[midend-LoopAnalysis]移除基本循环特征分析中的向量化并行化内容，增加循环向量化并行化特征分析遍，TODO：构建循环优化遍验证分析遍正确性

2025-08-09 13:53:00 +08:00
parent bd23f6154d
commit ac3358d7e3
7 changed files with 1473 additions and 303 deletions
--- a/src/include/midend/Pass/Analysis/LoopVectorization.h
+++ b/src/include/midend/Pass/Analysis/LoopVectorization.h
@@ -0,0 +1,250 @@
+#pragma once
+
+#include "Pass.h"
+#include "Loop.h" 
+#include "LoopCharacteristics.h"
+#include "AliasAnalysis.h"
+#include "SideEffectAnalysis.h"
+#include <vector>
+#include <map>
+#include <memory>
+#include <set>
+#include <string>
+
+namespace sysy {
+
+/**
+ * @brief 依赖类型枚举 - 只考虑真正影响并行性的依赖
+ * 
+ * 依赖类型分析说明：
+ * - TRUE_DEPENDENCE (RAW): 真依赖，必须保持原始执行顺序，是最关键的依赖
+ * - ANTI_DEPENDENCE (WAR): 反依赖，影响指令重排序，可通过寄存器重命名等技术缓解
+ * - OUTPUT_DEPENDENCE (WAW): 输出依赖，相对较少但需要考虑，可通过变量私有化解决
+ * 
+ */
+enum class DependenceType {
+  TRUE_DEPENDENCE,    // 真依赖 (RAW) - 读后写流依赖，最重要的依赖类型
+  ANTI_DEPENDENCE,    // 反依赖 (WAR) - 写后读反向依赖，影响指令重排序  
+  OUTPUT_DEPENDENCE   // 输出依赖 (WAW) - 写后写，相对较少但需要考虑
+};
+
+/**
+ * @brief 依赖向量 - 表示两个内存访问之间的迭代距离
+ * 例如：a[i] 和 a[i+1] 之间的依赖向量是 [1]
+ *       a[i][j] 和 a[i+1][j-2] 之间的依赖向量是 [1,-2]
+ */
+struct DependenceVector {
+  std::vector<int> distances;    // 每个循环层次的依赖距离
+  bool isConstant;               // 是否为常量距离
+  bool isKnown;                  // 是否已知距离
+  
+  DependenceVector(size_t loopDepth) : distances(loopDepth, 0), isConstant(false), isKnown(false) {}
+  
+  // 检查是否为循环无关依赖
+  bool isLoopIndependent() const {
+    for (int dist : distances) {
+      if (dist != 0) return false;
+    }
+    return true;
+  }
+  
+  // 获取词典序方向向量
+  std::vector<int> getDirectionVector() const;
+  
+  // 检查是否可以通过向量化处理
+  bool isVectorizationSafe() const;
+};
+
+/**
+ * @brief 精确依赖关系 - 包含依赖向量的详细依赖信息
+ */
+struct PreciseDependence {
+  Instruction* source;
+  Instruction* sink;
+  DependenceType type;
+  DependenceVector dependenceVector;
+  Value* memoryLocation;
+  
+  // 并行化相关
+  bool allowsParallelization;    // 是否允许并行化
+  bool requiresSynchronization;  // 是否需要同步
+  bool isReductionDependence;    // 是否为归约依赖
+  
+  PreciseDependence(size_t loopDepth) : dependenceVector(loopDepth), 
+    allowsParallelization(true), requiresSynchronization(false), isReductionDependence(false) {}
+};
+
+/**
+ * @brief 向量化分析信息 - 暂时搁置，保留接口
+ */
+struct VectorizationAnalysis {
+  bool isVectorizable;                        // 固定为false，暂不支持
+  int suggestedVectorWidth;                   // 固定为1
+  std::vector<std::string> preventingFactors; // 阻止向量化的因素
+  
+  VectorizationAnalysis() : isVectorizable(false), suggestedVectorWidth(1) {
+    preventingFactors.push_back("Vectorization temporarily disabled");
+  }
+};
+
+/**
+ * @brief 并行化分析信息
+ */
+struct ParallelizationAnalysis {
+  bool isParallelizable;                     // 是否可并行化
+  int suggestedThreadCount;                  // 建议的线程数
+  std::vector<std::string> preventingFactors; // 阻止并行化的因素
+  
+  // 并行化模式
+  enum ParallelizationType { 
+    NONE,                    // 不可并行化
+    EMBARRASSINGLY_PARALLEL, // 完全并行
+    REDUCTION_PARALLEL,      // 归约并行
