977,7 @@ void SpatialToPimPass::runOnOperation() {
     runOnComputeBatchOp(computeBatchOp, rewriter);
   }
 
+  compactSpatialTensorGroups(funcOp, rewriter);
   lowerMapOps(funcOp, rewriter);
 
   SmallVector<spatial::SpatChannelReceiveOp> receiveOps;
@@ -1036,6 +1081,8 @@ void SpatialToPimPass::runOnOperation() {
     assert(false && "tracked op removal reached a cycle or missed dependency");
   }
 
+  compactSpatialTensorGroups(funcOp, rewriter);
+
   SmallVector<spatial::SpatConcatOp> remainingConcatOps;
   funcOp.walk([&](spatial::SpatConcatOp op) { remainingConcatOps.push_back(op); });
   for (auto concatOp : remainingConcatOps)
@@ -1066,8 +1113,6 @@ void SpatialToPimPass::runOnOperation() {
   for (auto extractRowsOp : remainingExtractRowsOps)
     lowerExtractRows(extractRowsOp, rewriter);
 
-  compactPimTensorGroups(funcOp, rewriter);
-
   // Dump to file for debug
   bool hasSpatialOps = false;
   moduleOp.walk([&](Operation* op) {
@@ -1170,6 +1215,8 @@ void SpatialToPimPass::runOnComputeOp(spatial::SpatCompute computeOp, IRRewriter
 
     if (auto concatReturnUse = analyzeConcatReturnUse(result)) {
       size_t elementSize = yieldType.getElementTypeBitWidth() / 8;
+      for (Operation* concatOp : concatReturnUse->concatChain)
+        markOpToRemove(concatOp);
 
       if (concatReturnUse->helperChain.empty()) {
         rewriter.setInsertionPointAfterValue(yieldValue);
@@ -1481,13 +1528,15 @@ void SpatialToPimPass::enlargeVMMOutTensorsToCrossbarSize(func::FuncOp funcOp, I
 void SpatialToPimPass::addResultBuffer(func::ReturnOp& returnOp, IRRewriter& rewriter) {
   outputTensors.reserve(returnOp->getNumOperands());
   for (auto [index, returnValue] : llvm::enumerate(returnOp->getOperands())) {
-    Operation* returnValueDefiningOp = returnValue.getDefiningOp();
+    Value currentReturnValue = returnValue;
+    Operation* returnValueDefiningOp = currentReturnValue.getDefiningOp();
     if (returnValueDefiningOp->hasTrait<OpTrait::ConstantLike>()) {
       assert(!hasWeightAlways(returnValueDefiningOp));
-      outputTensors.push_back([returnValue](IRRewriter& rewriter, Location loc) -> Value { return returnValue; });
+      outputTensors.push_back(
+        [currentReturnValue](IRRewriter& rewriter, Location loc) -> Value { return currentReturnValue; });
     }
     else {
-      auto outRankedTensorType = llvm::dyn_cast<mlir::RankedTensorType>(returnValue.getType());
+      auto outRankedTensorType = llvm::dyn_cast<mlir::RankedTensorType>(currentReturnValue.getType());
       auto memRefType = mlir::MemRefType::get(outRankedTensorType.getShape(), outRankedTensorType.getElementType());
 
       std::string outputName = "output_" + std::to_string(index);
@@ -1565,7 +1614,7 @@ void SpatialToPimPass::replaceReturnOpOperands(func::ReturnOp& returnOp, IRRewri
     if (!isExclusivelyOwnedByReturnChain && op->hasOneUse()) {
       Operation* onlyUser = *op->getUsers().begin();
       isExclusivelyOwnedByReturnChain =
-        isa<func::ReturnOp, tensor::ConcatOp, pim::PimConcatOp, spatial::SpatCompute>(onlyUser)
+        isa<func::ReturnOp, tensor::ConcatOp, spatial::SpatConcatOp, pim::PimConcatOp, spatial::SpatCompute>(onlyUser)
         || isChannelUseChainOp(onlyUser);
     }
     if (!isExclusivelyOwnedByReturnChain)
@@ -1593,6 +1642,13 @@ void SpatialToPimPass::replaceReturnOpOperands(func::ReturnOp& returnOp, IRRewri
       return;
     }
 
+    if (auto concatOp = dyn_cast<spatial::SpatConcatOp>(op)) {
+      markOpToRemove(concatOp);
+      for (Value operand : concatOp.getInputs())
+        markOwnedReturnChain(operand.getDefiningOp(), markOwnedReturnChain);
+      return;
+    }
+
     if (auto concatOp = dyn_cast<pim::PimConcatOp>(op)) {
       markOpToRemove(concatOp);
       for (Value operand : concatOp.getInputs())

src/PIM/Dialect/Pim/Pim.td

@@ -71,38 +71,6 @@ def PimYieldOp : PimOp<"yield", [Terminator]> {
   let hasCustomAssemblyFormat = 1;
 }
 
-def PimMapOp : PimOp<"map", [SingleBlock]> {
-  let summary = "Apply the same lane-local region to many independent tensors";
-
-  let arguments = (ins
-    Variadic<PimTensor>:$inputs
-  );
-
-  let results = (outs
-    Variadic<PimTensor>:$outputs
-  );
-
-  let regions = (region SizedRegion<1>:$body);
-
-  let hasVerifier = 1;
-  let hasCustomAssemblyFormat = 1;
-}
-
-//===----------------------------------------------------------------------===//
-// Tensor Utilities
-//===----------------------------------------------------------------------===//
-
-def PimEmptyManyOp : PimOp<"empty_many", []> {
-  let summary = "Create many identical empty tensors";
-
-  let results = (outs
-    Variadic<PimTensor>:$outputs
-  );
-
-  let hasVerifier = 1;
-  let hasCustomAssemblyFormat = 1;
-}
-
 //===----------------------------------------------------------------------===//
 // Communication
 //===----------------------------------------------------------------------===//
@@ -121,18 +89,6 @@ def PimSendOp : PimOp<"send", []> {
   }];
 }
 
-def PimSendManyOp : PimOp<"send_many", []> {
-  let summary = "Send multiple tensors to target cores";
-
-  let arguments = (ins
-    DenseI32ArrayAttr:$targetCoreIds,
-    Variadic<PimTensor>:$inputs
-  );
-
-  let hasVerifier = 1;
-  let hasCustomAssemblyFormat = 1;
-}
-
 def PimSendTensorOp : PimOp<"send_tensor", []> {
   let summary = "Send equal contiguous chunks of one tensor to target cores";
 
@@ -157,18 +113,6 @@ def PimSendBatchOp : PimOp<"send_batch", []> {
   let hasCustomAssemblyFormat = 1;
 }
 
-def PimSendManyBatchOp : PimOp<"send_many_batch", []> {
-  let summary = "Send multiple per-lane tensors to target cores from a batched core";
-
-  let arguments = (ins
-    DenseI32ArrayAttr:$targetCoreIds,
-    Variadic<PimTensor>:$inputs
-  );
-
-  let hasVerifier = 1;
-  let hasCustomAssemblyFormat = 1;
-}
-
 def PimReceiveOp : PimOp<"receive", [DestinationStyleOpInterface]> {
   let summary = "Receive a tensor from another core";
 
@@ -193,28 +137,6 @@ def PimReceiveOp : PimOp<"receive", [DestinationStyleOpInterface]> {
   }];
 }
 
-def PimReceiveManyOp : PimOp<"receive_many", [DestinationStyleOpInterface]> {
-  let summary = "Receive multiple tensors from source cores";
-
-  let arguments = (ins
-    Variadic<PimTensor>:$outputBuffers,
-    DenseI32ArrayAttr:$sourceCoreIds
-  );
-
-  let results = (outs
-    Variadic<PimTensor>:$outputs
-  );
-
-  let extraClassDeclaration = [{
-    mlir::MutableOperandRange getDpsInitsMutable() {
-      return getOutputBuffersMutable();
-    }
-  }];
-
-  let hasVerifier = 1;
-  let hasCustomAssemblyFormat = 1;
-}
-
 def PimReceiveTensorOp : PimOp<"receive_tensor", [DestinationStyleOpInterface]> {
   let summary = "Receive equal contiguous chunks from source cores into one tensor";
 
@@ -259,28 +181,6 @@ def PimReceiveBatchOp : PimOp<"receive_batch", [DestinationStyleOpInterface]> {
   let hasCustomAssemblyFormat = 1;
 }
 
