Bundle individual memory pools into a single memory pool (#183)

* Reorganize main function.

* Follow review comments.

* Emit constants are globals in Krnl and LLVM dialects.

* Add memory pooling for constant sized arrays.

* Clean code.

* Clean code.

* Clean code.

* Add simple bundling test.

Co-authored-by: Tian Jin <tjingrant@gmail.com>

src/CMakeLists.txt

@@ -22,7 +22,8 @@ set(OMLibs
         OMElideConstants
         OMElideKrnlGlobalConstants
         OMPackKrnlGlobalConstants
-        OMEnableMemoryPool)
+        OMEnableMemoryPool
+        OMBundleMemoryPools)
 set(OMLibs ${OMLibs} PARENT_SCOPE)
 
 message(SATUS "OMLibs" ${OMLibs})

src/Conversion/ONNXToKrnl/ONNXToKrnlCommon.cpp

@@ -461,3 +461,28 @@ Value emitNegativeInfinityConstantOp(
 int64_t ArrayAttrIntVal(ArrayAttr a, int i) {
   return (a.getValue()[i]).cast<IntegerAttr>().getInt();
 }
+
+bool checkOpResultIsUsedByGetRef(AllocOp *allocOp) {
+  auto parentBlock = allocOp->getOperation()->getBlock();
+
+  bool opIsUsedInGetRef = false;
+  parentBlock->walk([&opIsUsedInGetRef, allocOp](KrnlGetRefOp op) {
+    auto result = allocOp->getResult();
+    for (const auto &operand : op.getOperands())
+      if (operand == result)
+        opIsUsedInGetRef = true;
+  });
+
+  return opIsUsedInGetRef;
+}
+
+// TODO: support dynamic sizes.
+int64_t getMemRefSizeInBytes(Value val) {
+  auto memRefType = convertToMemRefType(val.getType());
+  auto memRefShape = memRefType.getShape();
+  int64_t size = 1;
+  for (int i = 0; i < memRefShape.size(); i++)
+    size *= memRefShape[i];
+  size *= getMemRefEltSizeInBytes(memRefType);
+  return size;
+}

src/Conversion/ONNXToKrnl/ONNXToKrnlCommon.hpp

@@ -242,3 +242,7 @@ void populateLoweringONNXSqueezeOpPattern(
 
 void populateLoweringONNXSplitOpPattern(
     OwningRewritePatternList &patterns, MLIRContext *ctx);
+
+bool checkOpResultIsUsedByGetRef(AllocOp *allocOp);
+
+int64_t getMemRefSizeInBytes(Value val);

src/InitOMPasses.hpp

@@ -42,6 +42,12 @@ void initOMPasses() {
         return mlir::createKrnlEnableMemoryPoolPass();
       });
 
+  mlir::registerPass("bundle-memory-pools",
+      "Bundle memory pools of internal MemRefs into a single memory pool.",
+      []() -> std::unique_ptr<mlir::Pass> {
+        return mlir::createKrnlBundleMemoryPoolsPass();
+      });
+
   mlir::registerPass(
       "lower-krnl", "Lower Krnl dialect.", []() -> std::unique_ptr<mlir::Pass> {
         return mlir::createLowerKrnlPass();

src/MainUtils.cpp

@@ -269,6 +269,8 @@ void addONNXToKrnlPasses(mlir::PassManager &pm) {
 
   // TODO: make this pass optional:
   pm.addPass(mlir::createKrnlEnableMemoryPoolPass());
+  pm.addPass(mlir::createKrnlBundleMemoryPoolsPass());
+  pm.addPass(mlir::createCanonicalizerPass());
 }
 
 void addKrnlToAffinePasses(mlir::PassManager &pm) {

src/Pass/Passes.hpp

@@ -31,6 +31,9 @@ std::unique_ptr<Pass> createElideConstantValuePass();
 /// Pass for enabling a memory pool for MemRefs.
 std::unique_ptr<Pass> createKrnlEnableMemoryPoolPass();
 