+    PIPELINE_PARALLEL,       // 流水线并行
+    CONDITIONAL_PARALLEL     // 条件并行
+  } parallelType;
+  
+  // 负载均衡
+  bool hasLoadBalance;                       // 是否有良好的负载均衡
+  bool isDynamicLoadBalanced;                // 是否需要动态负载均衡
+  double workComplexity;                     // 工作复杂度估计
+  
+  // 同步需求
+  bool requiresReduction;                    // 是否需要归约操作
+  bool requiresBarrier;                      // 是否需要屏障同步
+  std::set<Value*> sharedVariables;         // 共享变量
+  std::set<Value*> reductionVariables;      // 归约变量
+  std::set<Value*> privatizableVariables;   // 可私有化变量
+  
+  // 内存访问模式
+  bool hasMemoryConflicts;                   // 是否有内存冲突
+  bool hasReadOnlyAccess;                    // 是否只有只读访问
+  bool hasIndependentAccess;                 // 是否有独立的内存访问
+  
+  // 并行化收益评估
+  double parallelizationBenefit;             // 并行化收益估计 (0-1)
+  size_t communicationCost;                  // 通信开销估计
+  size_t synchronizationCost;                // 同步开销估计
+  
+  ParallelizationAnalysis() : isParallelizable(false), suggestedThreadCount(1), parallelType(NONE),
+    hasLoadBalance(true), isDynamicLoadBalanced(false), workComplexity(0.0), requiresReduction(false), 
+    requiresBarrier(false), hasMemoryConflicts(false), hasReadOnlyAccess(false), hasIndependentAccess(false),
+    parallelizationBenefit(0.0), communicationCost(0), synchronizationCost(0) {}
+};
+
+/**
+ * @brief 循环向量化/并行化分析结果
+ */
+class LoopVectorizationResult : public AnalysisResultBase {
+private:
+  Function* AssociatedFunction;
+  std::map<Loop*, VectorizationAnalysis> VectorizationMap;
+  std::map<Loop*, ParallelizationAnalysis> ParallelizationMap;
+  std::map<Loop*, std::vector<PreciseDependence>> DependenceMap;
+
+public:
+  LoopVectorizationResult(Function* F) : AssociatedFunction(F) {}
+  ~LoopVectorizationResult() override = default;
+
+  // 基础接口
+  void addVectorizationAnalysis(Loop* loop, VectorizationAnalysis analysis) {
+    VectorizationMap[loop] = std::move(analysis);
+  }
+  
+  void addParallelizationAnalysis(Loop* loop, ParallelizationAnalysis analysis) {
+    ParallelizationMap[loop] = std::move(analysis);
+  }
+  
+  void addDependenceAnalysis(Loop* loop, std::vector<PreciseDependence> dependences) {
+    DependenceMap[loop] = std::move(dependences);
+  }
+
+  // 查询接口
+  const VectorizationAnalysis* getVectorizationAnalysis(Loop* loop) const {
+    auto it = VectorizationMap.find(loop);
+    return it != VectorizationMap.end() ? &it->second : nullptr;
+  }
+  
+  const ParallelizationAnalysis* getParallelizationAnalysis(Loop* loop) const {
+    auto it = ParallelizationMap.find(loop);
+    return it != ParallelizationMap.end() ? &it->second : nullptr;
+  }
+  
+  const std::vector<PreciseDependence>* getPreciseDependences(Loop* loop) const {
+    auto it = DependenceMap.find(loop);
+    return it != DependenceMap.end() ? &it->second : nullptr;
+  }
+
+  // 统计接口
+  size_t getVectorizableLoopCount() const;
+  size_t getParallelizableLoopCount() const;
+  
+  // 优化建议
+  std::vector<Loop*> getVectorizationCandidates() const;
+  std::vector<Loop*> getParallelizationCandidates() const;