-def PimReceiveManyBatchOp : PimOp<"receive_many_batch", [DestinationStyleOpInterface]> {
-  let summary = "Receive multiple per-lane tensors from source cores into a batched core";
-
-  let arguments = (ins
-    Variadic<PimTensor>:$outputBuffers,
-    DenseI32ArrayAttr:$sourceCoreIds
-  );
-
-  let results = (outs
-    Variadic<PimTensor>:$outputs
-  );
-
-  let extraClassDeclaration = [{
-    mlir::MutableOperandRange getDpsInitsMutable() {
-      return getOutputBuffersMutable();
-    }
-  }];
-
-  let hasVerifier = 1;
-  let hasCustomAssemblyFormat = 1;
-}
-
 def PimMemCopyHostToDevOp : PimOp<"memcp_hd", [DestinationStyleOpInterface]> {
   let summary = "Copy a memory region from host memory into device memory";
 
@@ -385,32 +285,6 @@ def PimMemCopyOp : PimOp<"memcp", [DestinationStyleOpInterface]> {
   }];
 }
 
-//===----------------------------------------------------------------------===//
-// Tensor utilities
-//===----------------------------------------------------------------------===//
-
-def PimExtractRowsOp : PimOp<"extract_rows", [DestinationStyleOpInterface]> {
-  let summary = "Extract every row of a rank-2 tensor as separate rank-2 row tensors";
-
-  let arguments = (ins
-    PimTensor:$input,
-    Variadic<PimTensor>:$outputBuffers
-  );
-
-  let results = (outs
-    Variadic<PimTensor>:$outputs
-  );
-
-  let extraClassDeclaration = [{
-    mlir::MutableOperandRange getDpsInitsMutable() {
-      return getOutputBuffersMutable();
-    }
-  }];
-
-  let hasVerifier = 1;
-  let hasCustomAssemblyFormat = 1;
-}
-
 def PimConcatOp : PimOp<"concat", [DestinationStyleOpInterface]> {
   let summary = "Concatenate tensors";
 

src/PIM/Dialect/Pim/PimOpsAsm.cpp

@@ -147,69 +147,6 @@ ParseResult PimYieldOp::parse(OpAsmParser& parser, OperationState& result) {
   return parser.resolveOperands(outputs, outputTypes, parser.getCurrentLocation(), result.operands);
 }
 
-void PimMapOp::print(OpAsmPrinter& printer) {
-  printer << " ";
-  printArgumentBindings(printer, getBody().front(), getInputs());
-  printer.printOptionalAttrDict((*this)->getAttrs());
-  printer << " : ";
-  printer.printType(getInputs().front().getType());
-  printer << " -> ";
-  printer.printType(getOutputs().front().getType());
-  printer << " ";
-  printer.printRegion(getBody(), /*printEntryBlockArgs=*/false);
-}
-
-ParseResult PimMapOp::parse(OpAsmParser& parser, OperationState& result) {
-  SmallVector<OpAsmParser::Argument> regionArgs;
-  SmallVector<OpAsmParser::UnresolvedOperand> inputs;
-  Type inputType;
-  Type outputType;
-
-  if (parseArgumentBindings(parser, regionArgs, inputs))
-    return failure();
-  if (inputs.empty())
-    return parser.emitError(parser.getCurrentLocation(), "map requires at least one input");
-
-  if (parser.parseOptionalAttrDict(result.attributes) || parser.parseColon() || parser.parseType(inputType)
-      || parser.parseArrow() || parser.parseType(outputType))
-    return failure();
-
-  SmallVector<Type> inputTypes(inputs.size(), inputType);
-  SmallVector<Type> outputTypes(inputs.size(), outputType);
-  if (regionArgs.size() != inputs.size())
-    return parser.emitError(parser.getCurrentLocation(), "number of argument bindings and input operands must match");
-  if (parser.resolveOperands(inputs, inputTypes, parser.getCurrentLocation(), result.operands))
-    return failure();
-  result.addTypes(outputTypes);
-
-  applyArgumentTypes(inputTypes, regionArgs);
-  Region* body = result.addRegion();
-  return parser.parseRegion(*body, regionArgs);
-}
-
-void PimEmptyManyOp::print(OpAsmPrinter& printer) {
-  printer.printOptionalAttrDict((*this)->getAttrs());
-  printer << " : ";
-  printer.printType(getOutputs().front().getType());
-  printer << " x" << getOutputs().size();
-}
-
-ParseResult PimEmptyManyOp::parse(OpAsmParser& parser, OperationState& result) {
-  Type outputType;
-  int64_t resultCount = 0;
-
-  if (parser.parseOptionalAttrDict(result.attributes) || parser.parseColon() || parser.parseType(outputType)
-      || parser.parseKeyword("x") || parser.parseInteger(resultCount))
-    return failure();
-
-  if (resultCount <= 0)
-    return parser.emitError(parser.getCurrentLocation(), "result count after 'x' must be positive");
-
-  SmallVector<Type> resultTypes(resultCount, outputType);
-  result.addTypes(resultTypes);
-  return success();
-}
-
 void PimSendBatchOp::print(OpAsmPrinter& printer) {
   printer << " ";
   printer.printOperand(getInput());
@@ -237,36 +174,6 @@ ParseResult PimSendBatchOp::parse(OpAsmParser& parser, OperationState& result) {
   return parser.resolveOperand(input, inputType, result.operands);
 }
 
-void PimSendManyOp::print(OpAsmPrinter& printer) {
-  printer << " ";
-  printCompressedValueSequence(printer, getInputs());
-  printCoreIdList(printer, "to", getTargetCoreIds());
-  printer.printOptionalAttrDict((*this)->getAttrs(), {getTargetCoreIdsAttrName().getValue()});
-  printer << " : ";
-  printCompressedTypeSequence(printer, TypeRange(getInputs()));
-}
-
-ParseResult PimSendManyOp::parse(OpAsmParser& parser, OperationState& result) {
-  SmallVector<OpAsmParser::UnresolvedOperand> inputs;
-  SmallVector<Type> inputTypes;
-  SmallVector<int32_t> targetCoreIds;
-
-  if (parseCompressedOperandSequence(parser, inputs) || parseOptionalCoreIdList(parser, "to", targetCoreIds)
-      || parser.parseOptionalAttrDict(result.attributes) || parser.parseColon()
-      || parseCompressedTypeSequence(parser, inputTypes, /*allowEmpty=*/false))
-    return failure();
-
-  if (inputs.size() != inputTypes.size())
-    return parser.emitError(parser.getCurrentLocation(), "number of inputs and input types must match");
-  if (!targetCoreIds.empty() && result.attributes.get("targetCoreIds"))
-    return parser.emitError(parser.getCurrentLocation(),
-                            "targetCoreIds cannot be specified both positionally and in attr-dict");
-  if (!targetCoreIds.empty())
-    result.addAttribute("targetCoreIds", getDenseI32ArrayAttr(parser, targetCoreIds));
-
-  return parser.resolveOperands(inputs, inputTypes, parser.getCurrentLocation(), result.operands);
-}
-
 void PimSendTensorOp::print(OpAsmPrinter& printer) {
   printer << " ";
   printer.printOperand(getInput());
@@ -294,72 +201,6 @@ ParseResult PimSendTensorOp::parse(OpAsmParser& parser, OperationState& result)
   return parser.resolveOperand(input, inputType, result.operands);
 }
 
