huge refactor for high RewritePatterns usage and less ad-hoc cpp code

remove Spatial many ops in favor of tensor ops like in pim

src/PIM/Compiler/PimArtifactWriter.cpp

@@ -0,0 +1,123 @@
+#include "mlir/Dialect/MemRef/IR/MemRef.h"
+
+#include "llvm/ADT/SmallPtrSet.h"
+#include "llvm/Support/FileSystem.h"
+#include "llvm/Support/raw_ostream.h"
+
+#include <algorithm>
+#include <cassert>
+#include <cstring>
+#include <vector>
+
+#include "src/Accelerators/PIM/Common/IR/WeightUtils.hpp"
+#include "src/Accelerators/PIM/Compiler/PimArtifactWriter.hpp"
+#include "src/Accelerators/PIM/Compiler/PimCodeGen.hpp"
+#include "src/Accelerators/PIM/Compiler/PimCompilerOptions.hpp"
+
+using namespace llvm;
+using namespace mlir;
+
+namespace onnx_mlir {
+
+OnnxMlirCompilerErrorCodes writeHostCoreJson(StringRef outputDirPath) {
+  std::error_code errorCode;
+  std::string outputHostCorePath = outputDirPath.str() + "/core_0.json";
+  raw_fd_ostream hostFileStream(outputHostCorePath, errorCode);
+  if (errorCode) {
+    errs() << "Error while opening host core file `" << outputHostCorePath << "`: " << errorCode.message() << '\n';
+    return InvalidOutputFileAccess;
+  }
+
+  // The host core json contains two no-op-like instructions to satisfy pimsim-nn.
+  hostFileStream << "[{\"imm\":0,\"op\":\"sldi\",\"rd\":0},{\"imm\":0,\"op\":\"sldi\",\"rd\":0}]";
+  hostFileStream.close();
+  return CompilerSuccess;
+}
+
+OnnxMlirCompilerErrorCodes
+writeMemoryBinary(ModuleOp moduleOp, func::FuncOp funcOp, PimAcceleratorMemory& memory, StringRef outputDirPath) {
+  auto memoryFilePath = (outputDirPath + "/memory.bin").str();
+  std::error_code errorCode;
+  raw_fd_ostream memoryFileStream(memoryFilePath, errorCode, sys::fs::OF_None);
+  if (errorCode) {
+    errs() << "Error while opening memory file " << memoryFilePath << ": " << errorCode.message() << '\n';
+    return InvalidOutputFileAccess;
+  }
+
+  std::vector<char> memoryBuffer(memory.hostMem.getFirstAvailableAddress(), 0);
+
+  SmallPtrSet<Operation*, 16> writtenGlobals;
+  funcOp.walk([&](memref::GetGlobalOp getGlobalOp) {
+    if (hasWeightAlways(getGlobalOp))
+      return;
+    auto globalOp = lookupGlobalForGetGlobal(moduleOp, getGlobalOp);
+    if (!globalOp)
+      return;
+    if (!writtenGlobals.insert(globalOp.getOperation()).second)
+      return;
+    auto initialValue = globalOp.getInitialValue();
+    if (!initialValue)
+      return;
+    auto denseAttr = dyn_cast<DenseElementsAttr>(*initialValue);
+    if (!denseAttr)
+      return;
+
+    MemEntry memEntry = memory.hostMem.getMemEntry(getGlobalOp.getResult());
+    ArrayRef<char> rawData = denseAttr.getRawData();
+    char* dst = memoryBuffer.data() + memEntry.address;
+
+    if (denseAttr.isSplat()) {
+      size_t elementSize = rawData.size();
+      assert(elementSize * getGlobalOp.getType().getNumElements() == memEntry.size && "Data size mismatch");
+      for (size_t offset = 0; offset < memEntry.size; offset += elementSize)
+        std::memcpy(dst + offset, rawData.data(), std::min(elementSize, memEntry.size - offset));
+    }
+    else {
+      assert(rawData.size() == memEntry.size && "Data size mismatch");
+      std::memcpy(dst, rawData.data(), rawData.size());
+    }
+  });
+
+  memoryFileStream.write(memoryBuffer.data(), memoryBuffer.size());
+  memoryFileStream.close();
+  return CompilerSuccess;
+}
+
+OnnxMlirCompilerErrorCodes writeConfigJson(func::FuncOp funcOp,
+                                           PimAcceleratorMemory& memory,
+                                           size_t maxCoreId,
+                                           json::Object xbarsPerArrayGroup,
+                                           StringRef outputDirPath) {
+  json::Object configJson;
+
+  configJson["core_cnt"] = maxCoreId + 1;
+  configJson["adc_count"] = 16;
+  configJson["cell_precision"] = 2;
+  configJson["xbar_array_count"] = crossbarCountInCore.getValue();
+  configJson["xbar_size"] = {crossbarSize.getValue(), crossbarSize.getValue()};
+  configJson["array_group_map"] = std::move(xbarsPerArrayGroup);
+
+  json::Array inputsAddresses;
+  for (BlockArgument input : funcOp.getArguments())
+    inputsAddresses.push_back(memory.getValueAddress(input));
+  configJson["inputs_addresses"] = std::move(inputsAddresses);
+
+  json::Array outputsAddresses;
+  for (func::ReturnOp returnOp : funcOp.getOps<func::ReturnOp>())
+    for (mlir::Value output : returnOp.getOperands())
+      outputsAddresses.push_back(memory.getValueAddress(output));
+  configJson["outputs_addresses"] = std::move(outputsAddresses);
+
+  auto configPath = (outputDirPath + "/config.json").str();
+  std::error_code errorCode;
+  raw_fd_ostream jsonOS(configPath, errorCode);
+  if (errorCode) {
+    errs() << "Error while opening config file: " << errorCode.message() << '\n';
+    return InvalidOutputFileAccess;
+  }
+  jsonOS << json::Value(std::move(configJson)) << '\n';
+  jsonOS.close();
+  return CompilerSuccess;
+}
+
+} // namespace onnx_mlir