@mytec: iter2.4 ready for testing

2026-02-01 10:48:23 +02:00
parent 7893c57bc9
commit 5488633e43
19 changed files with 1448 additions and 69 deletions
--- a/RFCP-Phase-2.4-GPU-Elevation.md
+++ b/RFCP-Phase-2.4-GPU-Elevation.md
@@ -0,0 +1,821 @@
+# RFCP Phase 2.4: GPU Acceleration + Elevation Layer
+
+**Date:** February 1, 2025  
+**Type:** Performance + UI Enhancement  
+**Priority:** HIGH  
+**Depends on:** Phase 2.3 (Performance fixes)
+
+---
+
+## 🎯 Goals
+
+1. **Elevation Layer** — візуалізація рельєфу на карті
+2. **GPU Acceleration** — прискорення розрахунків через CUDA
+3. **Bug Fixes** — закриття app, timeout handling
+
+---
+
+## 🐛 Bug Fixes (CRITICAL — Do First!)
+
+### Bug 2.4.0a: App Close Still Not Working
+
+**Symptoms:**
+- Clicking X closes window but processes stay running
+- rfcp-server.exe stays in Task Manager
+- Have to manually kill processes
+
+**File:** `desktop/main.js`
+
+**Debug steps:**
+1. Add console.log at START of killBackend():
+```javascript
+function killBackend() {
+  console.log('[KILL] killBackend() called, pid:', backendPid);
+  // ... rest of function
+}
+```
+
+2. Add console.log in close handler:
+```javascript
+mainWindow.on('close', (event) => {
+  console.log('[CLOSE] Window close event triggered');
+  killBackend();
+});
+```
+
+3. Check if the issue is:
+   - killBackend() not being called at all
+   - taskkill not working (wrong PID?)
+   - Process spawning children that aren't killed
+
+**Potential fix:**
+```javascript
+function killBackend() {
+  console.log('[KILL] killBackend() called');
+  
+  if (!backendPid && !backendProcess) {
+    console.log('[KILL] No backend to kill');
+    return;
+  }
+  
+  const pid = backendPid || backendProcess?.pid;
+  console.log('[KILL] Killing PID:', pid);
+  
+  if (process.platform === 'win32') {
+    // Force kill entire process tree
+    try {
+      require('child_process').execSync(`taskkill /F /T /PID ${pid}`, {
+        stdio: 'ignore'
+      });
+      console.log('[KILL] taskkill completed');
+    } catch (e) {
+      console.log('[KILL] taskkill error:', e.message);
+    }
+  }
+  
+  backendProcess = null;
+  backendPid = null;
+}
+```
+
+4. Add in app quit:
+```javascript
+app.on('before-quit', () => {
+  console.log('[QUIT] before-quit event');
+  killBackend();
+});
+
+app.on('will-quit', () => {
+  console.log('[QUIT] will-quit event');
+  killBackend();
+});
+```
+
+---
+
+### Bug 2.4.0b: Calculation Continues After Timeout
+
+**Symptoms:**
+- User gets "timeout" error in UI
+- But backend keeps calculating (CPU stays loaded)
+- Machine stays slow until manually kill process
+
+**File:** `backend/app/services/coverage_service.py`
+
+**Root cause:** asyncio.wait_for() cancels the coroutine but:
+- ProcessPoolExecutor workers keep running
+- Ray tasks keep running
+- No cancellation signal sent
+
+**Fix in coverage_service.py:**
+
+```python
+# Add cancellation flag
+_calculation_cancelled = False
+
+async def calculate_coverage(sites, settings):
+    global _calculation_cancelled
+    _calculation_cancelled = False
+    
+    try:
+        result = await asyncio.wait_for(
+            _do_calculation(sites, settings),
+            timeout=300  # 5 minutes
+        )
+        return result
+    except asyncio.TimeoutError:
+        _calculation_cancelled = True
+        _cleanup_running_tasks()  # NEW
+        raise HTTPException(408, "Calculation timeout")
+
+def _cleanup_running_tasks():
+    """Stop any running parallel workers."""
+    global _calculation_cancelled
+    _calculation_cancelled = True
+    
+    # If using Ray
+    if RAY_AVAILABLE and ray.is_initialized():
+        # Cancel pending tasks
+        # Ray doesn't have great cancellation, but we can try
+        pass
+    
+    # If using ProcessPoolExecutor - it will check flag
+    _clog("Calculation cancelled, cleaning up workers")
+```
+
+**In parallel workers, check cancellation:**
+
+```python
+def _process_chunk(chunk, ...):
+    results = []
+    for point in chunk:
+        # Check if cancelled
+        if _calculation_cancelled:
+            _clog("Worker detected cancellation, stopping")
+            break
+        
+        result = _calculate_point_sync(point, ...)