-void PimSendManyBatchOp::print(OpAsmPrinter& printer) {
-  printer << " ";
-  printCompressedValueSequence(printer, getInputs());
-  printCoreIdList(printer, "to", getTargetCoreIds());
-  printer.printOptionalAttrDict((*this)->getAttrs(), {getTargetCoreIdsAttrName().getValue()});
-  printer << " : ";
-  printCompressedTypeSequence(printer, TypeRange(getInputs()));
-}
-
-ParseResult PimSendManyBatchOp::parse(OpAsmParser& parser, OperationState& result) {
-  SmallVector<OpAsmParser::UnresolvedOperand> inputs;
-  SmallVector<Type> inputTypes;
-  SmallVector<int32_t> targetCoreIds;
-
-  if (parseCompressedOperandSequence(parser, inputs) || parseOptionalCoreIdList(parser, "to", targetCoreIds)
-      || parser.parseOptionalAttrDict(result.attributes) || parser.parseColon()
-      || parseCompressedTypeSequence(parser, inputTypes, /*allowEmpty=*/false))
-    return failure();
-
-  if (inputs.size() != inputTypes.size())
-    return parser.emitError(parser.getCurrentLocation(), "number of inputs and input types must match");
-  if (!targetCoreIds.empty() && result.attributes.get("targetCoreIds"))
-    return parser.emitError(parser.getCurrentLocation(),
-                            "targetCoreIds cannot be specified both positionally and in attr-dict");
-  if (!targetCoreIds.empty())
-    result.addAttribute("targetCoreIds", getDenseI32ArrayAttr(parser, targetCoreIds));
-
-  return parser.resolveOperands(inputs, inputTypes, parser.getCurrentLocation(), result.operands);
-}
-
-void PimReceiveManyOp::print(OpAsmPrinter& printer) {
-  printCoreIdList(printer, "from", getSourceCoreIds());
-  printer << " into ";
-  printOpenDelimiter(printer, ListDelimiter::Paren);
-  printCompressedValueSequence(printer, getOutputBuffers());
-  printCloseDelimiter(printer, ListDelimiter::Paren);
-  printer.printOptionalAttrDict((*this)->getAttrs(), {getSourceCoreIdsAttrName().getValue()});
-  printer << " : ";
-  printCompressedTypeSequence(printer, getOutputs().getTypes());
-}
-
-ParseResult PimReceiveManyOp::parse(OpAsmParser& parser, OperationState& result) {
-  SmallVector<OpAsmParser::UnresolvedOperand> outputBuffers;
-  SmallVector<Type> outputTypes;
-  SmallVector<int32_t> sourceCoreIds;
-
-  if (parseOptionalCoreIdList(parser, "from", sourceCoreIds) || parser.parseKeyword("into") || parser.parseLParen()
-      || parseCompressedOperandSequence(parser, outputBuffers) || parser.parseRParen()
-      || parser.parseOptionalAttrDict(result.attributes) || parser.parseColon()
-      || parseCompressedTypeSequence(parser, outputTypes, /*allowEmpty=*/false))
-    return failure();
-
-  if (outputBuffers.size() != outputTypes.size())
-    return parser.emitError(parser.getCurrentLocation(), "number of output buffers and output types must match");
-  if (!sourceCoreIds.empty() && result.attributes.get("sourceCoreIds"))
-    return parser.emitError(parser.getCurrentLocation(),
-                            "sourceCoreIds cannot be specified both positionally and in attr-dict");
-  if (!sourceCoreIds.empty())
-    result.addAttribute("sourceCoreIds", getDenseI32ArrayAttr(parser, sourceCoreIds));
-
-  if (parser.resolveOperands(outputBuffers, outputTypes, parser.getCurrentLocation(), result.operands))
-    return failure();
-  result.addTypes(outputTypes);
-  return success();
-}
-
 void PimReceiveTensorOp::print(OpAsmPrinter& printer) {
   printCoreIdList(printer, "from", getSourceCoreIds());
   printer << " into ";
@@ -434,77 +275,6 @@ ParseResult PimReceiveBatchOp::parse(OpAsmParser& parser, OperationState& result
   return success();
 }
 
-void PimReceiveManyBatchOp::print(OpAsmPrinter& printer) {
-  printCoreIdList(printer, "from", getSourceCoreIds());
-  printer << " into ";
-  printOpenDelimiter(printer, ListDelimiter::Paren);
-  printCompressedValueSequence(printer, getOutputBuffers());
-  printCloseDelimiter(printer, ListDelimiter::Paren);
-  printer.printOptionalAttrDict((*this)->getAttrs(), {getSourceCoreIdsAttrName().getValue()});
-  printer << " : ";
-  printCompressedTypeSequence(printer, getOutputs().getTypes());
-}
-
-ParseResult PimReceiveManyBatchOp::parse(OpAsmParser& parser, OperationState& result) {
-  SmallVector<OpAsmParser::UnresolvedOperand> outputBuffers;
-  SmallVector<Type> outputTypes;
-  SmallVector<int32_t> sourceCoreIds;
-
-  if (parseOptionalCoreIdList(parser, "from", sourceCoreIds) || parser.parseKeyword("into") || parser.parseLParen()
-      || parseCompressedOperandSequence(parser, outputBuffers) || parser.parseRParen()
-      || parser.parseOptionalAttrDict(result.attributes) || parser.parseColon()
-      || parseCompressedTypeSequence(parser, outputTypes, /*allowEmpty=*/false))
-    return failure();
-
-  if (outputBuffers.size() != outputTypes.size())
-    return parser.emitError(parser.getCurrentLocation(), "number of output buffers and output types must match");
-  if (!sourceCoreIds.empty() && result.attributes.get("sourceCoreIds"))
-    return parser.emitError(parser.getCurrentLocation(),
-                            "sourceCoreIds cannot be specified both positionally and in attr-dict");
-  if (!sourceCoreIds.empty())
-    result.addAttribute("sourceCoreIds", getDenseI32ArrayAttr(parser, sourceCoreIds));
-
-  if (parser.resolveOperands(outputBuffers, outputTypes, parser.getCurrentLocation(), result.operands))
-    return failure();
-  result.addTypes(outputTypes);
-  return success();
-}
-
-void PimExtractRowsOp::print(OpAsmPrinter& printer) {
-  printer << " ";
-  printer.printOperand(getInput());
-  printer << " into ";
-  printOpenDelimiter(printer, ListDelimiter::Paren);
-  printCompressedValueSequence(printer, getOutputBuffers());
-  printCloseDelimiter(printer, ListDelimiter::Paren);
-  printer.printOptionalAttrDict((*this)->getAttrs());
-  printer << " : ";
-  printer.printType(getInput().getType());
-  printer << " -> ";
-  printCompressedTypeSequence(printer, getOutputs().getTypes());
-}
-
-ParseResult PimExtractRowsOp::parse(OpAsmParser& parser, OperationState& result) {
-  OpAsmParser::UnresolvedOperand input;
-  SmallVector<OpAsmParser::UnresolvedOperand> outputBuffers;
-  Type inputType;
-  SmallVector<Type> outputTypes;
-
-  if (parser.parseOperand(input) || parser.parseKeyword("into") || parser.parseLParen()
-      || parseCompressedOperandSequence(parser, outputBuffers) || parser.parseRParen()
-      || parser.parseOptionalAttrDict(result.attributes) || parser.parseColon() || parser.parseType(inputType)
-      || parser.parseArrow() || parseCompressedTypeSequence(parser, outputTypes, /*allowEmpty=*/false))
-    return failure();
-
-  if (outputBuffers.size() != outputTypes.size())
-    return parser.emitError(parser.getCurrentLocation(), "number of output buffers and output types must match");
-  if (parser.resolveOperand(input, inputType, result.operands)
-      || parser.resolveOperands(outputBuffers, outputTypes, parser.getCurrentLocation(), result.operands))
-    return failure();
-  result.addTypes(outputTypes);
-  return success();
-}
-
 void PimConcatOp::print(OpAsmPrinter& printer) {
   printer << " axis " << getAxis() << " ";
   printCompressedValueSequence(printer, getInputs());

src/PIM/Dialect/Pim/PimOpsVerify.cpp

@@ -13,12 +13,6 @@ namespace pim {
 
 namespace {
 
-static LogicalResult verifyManyCommunicationSizes(Operation* op, ArrayRef<int32_t> coreIds, size_t valueCount) {
-  if (coreIds.size() != valueCount)
-    return op->emitError("core id metadata length must match the number of values");
-  return success();
-}
-
 static bool haveSameShapedContainerKind(Type lhs, Type rhs) {
   return (isa<RankedTensorType>(lhs) && isa<RankedTensorType>(rhs)) || (isa<MemRefType>(lhs) && isa<MemRefType>(rhs));
 }
@@ -33,28 +27,6 @@ static LogicalResult verifyCompatibleShapedTypes(Operation* op, Type lhs, Type r
   return success();
 }
 
