Add comprehensive analysis of ZScream vs YAZE overworld implementations

- Introduced a detailed comparison document highlighting the functional equivalence between ZScream (C#) and YAZE (C++) overworld loading logic.
- Verified key areas such as tile loading, expansion detection, map decompression, and coordinate calculations, confirming consistent behavior across both implementations.
- Documented differences and improvements in YAZE, including enhanced error handling and memory management.
- Provided validation results from integration tests ensuring data integrity and compatibility with existing ROMs.

docs/analysis/dungeon_parallel_optimization_summary.md

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+# DungeonEditor Parallel Optimization Implementation
+
+## 🚀 **Parallelization Strategy Implemented**
+
+### **Problem Identified**
+- **DungeonEditor::LoadAllRooms**: **17,966ms (17.97 seconds)** - 99.9% of loading time
+- Loading **296 rooms** sequentially, each involving complex operations
+- Perfect candidate for parallelization due to independent room processing
+
+### **Solution: Multi-Threaded Room Loading**
+
+#### **Key Optimizations**
+
+1. **Parallel Room Processing**
+   ```cpp
+   // Load 296 rooms using up to 8 threads
+   const int max_concurrency = std::min(8, std::thread::hardware_concurrency());
+   const int rooms_per_thread = (296 + max_concurrency - 1) / max_concurrency;
+   ```
+
+2. **Thread-Safe Result Collection**
+   ```cpp
+   std::mutex results_mutex;
+   std::vector<std::pair<int, zelda3::RoomSize>> room_size_results;
+   std::vector<std::pair<int, ImVec4>> room_palette_results;
+   ```
+
+3. **Optimized Thread Distribution**
+   - **8 threads maximum** (reasonable limit for room loading)
+   - **~37 rooms per thread** (296 ÷ 8 = 37 rooms per thread)
+   - **Hardware concurrency aware** (adapts to available CPU cores)
+
+#### **Parallel Processing Flow**
+
+```cpp
+// Each thread processes a batch of rooms
+for (int i = start_room; i < end_room; ++i) {
+  // 1. Load room data (expensive operation)
+  rooms[i] = zelda3::LoadRoomFromRom(rom_, i);
+  
+  // 2. Calculate room size
+  auto room_size = zelda3::CalculateRoomSize(rom_, i);
+  
+  // 3. Load room objects
+  rooms[i].LoadObjects();
+  
+  // 4. Process palette (thread-safe collection)
+  // ... palette processing ...
+}
+```
+
+#### **Thread Safety Features**
+
+1. **Mutex Protection**: `std::mutex results_mutex` protects shared data structures
+2. **Lock Guards**: `std::lock_guard<std::mutex>` ensures thread-safe result collection
+3. **Independent Processing**: Each thread works on different room ranges
+4. **Synchronized Results**: Results collected and sorted on main thread
+
+### **Expected Performance Impact**
+
+#### **Theoretical Speedup**
+- **8x faster** with 8 threads (ideal case)
+- **Realistic expectation**: **4-6x speedup** due to:
+  - Thread creation overhead
+  - Mutex contention
+  - Memory bandwidth limitations
+  - Cache coherency issues
+
+#### **Expected Results**
+- **Before**: 17,966ms (17.97 seconds)
+- **After**: **2,000-4,500ms (2-4.5 seconds)**
+- **Total Loading Time**: **2.5-5 seconds** (down from 18.6 seconds)
+- **Overall Improvement**: **70-85% reduction** in loading time
+
+### **Technical Implementation Details**
+
+#### **Thread Management**
+```cpp
+std::vector<std::future<absl::Status>> futures;
+
+for (int thread_id = 0; thread_id < max_concurrency; ++thread_id) {
+  auto task = [this, &rooms, thread_id, rooms_per_thread, ...]() -> absl::Status {
+    // Process room batch
+    return absl::OkStatus();
+  };
+  
+  futures.emplace_back(std::async(std::launch::async, task));
+}
+
+// Wait for all threads to complete
+for (auto& future : futures) {
+  RETURN_IF_ERROR(future.get());
+}
+```
+
+#### **Result Processing**
+```cpp
+// Sort results by room ID for consistent ordering
+std::sort(room_size_results.begin(), room_size_results.end(), 
+          [](const auto& a, const auto& b) { return a.first < b.first; });
+
+// Process collected results on main thread
+for (const auto& [room_id, room_size] : room_size_results) {
+  room_size_pointers_.push_back(room_size.room_size_pointer);
+  // ... process results ...
+}
+```
+
+### **Monitoring and Validation**
+
+#### **Performance Timing Added**
+- **DungeonRoomLoader::PostProcessResults**: Measures result processing time
+- **Thread creation overhead**: Minimal compared to room loading time
+- **Result collection time**: Expected to be <100ms
+
+#### **Logging and Debugging**
+```cpp
+util::logf("Loading %d dungeon rooms using %d threads (%d rooms per thread)", 
+           kTotalRooms, max_concurrency, rooms_per_thread);
+```
+
+### **Benefits of This Approach**
+
+1. **Massive Performance Gain**: 70-85% reduction in loading time
+2. **Scalable**: Automatically adapts to available CPU cores
+3. **Thread-Safe**: Proper synchronization prevents data corruption
+4. **Maintainable**: Clean separation of parallel processing and result collection
+5. **Robust**: Error handling per thread with proper status propagation
+
+### **Next Steps**
+
+1. **Test Performance**: Run application and measure actual speedup
+2. **Validate Results**: Ensure room data integrity is maintained
+3. **Fine-tune**: Adjust thread count if needed based on results
+4. **Monitor**: Watch for any threading issues or performance regressions
+
+This parallel optimization should transform YAZE from a slow-loading application to a lightning-fast ROM editor!