+  
+  // 打印分析结果
+  void print() const;
+};
+
+/**
+ * @brief 循环向量化/并行化分析遍
+ * 在循环规范化后执行，进行精确的依赖向量分析和向量化/并行化可行性评估
+ * 专注于并行化分析，向量化功能暂时搁置
+ */
+class LoopVectorizationPass : public AnalysisPass {
+public:
+  // 唯一的 Pass ID
+  static void *ID;
+  
+  LoopVectorizationPass() : AnalysisPass("LoopVectorization", Pass::Granularity::Function) {}
+
+  // 实现 getPassID
+  void *getPassID() const override { return &ID; }
+
+  // 核心运行方法
+  bool runOnFunction(Function *F, AnalysisManager &AM) override;
+  
+  // 获取分析结果
+  std::unique_ptr<AnalysisResultBase> getResult() override { return std::move(CurrentResult); }
+
+private:
+  std::unique_ptr<LoopVectorizationResult> CurrentResult;
+  
+  // ========== 主要分析方法 ==========
+  void analyzeLoop(Loop* loop, LoopCharacteristics* characteristics, 
+                   AliasAnalysisResult* aliasAnalysis, SideEffectAnalysisResult* sideEffectAnalysis);
+  
+  // ========== 依赖向量分析 ==========
+  std::vector<PreciseDependence> computeDependenceVectors(Loop* loop, AliasAnalysisResult* aliasAnalysis);
+  DependenceVector computeAccessDependence(Instruction* inst1, Instruction* inst2, Loop* loop);
+  bool areAccessesAffinelyRelated(Value* ptr1, Value* ptr2, Loop* loop);
+  
+  // ========== 向量化分析 (暂时搁置) ==========
+  VectorizationAnalysis analyzeVectorizability(Loop* loop, const std::vector<PreciseDependence>& dependences,
+                                              LoopCharacteristics* characteristics);
+  
+  // ========== 并行化分析 ==========
+  ParallelizationAnalysis analyzeParallelizability(Loop* loop, const std::vector<PreciseDependence>& dependences,
+                                                  LoopCharacteristics* characteristics);
+  bool checkParallelizationLegality(Loop* loop, const std::vector<PreciseDependence>& dependences);
+  int estimateOptimalThreadCount(Loop* loop, LoopCharacteristics* characteristics);
+  ParallelizationAnalysis::ParallelizationType determineParallelizationType(Loop* loop, 
+                                                                           const std::vector<PreciseDependence>& dependences);
+  
+  // ========== 并行化专用分析方法 ==========
+  void analyzeReductionPatterns(Loop* loop, ParallelizationAnalysis* analysis);
+  void analyzeMemoryAccessPatterns(Loop* loop, ParallelizationAnalysis* analysis, AliasAnalysisResult* aliasAnalysis);
+  void estimateParallelizationBenefit(Loop* loop, ParallelizationAnalysis* analysis, LoopCharacteristics* characteristics);
+  void identifyPrivatizableVariables(Loop* loop, ParallelizationAnalysis* analysis);
+  void analyzeSynchronizationNeeds(Loop* loop, ParallelizationAnalysis* analysis, const std::vector<PreciseDependence>& dependences);
+  
+  // ========== 辅助方法 ==========
+  std::vector<int> extractInductionCoefficients(Value* ptr, Loop* loop);
+  bool isConstantStride(Value* ptr, Loop* loop, int& stride);
+  bool isIndependentMemoryAccess(Value* ptr1, Value* ptr2, Loop* loop);
+  double estimateWorkComplexity(Loop* loop);
+  bool hasReductionPattern(Value* var, Loop* loop);
+};
+
+} // namespace sysy