-static LogicalResult verifyManyCommunicationTypes(Operation* op, TypeRange types, StringRef kind) {
-  if (types.empty())
-    return op->emitError() << kind << " must carry at least one value";
-
-  Type firstType = types.front();
-  auto firstShapedType = dyn_cast<ShapedType>(firstType);
-  bool firstIsTensor = isa<RankedTensorType>(firstType);
-  bool firstIsMemRef = isa<MemRefType>(firstType);
-  for (Type type : types.drop_front())
-    if (type != firstType) {
-      auto shapedType = dyn_cast<ShapedType>(type);
-      if (!firstShapedType || !shapedType)
-        return op->emitError() << kind << " values must all have the same type";
-      if (firstIsTensor != isa<RankedTensorType>(type) || firstIsMemRef != isa<MemRefType>(type))
-        return op->emitError() << kind << " values must all use the same shaped container kind";
-      if (firstShapedType.getElementType() != shapedType.getElementType()
-          || firstShapedType.getShape() != shapedType.getShape())
-        return op->emitError() << kind << " values must all have the same shape and element type";
-    }
-  return success();
-}
-
 static LogicalResult verifyTensorCommunication(Operation* op, Type type, ArrayRef<int32_t> coreIds, StringRef kind) {
   if (coreIds.empty())
     return op->emitError() << kind << " must carry at least one chunk";
@@ -74,109 +46,12 @@ static LogicalResult verifyTensorCommunication(Operation* op, Type type, ArrayRe
   return success();
 }
 
-static FailureOr<int32_t> getParentBatchLaneCount(Operation* op) {
-  auto coreBatchOp = op->getParentOfType<PimCoreBatchOp>();
-  if (!coreBatchOp)
-    return failure();
-  return coreBatchOp.getLaneCount();
-}
-
-static LogicalResult verifyManyBatchCommunicationSizes(Operation* op, ArrayRef<int32_t> coreIds, size_t valueCount) {
-  auto laneCount = getParentBatchLaneCount(op);
-  if (failed(laneCount))
-    return op->emitError("must be nested inside pim.core_batch");
-  if (coreIds.size() != valueCount * static_cast<size_t>(*laneCount))
-    return op->emitError("core id metadata length must match the number of values times parent laneCount");
-  return success();
-}
-
 } // namespace
 
-LogicalResult PimEmptyManyOp::verify() {
-  if (getOutputs().empty())
-    return emitError("must produce at least one output");
-
-  Type firstType = getOutputs().front().getType();
-  auto firstShapedType = dyn_cast<ShapedType>(firstType);
-  if (!firstShapedType || !firstShapedType.hasRank())
-    return emitError("outputs must all be ranked shaped types");
-
-  for (Value output : getOutputs().drop_front())
-    if (output.getType() != firstType)
-      return emitError("outputs must all have the same type");
-
-  return success();
-}
-
-LogicalResult PimMapOp::verify() {
-  if (getInputs().empty())
-    return emitError("requires at least one input");
-  if (getOutputs().size() != getInputs().size())
-    return emitError("number of outputs must match number of inputs");
-
-  Type inputType = getInputs().front().getType();
-  for (Value input : getInputs().drop_front())
-    if (input.getType() != inputType)
-      return emitError("all inputs must have the same type");
-
-  Type outputType = getOutputs().front().getType();
-  for (Value output : getOutputs().drop_front())
-    if (output.getType() != outputType)
-      return emitError("all outputs must have the same type");
-
-  Block& block = getBody().front();
-  if (block.getNumArguments() != 1)
-    return emitError("body must have exactly one block argument");
-  if (failed(verifyCompatibleShapedTypes(
-        getOperation(), block.getArgument(0).getType(), inputType, "body block argument type must match input type")))
-    return emitError("body block argument type must match input type");
-
-  auto yieldOp = dyn_cast_or_null<PimYieldOp>(block.getTerminator());
-  if (!yieldOp)
-    return emitError("body must terminate with pim.yield");
-  if (yieldOp.getNumOperands() != 1)
-    return emitError("body yield must produce exactly one value");
-  if (failed(verifyCompatibleShapedTypes(
-        getOperation(), yieldOp.getOperand(0).getType(), outputType, "body yield type must match output type")))
-    return emitError("body yield type must match output type");
-
-  return success();
-}
-
-LogicalResult PimSendManyOp::verify() {
-  if (failed(verifyManyCommunicationSizes(getOperation(), getTargetCoreIds(), getInputs().size())))
-    return failure();
-  return verifyManyCommunicationTypes(getOperation(), getInputs().getTypes(), "send_many");
-}
-
 LogicalResult PimSendTensorOp::verify() {
   return verifyTensorCommunication(getOperation(), getInput().getType(), getTargetCoreIds(), "send_tensor");
 }
 
-LogicalResult PimSendManyBatchOp::verify() {
-  if (failed(verifyManyBatchCommunicationSizes(getOperation(), getTargetCoreIds(), getInputs().size())))
-    return failure();
-  return verifyManyCommunicationTypes(getOperation(), getInputs().getTypes(), "send_many_batch");
-}
-
-LogicalResult PimReceiveManyOp::verify() {
-  if (getOutputBuffers().size() != getOutputs().size())
-    return emitError("number of output buffers must match the number of outputs");
-  if (failed(verifyManyCommunicationSizes(getOperation(), getSourceCoreIds(), getOutputs().size())))
-    return failure();
-
-  if (failed(verifyManyCommunicationTypes(getOperation(), getOutputBuffers().getTypes(), "receive_many")))
-    return failure();
-  if (failed(verifyManyCommunicationTypes(getOperation(), getOperation()->getResultTypes(), "receive_many")))
-    return failure();
-
-  for (auto [outputBuffer, output] : llvm::zip(getOutputBuffers(), getOutputs()))
-    if (outputBuffer.getType() != output.getType())
-      return emitError("output buffers and outputs must have matching types");
-
-  return success();
-}
-
 LogicalResult PimReceiveTensorOp::verify() {
   if (failed(verifyCompatibleShapedTypes(
         getOperation(), getOutputBuffer().getType(), getOutput().getType(), "output buffer and output must match")))
@@ -185,61 +60,6 @@ LogicalResult PimReceiveTensorOp::verify() {
   return verifyTensorCommunication(getOperation(), getOutput().getType(), getSourceCoreIds(), "receive_tensor");
 }
 
-LogicalResult PimReceiveManyBatchOp::verify() {
-  if (getOutputBuffers().size() != getOutputs().size())
-    return emitError("number of output buffers must match the number of outputs");
-  if (failed(verifyManyBatchCommunicationSizes(getOperation(), getSourceCoreIds(), getOutputs().size())))
-    return failure();
-
-  if (failed(verifyManyCommunicationTypes(getOperation(), getOutputBuffers().getTypes(), "receive_many_batch")))
-    return failure();
-  if (failed(verifyManyCommunicationTypes(getOperation(), getOperation()->getResultTypes(), "receive_many_batch")))
-    return failure();
-
-  for (auto [outputBuffer, output] : llvm::zip(getOutputBuffers(), getOutputs()))
-    if (outputBuffer.getType() != output.getType())
-      return emitError("output buffers and outputs must have matching types");
-
-  return success();
-}
-
-LogicalResult PimExtractRowsOp::verify() {
-  if (getOutputBuffers().size() != getOutputs().size())
-    return emitError("number of output buffers must match the number of outputs");
-
-  auto inputType = dyn_cast<ShapedType>(getInput().getType());
-  if (!inputType || !inputType.hasRank() || inputType.getRank() != 2)
-    return emitError("input must be a rank-2 shaped type");
-
-  int64_t numRows = inputType.getShape()[0];
-  int64_t numCols = inputType.getShape()[1];
-  Type elementType = inputType.getElementType();
-
-  if (numRows >= 0 && static_cast<int64_t>(getOutputs().size()) != numRows)
-    return emitError("number of outputs must match the number of input rows");
-
-  for (auto [outputBuffer, output] : llvm::zip(getOutputBuffers(), getOutputs())) {
-    if (failed(verifyCompatibleShapedTypes(
-          getOperation(), outputBuffer.getType(), output.getType(), "output buffers and outputs must match")))
-      return failure();
-
-    auto outputType = dyn_cast<ShapedType>(output.getType());
-    if (!outputType || !outputType.hasRank() || outputType.getRank() != 2)
-      return emitError("outputs must all be rank-2 shaped types");
-    if (!haveSameShapedContainerKind(getInput().getType(), output.getType()))
-      return emitError("outputs must use the same shaped container kind as the input");
-    if (outputType.getElementType() != elementType)
-      return emitError("output element types must match input element type");
-    auto outputShape = outputType.getShape();
-    if (outputShape[0] != 1)
-      return emitError("each output must have exactly one row");
-    if (numCols >= 0 && outputShape[1] != numCols)
-      return emitError("output column count must match input column count");
-  }
-
-  return success();
-}
-
 LogicalResult PimConcatOp::verify() {
   if (getInputs().empty())
     return emitError("requires at least one input");

src/PIM/Dialect/Pim/Transforms/Bufferization/OpBufferizationInterfaces.cpp

@@ -180,39 +180,6 @@ struct ReceiveBatchOpInterface : DstBufferizableOpInterfaceExternalModel<Receive
   }
 };
 