+/// Pass for enabling a memory pool for MemRefs.
+std::unique_ptr<Pass> createKrnlBundleMemoryPoolsPass();
+
 /// Add pass for lowering to Krnl IR.
 std::unique_ptr<Pass> createLowerToKrnlPass();
 

src/Transform/BundleMemoryPools.cpp

@@ -0,0 +1,148 @@
+//===-- BundleMemoryPools.cpp - Bundle Memory Pools for  internal MemRefs -===//
+//
+// Copyright 2019-2020 The IBM Research Authors.
+//
+// =============================================================================
+//
+// For certain cases the number of individual memory allocations required for
+// all internal tensors is large and needs to be mitigated. This pass bundles
+// all the internal MemRef memory pools emitted by the EnableMemoryPool pass
+// int a single memory pool.
+//
+//===----------------------------------------------------------------------===//
+
+#include "mlir/Dialect/Affine/IR/AffineOps.h"
+#include "mlir/Dialect/StandardOps/IR/Ops.h"
+#include "mlir/Pass/Pass.h"
+#include "mlir/Transforms/DialectConversion.h"
+
+#include "src/Conversion/ONNXToKrnl/ONNXToKrnlCommon.hpp"
+#include "src/Dialect/Krnl/KrnlOps.hpp"
+#include "src/Pass/Passes.hpp"
+
+using namespace mlir;
+
+namespace {
+
+KrnlGetRefOp getUnbundledGetRef(AllocOp *memPool) {
+  auto parentBlock = memPool->getOperation()->getBlock();
+
+  KrnlGetRefOp unbundledGetRef = nullptr;
+  parentBlock->walk([&unbundledGetRef, memPool](KrnlGetRefOp op) {
+    auto result = memPool->getResult();
+    if (op.getOperands()[0] != result)
+      unbundledGetRef = op;
+  });
+
+  return unbundledGetRef;
+}
+
+/*!
+ *  RewritePattern that replaces:
+ *    %mem1 = alloc() : memref<<dims1>x<type>>
+ *    %mem2 = alloc() : memref<<dims2>x<type>>
+ *    %1 = krnl.getref %mem2 0 : memref<<dims2>x<type>>
+ *  =>
+ *    %mem1 = alloc() : memref<<dims1 + dims2>x<type>>
+ *    %1 = krnl.getref %mem1 <dims1> : memref<<dims2>x<type>>
+ *
+ *
+ *  ASSUMPTION: All krnl.getref operations in the program have been emitted
+ *              by the EnableMemoryPool pass i.e. there are no krnl.getref
+ *              operations which are not related to the memory pool.
+ *              krnl.getref is an operation specific to memory management
+ *              for other use cases use MLIR Standard dialect operations.
+ *              This assumption simplifies the code and avoids additional
+ *              checks to ensure that all the participating krnl.getref
+ *              operations are part of memory pooling.
+ */
+
+class KrnlBundleMemoryPools : public OpRewritePattern<AllocOp> {
+public:
+  using OpRewritePattern<AllocOp>::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(
+      AllocOp allocOp, PatternRewriter &rewriter) const override {
+    auto loc = allocOp.getLoc();
+
+    auto memRefType = convertToMemRefType(allocOp.getResult().getType());
+    auto memRefShape = memRefType.getShape();
+
+    // If alloca result is not used by getref then it cannot be part of
+    // the memory pool.
+    if (!checkOpResultIsUsedByGetRef(&allocOp))
+      return failure();
+
+    // Alloc memory type must be byte.
+    if (getMemRefEltSizeInBytes(memRefType) != 1)
+      return failure();
+
+    // Rank of the allocated MemRef must be 1.
+    if (memRefShape.size() != 1)
+      return failure();
+
+    // TODO: Change this when dyanmic shapes are supported.
+    // TODO: Add support for dynamic shapes.
+    int64_t currentMemPoolSize = memRefShape[0];
+
+    // Get a KrnlGetRefOp which does not use the current alloc.
+    if (KrnlGetRefOp unbundledGetRef = getUnbundledGetRef(&allocOp)) {
+      unbundledGetRef.dump();
+
+      // Current memory pool size is the offset for the newly bundled
+      // internal MemRef. Emit the offset as a constant.
+      auto offset = rewriter.create<ConstantOp>(
+          loc, rewriter.getIntegerAttr(
+                   rewriter.getIntegerType(64), currentMemPoolSize));
+
+      // Size in bytes of the output of the krnl.getref operation.
+      int64_t unbundledTotalSize =
+          getMemRefSizeInBytes(unbundledGetRef.getResult());
+
+      // Compute new size.
+      int64_t bundleTotalSize = unbundledTotalSize + currentMemPoolSize;
+
+      // We need to emit a new alloc which contains the additional MemRef.
+      SmallVector<int64_t, 1> newMemPoolShape;
+      newMemPoolShape.emplace_back(bundleTotalSize);
+      auto bundledMemPoolMemRefType =
+          MemRefType::get(newMemPoolShape, rewriter.getIntegerType(8));
+      auto bundledAlloc =
+          rewriter.create<AllocOp>(loc, bundledMemPoolMemRefType);
+
+      // The newly bundled MemRef expressed as a KrnlGetRefOp.
+      auto bundledMemRef = rewriter.create<KrnlGetRefOp>(
+          loc, unbundledGetRef.getResult().getType(), bundledAlloc, offset);
+      rewriter.replaceOp(unbundledGetRef, bundledMemRef.getResult());
+
+      // Replace old memory pool with new one.
+      rewriter.replaceOp(allocOp, bundledAlloc.getResult());
+
+      return success();
+    }
+
+    return failure();
+  }
+};
+
+/*!
+ *  Function pass that enables memory pooling for MemRefs.
+ */
+class KrnlBundleMemoryPoolsPass
+    : public PassWrapper<KrnlBundleMemoryPoolsPass, FunctionPass> {
+public:
+  void runOnFunction() override {
+    auto function = getFunction();
+
+    ConversionTarget target(getContext());
+    OwningRewritePatternList patterns;
+    patterns.insert<KrnlBundleMemoryPools>(&getContext());
+
+    applyPatternsAndFoldGreedily(function, patterns);
+  }
+};
+} // namespace
+
+std::unique_ptr<Pass> mlir::createKrnlBundleMemoryPoolsPass() {
+  return std::make_unique<KrnlBundleMemoryPoolsPass>();
+}