+        results.append(result)
+    
+    return results
+```
+
+---
+
+## 📊 Part A: Elevation Layer
+
+### A.1: Backend API
+
+**New file:** `backend/app/api/routes/terrain.py`
+
+```python
+from fastapi import APIRouter, Query
+from typing import List
+from app.services.terrain_service import terrain_service
+
+router = APIRouter(prefix="/api/terrain", tags=["terrain"])
+
+@router.get("/elevation-grid")
+async def get_elevation_grid(
+    min_lat: float = Query(..., description="South boundary"),
+    max_lat: float = Query(..., description="North boundary"),
+    min_lon: float = Query(..., description="West boundary"),
+    max_lon: float = Query(..., description="East boundary"),
+    resolution: int = Query(100, description="Grid resolution in meters")
+) -> dict:
+    """
+    Get elevation grid for a bounding box.
+    Returns a 2D array of elevations for rendering terrain layer.
+    """
+    # Calculate grid dimensions
+    lat_range = max_lat - min_lat
+    lon_range = max_lon - min_lon
+    
+    # Approximate meters per degree
+    meters_per_lat = 111000
+    meters_per_lon = 111000 * cos(radians((min_lat + max_lat) / 2))
+    
+    # Grid size
+    rows = int((lat_range * meters_per_lat) / resolution)
+    cols = int((lon_range * meters_per_lon) / resolution)
+    
+    # Cap to reasonable size
+    rows = min(rows, 200)
+    cols = min(cols, 200)
+    
+    # Build elevation grid
+    elevations = []
+    lat_step = lat_range / rows
+    lon_step = lon_range / cols
+    
+    for i in range(rows):
+        row = []
+        lat = max_lat - (i + 0.5) * lat_step  # Start from north
+        for j in range(cols):
+            lon = min_lon + (j + 0.5) * lon_step
+            elev = terrain_service.get_elevation_sync(lat, lon)
+            row.append(elev)
+        elevations.append(row)
+    
+    # Get min/max for color scaling
+    flat = [e for row in elevations for e in row]
+    
+    return {
+        "elevations": elevations,
+        "rows": rows,
+        "cols": cols,
+        "min_elevation": min(flat),
+        "max_elevation": max(flat),
+        "bbox": {
+            "min_lat": min_lat,
+            "max_lat": max_lat,
+            "min_lon": min_lon,
+            "max_lon": max_lon
+        }
+    }
+```
+
+**Register in main.py:**
+```python
+from app.api.routes import terrain
+app.include_router(terrain.router)
+```
+
+---
+
+### A.2: Frontend Component
+
+**New file:** `frontend/src/components/ElevationLayer.tsx`
+
+```tsx
+import { useEffect, useRef } from 'react';
+import { useMap } from 'react-leaflet';
+import L from 'leaflet';
+
+interface ElevationLayerProps {
+  enabled: boolean;
+  opacity: number;
+  bbox: {
+    minLat: number;
+    maxLat: number;
+    minLon: number;
+    maxLon: number;
+  } | null;
+}
+
+// Color scale: blue (low) → green → yellow → brown (high)
+const ELEVATION_COLORS = [
+  { threshold: 0, color: [33, 102, 172] },      // #2166ac deep blue
+  { threshold: 100, color: [103, 169, 207] },   // #67a9cf light blue
+  { threshold: 150, color: [145, 207, 96] },    // #91cf60 green
+  { threshold: 200, color: [254, 224, 139] },   // #fee08b yellow
+  { threshold: 250, color: [252, 141, 89] },    // #fc8d59 orange
+  { threshold: 300, color: [215, 48, 39] },     // #d73027 red
+  { threshold: 400, color: [165, 0, 38] },      // #a50026 dark red
+];
+
+function getColorForElevation(elevation: number): [number, number, number] {
+  for (let i = ELEVATION_COLORS.length - 1; i >= 0; i--) {
+    if (elevation >= ELEVATION_COLORS[i].threshold) {
+      if (i === ELEVATION_COLORS.length - 1) {
+        return ELEVATION_COLORS[i].color as [number, number, number];
+      }
+      // Interpolate between this and next color
+      const low = ELEVATION_COLORS[i];
+      const high = ELEVATION_COLORS[i + 1];
+      const t = (elevation - low.threshold) / (high.threshold - low.threshold);
+      return [
+        Math.round(low.color[0] + t * (high.color[0] - low.color[0])),
+        Math.round(low.color[1] + t * (high.color[1] - low.color[1])),
+        Math.round(low.color[2] + t * (high.color[2] - low.color[2])),
+      ];
+    }
+  }
+  return ELEVATION_COLORS[0].color as [number, number, number];
+}
+
+export function ElevationLayer({ enabled, opacity, bbox }: ElevationLayerProps) {