-struct ReceiveManyOpInterface : DstBufferizableOpInterfaceExternalModel<ReceiveManyOpInterface, PimReceiveManyOp> {
-  bool bufferizesToMemoryRead(Operation* op, OpOperand& opOperand, const AnalysisState& state) const {
-    return !cast<DestinationStyleOpInterface>(op).isDpsInit(&opOperand);
-  }
-
-  LogicalResult bufferize(Operation* op,
-                          RewriterBase& rewriter,
-                          const BufferizationOptions& options,
-                          BufferizationState& state) const {
-    auto receiveOp = cast<PimReceiveManyOp>(op);
-    SmallVector<Value> outputBuffers;
-    SmallVector<Type> resultTypes;
-    outputBuffers.reserve(receiveOp.getOutputBuffers().size());
-    resultTypes.reserve(receiveOp.getOutputBuffers().size());
-
-    for (Value outputBuffer : receiveOp.getOutputBuffers()) {
-      auto outputBufferOpt = getBufferOrValue(rewriter, outputBuffer, options, state);
-      if (failed(outputBufferOpt))
-        return failure();
-      outputBuffers.push_back(*outputBufferOpt);
-      resultTypes.push_back(outputBufferOpt->getType());
-    }
-
-    auto newOp = PimReceiveManyOp::create(rewriter,
-                                          receiveOp.getLoc(),
-                                          TypeRange(resultTypes),
-                                          ValueRange(outputBuffers),
-                                          receiveOp.getSourceCoreIdsAttr());
-    rewriter.replaceOp(receiveOp, newOp.getOutputs());
-    return success();
-  }
-};
-
 struct ReceiveTensorOpInterface
 : DstBufferizableOpInterfaceExternalModel<ReceiveTensorOpInterface, PimReceiveTensorOp> {
   bool bufferizesToMemoryRead(Operation* op, OpOperand& opOperand, const AnalysisState& state) const {
@@ -234,77 +201,6 @@ struct ReceiveTensorOpInterface
   }
 };
 
-struct ReceiveManyBatchOpInterface
-: DstBufferizableOpInterfaceExternalModel<ReceiveManyBatchOpInterface, PimReceiveManyBatchOp> {
-  bool bufferizesToMemoryRead(Operation* op, OpOperand& opOperand, const AnalysisState& state) const {
-    return !cast<DestinationStyleOpInterface>(op).isDpsInit(&opOperand);
-  }
-
-  LogicalResult bufferize(Operation* op,
-                          RewriterBase& rewriter,
-                          const BufferizationOptions& options,
-                          BufferizationState& state) const {
-    auto receiveOp = cast<PimReceiveManyBatchOp>(op);
-    SmallVector<Value> outputBuffers;
-    SmallVector<Type> resultTypes;
-    outputBuffers.reserve(receiveOp.getOutputBuffers().size());
-    resultTypes.reserve(receiveOp.getOutputBuffers().size());
-
-    for (Value outputBuffer : receiveOp.getOutputBuffers()) {
-      auto outputBufferOpt = getBufferOrValue(rewriter, outputBuffer, options, state);
-      if (failed(outputBufferOpt))
-        return failure();
-      outputBuffers.push_back(*outputBufferOpt);
-      resultTypes.push_back(outputBufferOpt->getType());
-    }
-
-    auto newOp = PimReceiveManyBatchOp::create(rewriter,
-                                               receiveOp.getLoc(),
-                                               TypeRange(resultTypes),
-                                               ValueRange(outputBuffers),
-                                               receiveOp.getSourceCoreIdsAttr());
-    rewriter.replaceOp(receiveOp, newOp.getOutputs());
-    return success();
-  }
-};
-
-struct ExtractRowsOpInterface : DstBufferizableOpInterfaceExternalModel<ExtractRowsOpInterface, PimExtractRowsOp> {
-  bool bufferizesToMemoryRead(Operation* op, OpOperand& opOperand, const AnalysisState& state) const {
-    return !cast<DestinationStyleOpInterface>(op).isDpsInit(&opOperand);
-  }
-
-  LogicalResult bufferize(Operation* op,
-                          RewriterBase& rewriter,
-                          const BufferizationOptions& options,
-                          BufferizationState& state) const {
-    auto extractRowsOp = cast<PimExtractRowsOp>(op);
-    auto inputOpt = getBufferOrValue(rewriter, extractRowsOp.getInput(), options, state);
-    if (failed(inputOpt))
-      return failure();
-
-    SmallVector<Value> outputBuffers;
-    SmallVector<Type> resultTypes;
-    outputBuffers.reserve(extractRowsOp.getOutputBuffers().size());
-    resultTypes.reserve(extractRowsOp.getOutputBuffers().size());
-
-    for (Value outputBuffer : extractRowsOp.getOutputBuffers()) {
-      auto outputBufferOpt = getBufferOrValue(rewriter, outputBuffer, options, state);
-      if (failed(outputBufferOpt))
-        return failure();
-      outputBuffers.push_back(*outputBufferOpt);
-      resultTypes.push_back(outputBufferOpt->getType());
-    }
-
-    auto newOp = PimExtractRowsOp::create(rewriter,
-                                          extractRowsOp.getLoc(),
-                                          TypeRange(resultTypes),
-                                          materializeContiguousMemRef(*inputOpt, op->getLoc(), rewriter),
-                                          ValueRange(outputBuffers));
-    rewriter.replaceOp(extractRowsOp, newOp.getOutputs());
-    return success();
-  }
-};
-
 struct ConcatOpInterface : DstBufferizableOpInterfaceExternalModel<ConcatOpInterface, PimConcatOp> {
   bool bufferizesToMemoryRead(Operation* op, OpOperand& opOperand, const AnalysisState& state) const {
     return !cast<DestinationStyleOpInterface>(op).isDpsInit(&opOperand);
@@ -334,31 +230,6 @@ struct ConcatOpInterface : DstBufferizableOpInterfaceExternalModel<ConcatOpInter
   }
 };
 
-struct EmptyManyOpInterface : BufferizableOpInterface::ExternalModel<EmptyManyOpInterface, PimEmptyManyOp> {
-  bool bufferizesToAllocation(Operation* op, Value value) const { return true; }
-
-  bool resultBufferizesToMemoryWrite(Operation* op, OpResult opResult, const AnalysisState& state) const {
-    return false;
-  }
-
-  LogicalResult bufferize(Operation* op,
-                          RewriterBase& rewriter,
-                          const BufferizationOptions& options,
-                          BufferizationState& state) const {
-    auto emptyManyOp = cast<PimEmptyManyOp>(op);
-
-    SmallVector<Type> resultTypes;
-    resultTypes.reserve(emptyManyOp.getOutputs().size());
-    for (Value output : emptyManyOp.getOutputs()) {
-      auto shapedType = cast<ShapedType>(output.getType());
-      resultTypes.push_back(MemRefType::get(shapedType.getShape(), shapedType.getElementType()));
-    }
-
-    replaceOpWithNewBufferizedOp<PimEmptyManyOp>(rewriter, emptyManyOp, TypeRange(resultTypes));
-    return success();
-  }
-};
-
 struct SendTensorOpInterface : BufferizableOpInterface::ExternalModel<SendTensorOpInterface, PimSendTensorOp> {
   bool bufferizesToMemoryRead(Operation* op, OpOperand& opOperand, const AnalysisState& state) const { return true; }
 
@@ -383,7 +254,7 @@ struct SendTensorOpInterface : BufferizableOpInterface::ExternalModel<SendTensor
   }
 };
 
-struct MapOpInterface : BufferizableOpInterface::ExternalModel<MapOpInterface, PimMapOp> {
+struct SendOpInterface : BufferizableOpInterface::ExternalModel<SendOpInterface, PimSendOp> {
   bool bufferizesToMemoryRead(Operation* op, OpOperand& opOperand, const AnalysisState& state) const { return true; }
 
   bool bufferizesToMemoryWrite(Operation* op, OpOperand& opOperand, const AnalysisState& state) const { return false; }
@@ -392,75 +263,93 @@ struct MapOpInterface : BufferizableOpInterface::ExternalModel<MapOpInterface, P
     return {};
   }
 