src/Transform/CMakeLists.txt

@@ -46,6 +46,8 @@ target_include_directories(OMPackKrnlGlobalConstants
         ${ONNX_MLIR_SRC_ROOT}
         ${ONNX_MLIR_BIN_ROOT}
         ${ONNX_MLIR_SRC_ROOT})
+add_dependencies(OMPackKrnlGlobalConstants
+        OMKrnlOps)
 
 add_library(OMEnableMemoryPool
         EnableMemoryPool.cpp)
@@ -54,13 +56,23 @@ target_include_directories(OMEnableMemoryPool
         ${ONNX_MLIR_SRC_ROOT}
         ${ONNX_MLIR_BIN_ROOT}
         ${ONNX_MLIR_SRC_ROOT})
-add_dependencies(OMPackKrnlGlobalConstants
-        OMKrnlOps)
-
 target_link_libraries(OMEnableMemoryPool
         onnx)
 add_dependencies(OMEnableMemoryPool
         OMKrnlOps
         OMONNXOps)
 
+add_library(OMBundleMemoryPools
+        BundleMemoryPools.cpp)
+target_include_directories(OMBundleMemoryPools
+        PRIVATE
+        ${ONNX_MLIR_SRC_ROOT}
+        ${ONNX_MLIR_BIN_ROOT}
+        ${ONNX_MLIR_SRC_ROOT})
+target_link_libraries(OMBundleMemoryPools
+        onnx)
+add_dependencies(OMBundleMemoryPools
+        OMKrnlOps
+        OMONNXOps)
+
 add_subdirectory(ONNX)

src/Transform/EnableMemoryPool.cpp

@@ -37,20 +37,6 @@ bool checkOpResultIsReturned(AllocOp *allocOp) {
   return opIsReturned;
 }
 
-bool checkOpResultIsUsedByGetRef(AllocOp *allocOp) {
-  auto parentBlock = allocOp->getOperation()->getBlock();
-
-  bool opIsUsedInGetRef = false;
-  parentBlock->walk([&opIsUsedInGetRef, allocOp](KrnlGetRefOp op) {
-    auto result = allocOp->getResult();
-    for (const auto &operand : op.getOperands())
-      if (operand == result)
-        opIsUsedInGetRef = true;
-  });
-
-  return opIsUsedInGetRef;
-}
-
 /*!
  *  RewritePattern that replaces:
  *    %0 = alloc() : memref<<dims>x<type>>
@@ -84,11 +70,7 @@ public:
       return failure();
 