+  const map = useMap();
+  const canvasRef = useRef<HTMLCanvasElement | null>(null);
+  const overlayRef = useRef<L.ImageOverlay | null>(null);
+
+  useEffect(() => {
+    if (!enabled || !bbox) {
+      // Remove overlay if disabled
+      if (overlayRef.current) {
+        map.removeLayer(overlayRef.current);
+        overlayRef.current = null;
+      }
+      return;
+    }
+
+    // Fetch elevation data
+    const fetchElevation = async () => {
+      const params = new URLSearchParams({
+        min_lat: bbox.minLat.toString(),
+        max_lat: bbox.maxLat.toString(),
+        min_lon: bbox.minLon.toString(),
+        max_lon: bbox.maxLon.toString(),
+        resolution: '100',
+      });
+
+      const response = await fetch(`/api/terrain/elevation-grid?${params}`);
+      const data = await response.json();
+
+      // Create canvas
+      const canvas = document.createElement('canvas');
+      canvas.width = data.cols;
+      canvas.height = data.rows;
+      const ctx = canvas.getContext('2d')!;
+      const imageData = ctx.createImageData(data.cols, data.rows);
+
+      // Fill pixel data
+      for (let i = 0; i < data.rows; i++) {
+        for (let j = 0; j < data.cols; j++) {
+          const elevation = data.elevations[i][j];
+          const color = getColorForElevation(elevation);
+          const idx = (i * data.cols + j) * 4;
+          imageData.data[idx] = color[0];     // R
+          imageData.data[idx + 1] = color[1]; // G
+          imageData.data[idx + 2] = color[2]; // B
+          imageData.data[idx + 3] = 255;      // A
+        }
+      }
+
+      ctx.putImageData(imageData, 0, 0);
+
+      // Create overlay
+      const bounds = L.latLngBounds(
+        [bbox.minLat, bbox.minLon],
+        [bbox.maxLat, bbox.maxLon]
+      );
+
+      if (overlayRef.current) {
+        map.removeLayer(overlayRef.current);
+      }
+
+      overlayRef.current = L.imageOverlay(canvas.toDataURL(), bounds, {
+        opacity: opacity,
+        interactive: false,
+      });
+      
+      overlayRef.current.addTo(map);
+    };
+
+    fetchElevation();
+
+    return () => {
+      if (overlayRef.current) {
+        map.removeLayer(overlayRef.current);
+      }
+    };
+  }, [enabled, opacity, bbox, map]);
+
+  return null;
+}
+```
+
+---
+
+### A.3: Layer Controls UI
+
+**Update:** `frontend/src/App.tsx` or create `LayerControls.tsx`
+
+```tsx
+// Add to state
+const [showElevation, setShowElevation] = useState(false);
+const [elevationOpacity, setElevationOpacity] = useState(0.5);
+
+// Add to UI (in settings panel or toolbar)
+<div className="layer-controls">
+  <h4>Map Layers</h4>
+  
+  <label className="layer-toggle">
+    <input
+      type="checkbox"
+      checked={showElevation}
+      onChange={(e) => setShowElevation(e.target.checked)}
+    />
+    Show Elevation
+  </label>
+  
+  {showElevation && (
+    <div className="elevation-opacity">
+      <label>Opacity: {Math.round(elevationOpacity * 100)}%</label>
+      <input
+        type="range"
+        min="0.2"
+        max="1"
+        step="0.1"
+        value={elevationOpacity}
+        onChange={(e) => setElevationOpacity(parseFloat(e.target.value))}
+      />
+    </div>
+  )}
+  
+  {/* Elevation legend */}
+  {showElevation && (
+    <div className="elevation-legend">
+      <div className="legend-item">
+        <span className="color-box" style={{background: '#2166ac'}}></span>
+        &lt;100m
+      </div>
+      <div className="legend-item">
+        <span className="color-box" style={{background: '#91cf60'}}></span>
+        150-200m
+      </div>
+      <div className="legend-item">
+        <span className="color-box" style={{background: '#fee08b'}}></span>
+        200-250m
+      </div>
+      <div className="legend-item">
+        <span className="color-box" style={{background: '#d73027'}}></span>
+        &gt;300m
+      </div>
+    </div>
+  )}
+</div>
+
+// In Map component
+<ElevationLayer
+  enabled={showElevation}
+  opacity={elevationOpacity}
+  bbox={mapBounds}  // Current map view bounds
+/>
+```
+
+---
+
+## ⚡ Part B: GPU Acceleration
+
+### B.1: GPU Service
+
+**New file:** `backend/app/services/gpu_service.py`
+
+```python
+"""
+GPU acceleration for coverage calculations using CuPy.