-  AliasingOpOperandList getAliasingOpOperands(Operation* op, Value value, const AnalysisState& state) const {
-    auto mapOp = cast<PimMapOp>(op);
-    auto bbArg = dyn_cast<BlockArgument>(value);
-    if (!bbArg || bbArg.getOwner() != &mapOp.getBody().front() || bbArg.getArgNumber() != 0
-        || mapOp.getInputs().empty())
-      return {};
-
-    return {
-      {&mapOp->getOpOperand(0), BufferRelation::Equivalent}
-    };
-  }
-
-  bool isWritable(Operation* op, Value value, const AnalysisState& state) const { return false; }
-
-  FailureOr<BufferLikeType> getBufferType(Operation* op,
-                                          Value value,
+  LogicalResult bufferize(Operation* op,
+                          RewriterBase& rewriter,
                           const BufferizationOptions& options,
-                                          const BufferizationState& state,
-                                          SmallVector<Value>& invocationStack) const {
-    auto mapOp = cast<PimMapOp>(op);
-    auto bbArg = dyn_cast<BlockArgument>(value);
-    if (!bbArg || bbArg.getOwner() != &mapOp.getBody().front() || bbArg.getArgNumber() != 0
-        || mapOp.getInputs().empty())
+                          BufferizationState& state) const {
+    auto sendOp = cast<PimSendOp>(op);
+    auto inputOpt = getBufferOrValue(rewriter, sendOp.getInput(), options, state);
+    if (failed(inputOpt))
       return failure();
 
-    auto inputType = dyn_cast<BufferLikeType>(mapOp.getInputs().front().getType());
-    if (inputType)
-      return inputType;
+    replaceOpWithNewBufferizedOp<PimSendOp>(rewriter,
+                                            op,
+                                            materializeContiguousMemRef(*inputOpt, op->getLoc(), rewriter),
+                                            sendOp.getSizeAttr(),
+                                            sendOp.getTargetCoreIdAttr());
+    return success();
+  }
+};
 
-    auto shapedType = cast<ShapedType>(mapOp.getInputs().front().getType());
-    return BufferLikeType(MemRefType::get(shapedType.getShape(), shapedType.getElementType()));
+struct SendBatchOpInterface : BufferizableOpInterface::ExternalModel<SendBatchOpInterface, PimSendBatchOp> {
+  bool bufferizesToMemoryRead(Operation* op, OpOperand& opOperand, const AnalysisState& state) const { return true; }
+
+  bool bufferizesToMemoryWrite(Operation* op, OpOperand& opOperand, const AnalysisState& state) const { return false; }
+
+  AliasingValueList getAliasingValues(Operation* op, OpOperand& opOperand, const AnalysisState& state) const {
+    return {};
   }
 
   LogicalResult bufferize(Operation* op,
                           RewriterBase& rewriter,
                           const BufferizationOptions& options,
                           BufferizationState& state) const {
-    auto mapOp = cast<PimMapOp>(op);
-
-    SmallVector<Value> inputs;
-    SmallVector<Type> resultTypes;
-    inputs.reserve(mapOp.getInputs().size());
-    resultTypes.reserve(mapOp.getOutputs().size());
-
-    for (Value input : mapOp.getInputs()) {
-      if (isa<TensorType>(input.getType())) {
-        auto inputOpt = getBufferOrValue(rewriter, input, options, state);
+    auto sendOp = cast<PimSendBatchOp>(op);
+    auto inputOpt = getBufferOrValue(rewriter, sendOp.getInput(), options, state);
     if (failed(inputOpt))
       return failure();
-        inputs.push_back(*inputOpt);
+
+    replaceOpWithNewBufferizedOp<PimSendBatchOp>(rewriter,
+                                                 op,
+                                                 materializeContiguousMemRef(*inputOpt, op->getLoc(), rewriter),
+                                                 sendOp.getSizeAttr(),
+                                                 sendOp.getTargetCoreIdsAttr());
+    return success();
+  }
+};
+
+struct CoreOpInterface : BufferizableOpInterface::ExternalModel<CoreOpInterface, PimCoreOp> {
+  bool bufferizesToMemoryRead(Operation* op, OpOperand& opOperand, const AnalysisState& state) const { return true; }
+
+  bool bufferizesToMemoryWrite(Operation* op, OpOperand& opOperand, const AnalysisState& state) const { return false; }
+
+  AliasingValueList getAliasingValues(Operation* op, OpOperand& opOperand, const AnalysisState& state) const {
+    return {};
+  }
+
+  LogicalResult bufferize(Operation* op,
+                          RewriterBase& rewriter,
+                          const BufferizationOptions& options,
+                          BufferizationState& state) const {
+    auto coreOp = cast<PimCoreOp>(op);
+
+    bool alreadyBufferized =
+      llvm::all_of(coreOp.getWeights(), [](Value weight) { return isa<BufferLikeType>(weight.getType()); });
+    if (alreadyBufferized)
+      return success();
+
+    SmallVector<Value> weights;
+    weights.reserve(coreOp.getWeights().size());
+    for (Value weight : coreOp.getWeights()) {
+      if (isa<TensorType>(weight.getType())) {
+        auto weightOpt = getBufferOrValue(rewriter, weight, options, state);
+        if (failed(weightOpt))
+          return failure();
+        weights.push_back(*weightOpt);
       }
       else {
-        inputs.push_back(input);
+        weights.push_back(weight);
       }
     }
 
-    for (Value output : mapOp.getOutputs()) {
-      auto shapedType = cast<ShapedType>(output.getType());
-      resultTypes.push_back(MemRefType::get(shapedType.getShape(), shapedType.getElementType()));
-    }
-
-    rewriter.setInsertionPoint(mapOp);
-    auto newOp = PimMapOp::create(rewriter, mapOp.getLoc(), TypeRange(resultTypes), ValueRange(inputs));
-    rewriter.inlineRegionBefore(mapOp.getBody(), newOp.getBody(), newOp.getBody().begin());
+    rewriter.setInsertionPoint(coreOp);
+    auto newOp = PimCoreOp::create(rewriter, coreOp.getLoc(), ValueRange(weights), coreOp.getCoreIdAttr());
+    rewriter.inlineRegionBefore(coreOp.getBody(), newOp.getBody(), newOp.getBody().begin());
     for (Block& block : newOp.getBody())
       if (failed(bufferization::bufferizeBlockSignature(&block, rewriter, options, state)))
         return failure();
 
-    rewriter.replaceOp(mapOp, newOp.getOutputs());
+    rewriter.eraseOp(coreOp);
     return success();
   }
 };
@@ -730,16 +619,14 @@ struct UnaryDstOpInterface : DstBufferizableOpInterfaceExternalModel<UnaryDstOpI
 
 void registerOpBufferizationInterfaces(DialectRegistry& registry) {
   registry.addExtension(+[](MLIRContext* ctx, PimDialect* dialect) {
-    PimEmptyManyOp::attachInterface<EmptyManyOpInterface>(*ctx);
-    PimMapOp::attachInterface<MapOpInterface>(*ctx);
+    PimCoreOp::attachInterface<CoreOpInterface>(*ctx);
     PimCoreBatchOp::attachInterface<CoreBatchOpInterface>(*ctx);
     PimReceiveOp::attachInterface<ReceiveOpInterface>(*ctx);
-    PimReceiveManyOp::attachInterface<ReceiveManyOpInterface>(*ctx);
     PimReceiveTensorOp::attachInterface<ReceiveTensorOpInterface>(*ctx);
     PimReceiveBatchOp::attachInterface<ReceiveBatchOpInterface>(*ctx);
-    PimReceiveManyBatchOp::attachInterface<ReceiveManyBatchOpInterface>(*ctx);
+    PimSendOp::attachInterface<SendOpInterface>(*ctx);
+    PimSendBatchOp::attachInterface<SendBatchOpInterface>(*ctx);
     PimSendTensorOp::attachInterface<SendTensorOpInterface>(*ctx);
-    PimExtractRowsOp::attachInterface<ExtractRowsOpInterface>(*ctx);
     PimConcatOp::attachInterface<ConcatOpInterface>(*ctx);
     PimMemCopyHostToDevOp::attachInterface<MemCopyHostToDevOpInterface>(*ctx);
     PimMemCopyHostToDevBatchOp::attachInterface<MemCopyHostToDevBatchOpInterface>(*ctx);

src/PIM/Dialect/Pim/Transforms/Bufferization/PimBufferizationPass.cpp

@@ -1,10 +1,9 @@
 #include "mlir/Dialect/Bufferization/IR/Bufferization.h"
-#include "mlir/Dialect/Bufferization/Transforms/BufferViewFlowAnalysis.h"
 #include "mlir/Dialect/Bufferization/Transforms/OneShotAnalysis.h"
+#include "mlir/Dialect/Bufferization/Transforms/OneShotModuleBufferize.h"
 #include "mlir/Dialect/Func/IR/FuncOps.h"
 #include "mlir/Dialect/MemRef/IR/MemRef.h"
 #include "mlir/Dialect/Tensor/IR/Tensor.h"
-#include "mlir/IR/Threading.h"
 #include "mlir/IR/PatternMatch.h"
 #include "mlir/Pass/Pass.h"
 