     // Compute total size.
-    auto memRefShape = memRefType.getShape();
-    int64_t totalSize = 1;
-    for (int i = 0; i < memRefShape.size(); i++)
-      totalSize *= memRefShape[i];
-    totalSize *= getMemRefEltSizeInBytes(memRefType);
+    int64_t totalSize = getMemRefSizeInBytes(allocOp.getResult());
 
     // Emit new alloc.
     SmallVector<int64_t, 1> memPoolShape;

test/mlir/krnl/krnl_bundle_memory_pool.mlir

@@ -0,0 +1,53 @@
+// RUN: onnx-mlir-opt --bundle-memory-pools --canonicalize %s -split-input-file | FileCheck %s
+
+func @test_pool_bundling(%arg0: memref<10x10xf32>, %arg1: memref<10x20xf32>) -> memref<10x20xf32> {
+  %c0_i64 = constant 0 : i64
+  %ind = constant 0 : index
+  %cst = constant 0.000000e+00 : f32
+  %0 = alloc() : memref<10x20xf32>
+  %1 = alloc() : memref<800xi8>
+  %2 = "krnl.getref"(%1, %c0_i64) : (memref<800xi8>, i64) -> memref<10x20xf32>
+  %3 = alloc() : memref<400xi8>
+  %4 = "krnl.getref"(%3, %c0_i64) : (memref<400xi8>, i64) -> memref<10x10xf32>
+  %5 = alloc() : memref<800xi8>
+  %6 = "krnl.getref"(%5, %c0_i64) : (memref<800xi8>, i64) -> memref<10x20xf32>
+  %7 = alloc() : memref<800xi8>
+  %8 = "krnl.getref"(%7, %c0_i64) : (memref<800xi8>, i64) -> memref<10x20xf32>
+  %9 = alloc() : memref<400xi8>
+  %10 = "krnl.getref"(%9, %c0_i64) : (memref<400xi8>, i64) -> memref<10x10xf32>
+  affine.store %cst, %10[%ind, %ind] : memref<10x10xf32>
+  affine.store %cst, %8[%ind, %ind] : memref<10x20xf32>
+  affine.store %cst, %6[%ind, %ind] : memref<10x20xf32>
+  affine.store %cst, %4[%ind, %ind] : memref<10x10xf32>
+  affine.store %cst, %2[%ind, %ind] : memref<10x20xf32>
+  affine.store %cst, %0[%ind, %ind] : memref<10x20xf32>
+  dealloc %9 : memref<400xi8>
+  dealloc %7 : memref<800xi8>
+  dealloc %5 : memref<800xi8>
+  dealloc %3 : memref<400xi8>
+  dealloc %1 : memref<800xi8>
+  return %0 : memref<10x20xf32>
+
+  // CHECK-LABEL: test_pool_bundling
+  // CHECK: [[CONST_0:%.+]] = constant 0 : i64
+  // CHECK: [[CONST_CST:%.+]] = constant 0.000000e+00 : f32
+  // CHECK: [[CONST_400:%.+]] = constant 400 : i64
+  // CHECK: [[CONST_1200:%.+]] = constant 1200 : i64
+  // CHECK: [[CONST_2000:%.+]] = constant 2000 : i64
+  // CHECK: [[CONST_2400:%.+]] = constant 2400 : i64
+  // CHECK: [[RES:%.+]] = alloc() : memref<10x20xf32>
+  // CHECK: [[MEMPOOL:%.+]] = alloc() : memref<3200xi8>
+  // CHECK: [[MEMREF1:%.+]] = "krnl.getref"([[MEMPOOL]], [[CONST_2400]]) : (memref<3200xi8>, i64) -> memref<10x20xf32>
+  // CHECK: [[MEMREF2:%.+]] = "krnl.getref"([[MEMPOOL]], [[CONST_2000]]) : (memref<3200xi8>, i64) -> memref<10x10xf32>
+  // CHECK: [[MEMREF3:%.+]] = "krnl.getref"([[MEMPOOL]], [[CONST_1200]]) : (memref<3200xi8>, i64) -> memref<10x20xf32>
+  // CHECK: [[MEMREF4:%.+]] = "krnl.getref"([[MEMPOOL]], [[CONST_400]]) : (memref<3200xi8>, i64) -> memref<10x20xf32>
+  // CHECK: [[MEMREF5:%.+]] = "krnl.getref"([[MEMPOOL]], [[CONST_0]]) : (memref<3200xi8>, i64) -> memref<10x10xf32>
+  // CHECK: affine.store %cst, [[MEMREF5]][0, 0] : memref<10x10xf32>
+  // CHECK: affine.store %cst, [[MEMREF4]][0, 0] : memref<10x20xf32>
+  // CHECK: affine.store %cst, [[MEMREF3]][0, 0] : memref<10x20xf32>
+  // CHECK: affine.store %cst, [[MEMREF2]][0, 0] : memref<10x10xf32>
+  // CHECK: affine.store %cst, [[MEMREF1]][0, 0] : memref<10x20xf32>
+  // CHECK: affine.store %cst, [[RES]][0, 0] : memref<10x20xf32>
+  // CHECK: dealloc [[MEMPOOL]] : memref<3200xi8>
+  // CHECK: return [[RES]] : memref<10x20xf32>
+}