+Falls back to NumPy if CUDA not available.
+"""
+
+import numpy as np
+from typing import Tuple, Optional
+import os
+
+# Try to import CuPy
+GPU_AVAILABLE = False
+GPU_INFO = None
+
+try:
+    import cupy as cp
+    
+    # Check if CUDA actually works
+    try:
+        cp.cuda.runtime.getDeviceCount()
+        GPU_AVAILABLE = True
+        
+        # Get GPU info
+        props = cp.cuda.runtime.getDeviceProperties(0)
+        GPU_INFO = {
+            'name': props['name'].decode() if isinstance(props['name'], bytes) else props['name'],
+            'memory_mb': props['totalGlobalMem'] // (1024 * 1024),
+            'cuda_version': cp.cuda.runtime.runtimeGetVersion(),
+        }
+        print(f"[GPU] CUDA available: {GPU_INFO['name']} ({GPU_INFO['memory_mb']} MB)")
+    except Exception as e:
+        print(f"[GPU] CUDA device check failed: {e}")
+        
+except ImportError:
+    print("[GPU] CuPy not installed, using CPU only")
+
+
+def get_array_module():
+    """Get the appropriate array module (cupy or numpy)."""
+    if GPU_AVAILABLE:
+        return cp
+    return np
+
+
+def to_gpu(array: np.ndarray) -> 'cp.ndarray | np.ndarray':
+    """Move array to GPU if available."""
+    if GPU_AVAILABLE:
+        return cp.asarray(array)
+    return array
+
+
+def to_cpu(array) -> np.ndarray:
+    """Move array back to CPU."""
+    if GPU_AVAILABLE and hasattr(array, 'get'):
+        return array.get()
+    return np.asarray(array)
+
+
+class GPUService:
+    """GPU-accelerated calculations for coverage planning."""
+    
+    def __init__(self):
+        self.enabled = GPU_AVAILABLE
+        self.info = GPU_INFO
+    
+    def calculate_distances_batch(
+        self,
+        site_lat: float,
+        site_lon: float,
+        point_lats: np.ndarray,
+        point_lons: np.ndarray,
+    ) -> np.ndarray:
+        """
+        Calculate Haversine distances from site to all points.
+        Vectorized for GPU acceleration.
+        
+        Args:
+            site_lat, site_lon: Site coordinates (degrees)
+            point_lats, point_lons: Arrays of point coordinates (degrees)
+            
+        Returns:
+            Array of distances in meters
+        """
+        xp = get_array_module()
+        
+        # Move to GPU if available
+        lats = to_gpu(point_lats)
+        lons = to_gpu(point_lons)
+        
+        # Convert to radians
+        lat1 = xp.radians(site_lat)
+        lon1 = xp.radians(site_lon)
+        lat2 = xp.radians(lats)
+        lon2 = xp.radians(lons)
+        
+        # Haversine formula (vectorized)
+        dlat = lat2 - lat1
+        dlon = lon2 - lon1
+        
+        a = xp.sin(dlat / 2) ** 2 + xp.cos(lat1) * xp.cos(lat2) * xp.sin(dlon / 2) ** 2
+        c = 2 * xp.arcsin(xp.sqrt(a))
+        
+        R = 6371000  # Earth radius in meters
+        distances = R * c
+        
+        return to_cpu(distances)
+    
+    def calculate_free_space_path_loss_batch(
+        self,
+        distances: np.ndarray,
+        frequency_mhz: float,
+    ) -> np.ndarray:
+        """
+        Calculate Free Space Path Loss for all distances.