@@ -47,53 +46,18 @@ private:
 
 void PimBufferizationPass::runOnOperation() {
   auto moduleOp = getOperation();
-  // Refactor this into a function
-  {
   auto funcOp = *getPimEntryFunc(moduleOp);
 
-    SmallVector<Operation*> coreOps;
-    funcOp->walk<WalkOrder::PreOrder>([&](Operation* op) {
-      if (isa<pim::PimCoreOp, pim::PimCoreBatchOp>(op))
-        coreOps.push_back(op);
-    });
-    MLIRContext* ctx = moduleOp.getContext();
-    // failableParallelForEach will run the lambda in parallel and stop if any thread fails
-    LogicalResult result = mlir::failableParallelForEach(ctx, coreOps, [&](Operation* coreOp) {
-      // Again, allocate state LOCALLY per thread/function
   bufferization::OneShotBufferizationOptions options;
   options.allowUnknownOps = true;
-      if (isa<pim::PimCoreBatchOp>(coreOp))
-        options.opFilter.denyOperation([coreOp](Operation* op) { return op == coreOp; });
-      bufferization::BufferizationState state;
-      if (failed(bufferization::runOneShotBufferize(coreOp, options, state))) {
-        coreOp->emitError("Failed to bufferize PIM and Spatial ops");
-        return failure();
-      }
-      return success();
-    });
-
-    if (failed(result)) {
-      moduleOp.emitError("Failed to bufferize-parallel PIM and Spatial ops");
-      signalPassFailure();
-    }
-
-    funcOp->walk([&](bufferization::ToTensorOp toTensorOp) {
-      if (llvm::isa_and_present<pim::PimCoreOp, pim::PimCoreBatchOp>(toTensorOp->getParentOp()))
-        toTensorOp->setAttr("restrict", UnitAttr::get(ctx));
-    });
-
-    // One-Shot-Bufferization
-    bufferization::OneShotBufferizationOptions options;
-    options.allowUnknownOps = true;
-    options.opFilter.denyOperation([](Operation* op) {
-      return op->getParentOfType<pim::PimCoreOp>() || op->getParentOfType<pim::PimCoreBatchOp>();
-    });
+  options.bufferizeFunctionBoundaries = true;
+  options.setFunctionBoundaryTypeConversion(bufferization::LayoutMapOption::IdentityLayoutMap);
   bufferization::BufferizationState state;
 
-    if (failed(bufferization::runOneShotBufferize(moduleOp, options, state))) {
+  if (failed(bufferization::runOneShotModuleBufferize(moduleOp, options, state))) {
     moduleOp.emitError("Failed to bufferize PIM and Spatial ops");
     signalPassFailure();
-    }
+    return;
   }
 
   MLIRContext* ctx = moduleOp.getContext();
@@ -119,30 +83,6 @@ void PimBufferizationPass::runOnOperation() {
     return;
   }
 
-  // Remove toTensor operations: leave memrefs instead
-  moduleOp.walk([](bufferization::ToTensorOp toTensorOp) {
-    toTensorOp.replaceAllUsesWith(toTensorOp.getBuffer());
-    toTensorOp.erase();
-  });
-
-  // Change main function return types from tensors to memrefs
-  func::FuncOp funcOp;
-  for (Operation& op : moduleOp.getBody()->getOperations())
-    if ((funcOp = dyn_cast<func::FuncOp>(&op)))
-      break;
-  auto oldFuncType = funcOp.getFunctionType();
-  SmallVector<Type> newResults;
-  bool changed = false;
-  for (Type type : oldFuncType.getResults())
-    if (auto tensorType = dyn_cast<RankedTensorType>(type)) {
-      newResults.push_back(MemRefType::get(tensorType.getShape(), tensorType.getElementType()));
-      changed = true;
-    }
-    else
-      newResults.push_back(type);
-  if (changed)
-    funcOp.setType(FunctionType::get(funcOp.getContext(), oldFuncType.getInputs(), newResults));
-
   annotateWeightsMemrefs(moduleOp, funcOp);
 
   // Dump to file for debug

src/PIM/Pass/PimCodegen/MaterializeHostConstantsPass.cpp

@@ -1,13 +1,12 @@
 #include "mlir/Dialect/Func/IR/FuncOps.h"
 #include "mlir/Dialect/MemRef/IR/MemRef.h"
 #include "mlir/IR/Builders.h"
-#include "mlir/IR/IRMapping.h"
 #include "mlir/IR/PatternMatch.h"
 #include "mlir/Pass/Pass.h"
 
 #include "llvm/ADT/DenseMap.h"
-#include "llvm/ADT/SmallVector.h"
 #include "llvm/ADT/STLExtras.h"
+#include "llvm/ADT/SmallVector.h"
 #include "llvm/Support/MathExtras.h"
 
 #include "src/Accelerators/PIM/Common/PimCommon.hpp"
@@ -34,35 +33,6 @@ static int64_t getValueSizeInBytes(Value value) {
   return type.getNumElements() * type.getElementTypeBitWidth() / 8;
 }
 
-static void expandPimMapOps(func::FuncOp funcOp, IRRewriter& rewriter) {
-  SmallVector<pim::PimMapOp> mapOps;
-  funcOp.walk([&](pim::PimMapOp mapOp) { mapOps.push_back(mapOp); });
-
-  for (auto mapOp : mapOps) {
-    Block& body = mapOp.getBody().front();
-    auto yieldOp = cast<pim::PimYieldOp>(body.getTerminator());
-
-    SmallVector<Value> replacements;
-    replacements.reserve(mapOp.getInputs().size());
-    rewriter.setInsertionPoint(mapOp);
-    for (Value input : mapOp.getInputs()) {
-      IRMapping mapping;
-      mapping.map(body.getArgument(0), input);
-
-      for (Operation& op : body.without_terminator()) {
-        Operation* cloned = rewriter.clone(op, mapping);
-        for (auto [originalResult, clonedResult] : llvm::zip(op.getResults(), cloned->getResults()))
-          mapping.map(originalResult, clonedResult);
-        rewriter.setInsertionPointAfter(cloned);
-      }
-
-      replacements.push_back(mapping.lookupOrDefault(yieldOp.getOperand(0)));
-    }
-
-    rewriter.replaceOp(mapOp, replacements);
-  }
-}
-
 struct MaterializeHostConstantsPass : PassWrapper<MaterializeHostConstantsPass, OperationPass<ModuleOp>> {
   MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(MaterializeHostConstantsPass)
 
@@ -80,8 +50,6 @@ struct MaterializeHostConstantsPass : PassWrapper<MaterializeHostConstantsPass,
       if (funcOp.isExternal())
         continue;
 
-      expandPimMapOps(funcOp, rewriter);
-
       for (pim::PimCoreOp coreOp : funcOp.getOps<pim::PimCoreOp>()) {
         DenseMap<Value, DenseMap<int64_t, DenseMap<Type, Value>>> materializedValues;
 
@@ -150,38 +118,11 @@ struct MaterializeHostConstantsPass : PassWrapper<MaterializeHostConstantsPass,
 