test/mlir/onnx/onnx_bundle_memory_pool.mlir

@@ -0,0 +1,28 @@
+// RUN: onnx-mlir-opt --shape-inference --lower-frontend --enable-memory-pool --bundle-memory-pools --canonicalize %s -split-input-file | FileCheck %s
+
+func @test_bundle_memory_pool(%arg0: tensor<10x10xf32>, %arg1: tensor<10x20xf32>) -> tensor<10x20xf32> {
+  %0 = "onnx.Add"(%arg0, %arg0) : (tensor<10x10xf32>, tensor<10x10xf32>) -> tensor<10x10xf32>
+  %1 = "onnx.MatMul"(%0, %arg1) : (tensor<10x10xf32>, tensor<10x20xf32>) -> tensor<10x20xf32>
+  %2 = "onnx.Add"(%1, %arg1) : (tensor<10x20xf32>, tensor<10x20xf32>) -> tensor<10x20xf32>
+  %3 = "onnx.Add"(%0, %arg0) : (tensor<10x10xf32>, tensor<10x10xf32>) -> tensor<10x10xf32>
+  %4 = "onnx.MatMul"(%3, %arg1) : (tensor<10x10xf32>, tensor<10x20xf32>) -> tensor<10x20xf32>
+  %5 = "onnx.Add"(%4, %arg1) : (tensor<10x20xf32>, tensor<10x20xf32>) -> tensor<10x20xf32>
+  return %5 : tensor<10x20xf32>
+
+  // CHECK-LABEL: test_bundle_memory_pool
+  // CHECK: [[CONST0:%.+]] = constant 0 : i64
+  // CHECK: [[CONST00:%.+]] = constant 0.000000e+00 : f32
+  // CHECK: [[CONST400:%.+]] = constant 400 : i64
+  // CHECK: [[CONST1200:%.+]] = constant 1200 : i64
+  // CHECK: [[CONST2000:%.+]] = constant 2000 : i64
+  // CHECK: [[CONST2400:%.+]] = constant 2400 : i64
+  // CHECK: [[RES:%.+]] = alloc() : memref<10x20xf32>
+  // CHECK: [[MEMPOOL:%.+]] = alloc() : memref<3200xi8>
+  // CHECK: "krnl.getref"([[MEMPOOL]], [[CONST2400]]) : (memref<3200xi8>, i64) -> memref<10x20xf32>
+  // CHECK: "krnl.getref"([[MEMPOOL]], [[CONST2000]]) : (memref<3200xi8>, i64) -> memref<10x10xf32>
+  // CHECK: "krnl.getref"([[MEMPOOL]], [[CONST1200]]) : (memref<3200xi8>, i64) -> memref<10x20xf32>
+  // CHECK: "krnl.getref"([[MEMPOOL]], [[CONST400]]) : (memref<3200xi8>, i64) -> memref<10x20xf32>
+  // CHECK: "krnl.getref"([[MEMPOOL]], [[CONST0]]) : (memref<3200xi8>, i64) -> memref<10x10xf32>
+  // CHECK: dealloc [[MEMPOOL]] : memref<3200xi8>
+  // CHECK: return [[RES]] : memref<10x20xf32>
+}