       SmallVector<Operation*> hostCompactOps;
       for (Operation& op : funcOp.getBody().front())
-        if (isa<pim::PimExtractRowsOp, pim::PimConcatOp>(op))
+        if (isa<pim::PimConcatOp>(op))
           hostCompactOps.push_back(&op);
 
       for (Operation* op : hostCompactOps) {
         rewriter.setInsertionPoint(op);
-
-        if (auto extractRowsOp = dyn_cast<pim::PimExtractRowsOp>(op)) {
-          auto inputType = dyn_cast<ShapedType>(extractRowsOp.getInput().getType());
-          if (!inputType || !inputType.hasStaticShape() || inputType.getRank() != 2) {
-            extractRowsOp.emitOpError("host-side extract_rows lowering requires a static rank-2 input");
-            hasFailure = true;
-            continue;
-          }
-
-          int64_t numCols = inputType.getDimSize(1);
-          SmallVector<Value> replacementRows;
-          replacementRows.reserve(extractRowsOp.getOutputs().size());
-          for (auto rowIndex : llvm::seq<size_t>(0, extractRowsOp.getOutputs().size())) {
-            SmallVector<OpFoldResult> offsets = {rewriter.getIndexAttr(static_cast<int64_t>(rowIndex)),
-                                                 rewriter.getIndexAttr(0)};
-            SmallVector<OpFoldResult> sizes = {rewriter.getIndexAttr(1), rewriter.getIndexAttr(numCols)};
-            SmallVector<OpFoldResult> strides = {rewriter.getIndexAttr(1), rewriter.getIndexAttr(1)};
-            replacementRows.push_back(memref::SubViewOp::create(
-                                        rewriter, extractRowsOp.getLoc(), extractRowsOp.getInput(), offsets, sizes, strides)
-                                        .getResult());
-          }
-
-          extractRowsOp->replaceAllUsesWith(ValueRange(replacementRows));
-          extractRowsOp->erase();
-          continue;
-        }
-
         auto concatOp = cast<pim::PimConcatOp>(op);
         concatOp.emitOpError("host-side concat must be folded away or lowered into pim.core before materialization");
         hasFailure = true;

src/PIM/Pass/PimCodegen/VerificationPass.cpp

@@ -18,7 +18,6 @@ namespace {
 
 static bool isAddressOnlyHostOp(Operation* op) {
   return isa<arith::ConstantOp,
-             pim::PimEmptyManyOp,
              memref::AllocOp,
              memref::GetGlobalOp,
              memref::SubViewOp,
@@ -37,12 +36,24 @@ static bool isBaseAddressableValue(Value value) {
     Operation* defOp = value.getDefiningOp();
     if (!defOp)
       return false;
-    if (isa<pim::PimEmptyManyOp, memref::AllocOp, memref::GetGlobalOp>(defOp))
+    if (isa<memref::AllocOp, memref::GetGlobalOp>(defOp))
       return true;
-    if (auto subview = dyn_cast<memref::SubViewOp>(defOp)) { value = subview.getSource(); continue; }
-    if (auto cast = dyn_cast<memref::CastOp>(defOp)) { value = cast.getSource(); continue; }
-    if (auto collapse = dyn_cast<memref::CollapseShapeOp>(defOp)) { value = collapse.getSrc(); continue; }
-    if (auto expand = dyn_cast<memref::ExpandShapeOp>(defOp)) { value = expand.getSrc(); continue; }
+    if (auto subview = dyn_cast<memref::SubViewOp>(defOp)) {
+      value = subview.getSource();
+      continue;
+    }
+    if (auto cast = dyn_cast<memref::CastOp>(defOp)) {
+      value = cast.getSource();
+      continue;
+    }
+    if (auto collapse = dyn_cast<memref::CollapseShapeOp>(defOp)) {
+      value = collapse.getSrc();
+      continue;
+    }
+    if (auto expand = dyn_cast<memref::ExpandShapeOp>(defOp)) {
+      value = expand.getSrc();
+      continue;
+    }
     return false;
   }
 }
@@ -52,7 +63,38 @@ static bool isCodegenAddressableValue(Value value) {
   if (failed(resolvedAddress))
     return false;
   return isa<BlockArgument>(resolvedAddress->base)
-      || isa<pim::PimEmptyManyOp, memref::AllocOp, memref::GetGlobalOp>(resolvedAddress->base.getDefiningOp());
+      || isa<memref::AllocOp, memref::GetGlobalOp>(resolvedAddress->base.getDefiningOp());
+}
+
+static bool isConstantGlobalView(Value value) {
+  auto allStaticSubviewParts = [](memref::SubViewOp subview) {
+    return llvm::all_of(subview.getStaticOffsets(), [](int64_t value) { return !ShapedType::isDynamic(value); })
+        && llvm::all_of(subview.getStaticSizes(), [](int64_t value) { return !ShapedType::isDynamic(value); })
+        && llvm::all_of(subview.getStaticStrides(), [](int64_t value) { return !ShapedType::isDynamic(value); });
+  };
+
+  while (true) {
+    Operation* defOp = value.getDefiningOp();
+    if (!defOp)
+      return false;
+    if (auto getGlobalOp = dyn_cast<memref::GetGlobalOp>(defOp)) {
+      auto moduleOp = getGlobalOp->getParentOfType<ModuleOp>();
+      auto globalOp = lookupGlobalForGetGlobal(moduleOp, getGlobalOp);
+      return globalOp && globalOp.getConstant() && globalOp.getInitialValue()
+          && isa<DenseElementsAttr>(*globalOp.getInitialValue());
+    }
+    if (auto subview = dyn_cast<memref::SubViewOp>(defOp)) {
+      if (!allStaticSubviewParts(subview))
+        return false;
+      value = subview.getSource();
+      continue;
+    }
+    if (auto cast = dyn_cast<memref::CastOp>(defOp)) {
+      value = cast.getSource();
+      continue;
+    }
+    return false;
+  }
 }
 
 static bool isExplicitHostOperand(Operation* op, unsigned operandIndex) {
@@ -125,13 +167,17 @@ private:
     bool hasFailure = false;
     for (auto [weightIndex, weight] : llvm::enumerate(coreOp.getWeights())) {
       auto getGlobalOp = weight.template getDefiningOp<memref::GetGlobalOp>();
-      if (!getGlobalOp) {
+      if (!getGlobalOp && !isConstantGlobalView(weight)) {
         coreOp.emitOpError() << "weight #" << weightIndex
-                             << " must be materialized as memref.get_global before JSON codegen";
+                             << " must be materialized as a constant memref.global or a static view of one before JSON "
+                                "codegen";
         hasFailure = true;
         continue;
       }
 
+      if (!getGlobalOp)
+        continue;
+
       auto globalOp = lookupGlobalForGetGlobal(moduleOp, getGlobalOp);
       if (!globalOp) {
         coreOp.emitOpError() << "weight #" << weightIndex << " references an unknown memref.global";
@@ -185,7 +231,7 @@ private:
             continue;
           }
 
-          if (!isa<pim::PimEmptyManyOp, memref::AllocOp>(resolvedAddress->base.getDefiningOp())) {
+          if (!isa<memref::AllocOp>(resolvedAddress->base.getDefiningOp())) {
             op.emitOpError() << "operand #" << operandIndex
                              << " must be backed by device-local memory; materialize host values with pim.memcp_hd";
             hasFailure = true;
@@ -197,7 +243,7 @@ private:
 
   static LogicalResult verifyAddressOnlyHostOp(Operation* op) {
     if (auto subviewOp = dyn_cast<memref::SubViewOp>(op))
-      return verifyAddressOnlySource(op, subviewOp.getSource());
+      return verifyAddressOnlyBase(op, subviewOp.getSource());
     if (auto castOp = dyn_cast<memref::CastOp>(op))
       return verifyAddressOnlySource(op, castOp.getSource());
     if (auto collapseOp = dyn_cast<memref::CollapseShapeOp>(op))
@@ -221,6 +267,14 @@ private:
     op->emitOpError("depends on a value that is not backed by contiguous addressable storage");
     return failure();
   }
+
+  static LogicalResult verifyAddressOnlyBase(Operation* op, Value source) {
+    if (isBaseAddressableValue(source))
+      return success();
+
+    op->emitOpError("depends on a value that is not backed by addressable storage");
+    return failure();
+  }
 };
 
 } // namespace

src/PIM/TODO.md

@@ -1,10 +0,0 @@
-Rimuovere la gestione delle send e recive da sptaialtopim (nuovo mergeNode)
-
-AnalisiDCP
-NuovoPasso che inserische le send e recive e gestisce gli input
-Passo che fa il merge
-
-Probabilmente questo rompera' gli input e come venivano gestiti prima.
-
-
-