+        
+        FSPL = 20*log10(d) + 20*log10(f) + 20*log10(4π/c)
+             = 20*log10(d_km) + 20*log10(f_mhz) + 32.45
+        """
+        xp = get_array_module()
+        d = to_gpu(distances)
+        
+        # Avoid log(0)
+        d_km = xp.maximum(d / 1000.0, 0.001)
+        
+        fspl = 20 * xp.log10(d_km) + 20 * xp.log10(frequency_mhz) + 32.45
+        
+        return to_cpu(fspl)
+    
+    def calculate_okumura_hata_batch(
+        self,
+        distances: np.ndarray,
+        frequency_mhz: float,
+        tx_height: float,
+        rx_height: float = 1.5,
+        environment: str = 'urban',
+    ) -> np.ndarray:
+        """
+        Calculate Okumura-Hata path loss for all distances.
+        Vectorized for GPU acceleration.
+        """
+        xp = get_array_module()
+        d = to_gpu(distances)
+        
+        # Avoid log(0)
+        d_km = xp.maximum(d / 1000.0, 0.001)
+        
+        f = frequency_mhz
+        hb = tx_height
+        hm = rx_height
+        
+        # Mobile antenna height correction (urban)
+        if f <= 200:
+            a_hm = 8.29 * (xp.log10(1.54 * hm)) ** 2 - 1.1
+        elif f >= 400:
+            a_hm = 3.2 * (xp.log10(11.75 * hm)) ** 2 - 4.97
+        else:
+            a_hm = (1.1 * xp.log10(f) - 0.7) * hm - (1.56 * xp.log10(f) - 0.8)
+        
+        # Base formula
+        L = (69.55 + 26.16 * xp.log10(f) 
+             - 13.82 * xp.log10(hb) 
+             - a_hm 
+             + (44.9 - 6.55 * xp.log10(hb)) * xp.log10(d_km))
+        
+        # Environment corrections
+        if environment == 'suburban':
+            L = L - 2 * (xp.log10(f / 28)) ** 2 - 5.4
+        elif environment == 'rural':
+            L = L - 4.78 * (xp.log10(f)) ** 2 + 18.33 * xp.log10(f) - 40.94
+        
+        return to_cpu(L)
+    
+    def calculate_rsrp_batch(
+        self,
+        distances: np.ndarray,
+        tx_power_dbm: float,
+        antenna_gain_dbi: float,
+        frequency_mhz: float,
+        tx_height: float,
+        environment: str = 'urban',
+    ) -> np.ndarray:
+        """
+        Calculate RSRP for all points (basic, without terrain/buildings).
+        """
+        path_loss = self.calculate_okumura_hata_batch(
+            distances, frequency_mhz, tx_height, 
+            environment=environment
+        )
+        
+        rsrp = tx_power_dbm + antenna_gain_dbi - path_loss
+        
+        return rsrp
+
+
+# Singleton instance
+gpu_service = GPUService()
+```
+
+---
+
+### B.2: Integration with Coverage Service
+
+**Update:** `backend/app/services/coverage_service.py`
+
+```python
+from app.services.gpu_service import gpu_service, GPU_AVAILABLE
+
+# In calculate_coverage, before point loop:
+
+async def calculate_coverage(sites, settings):
+    # ... existing Phase 1 & 2 code ...
+    
+    # Phase 2.5: Pre-calculate with GPU if available
+    if GPU_AVAILABLE and len(grid) > 100:
+        _clog(f"Using GPU acceleration for {len(grid)} points")
+        
+        # Prepare arrays
+        point_lats = np.array([p[0] for p in grid])
+        point_lons = np.array([p[1] for p in grid])
+        
+        # Calculate all distances at once (GPU)
+        all_distances = gpu_service.calculate_distances_batch(
+            site.lat, site.lon, point_lats, point_lons
+        )
+        
+        # Calculate all basic path losses at once (GPU)
+        all_path_losses = gpu_service.calculate_okumura_hata_batch(
+            all_distances,
+            site.frequency,
+            site.height,
+            environment='urban' if settings.use_buildings else 'rural'
+        )
+        
+        # Store for use in point loop
+        precomputed = {
+            'distances': all_distances,
+            'path_losses': all_path_losses,
+        }
+        _clog(f"GPU pre-calculation done: {len(grid)} distances + path losses")
+    else:
+        precomputed = None
+    
+    # Phase 3: Point loop (uses precomputed if available)
+    # ... modify _calculate_point_sync to accept precomputed values ...
+```
+
+---
+
+### B.3: System Info Update
+
+**Update:** `backend/app/api/routes/system.py`
+
+```python
+from app.services.gpu_service import GPU_AVAILABLE, GPU_INFO
+
+@router.get("/api/system/info")
+async def get_system_info():
+    return {
+        "cpu_cores": mp.cpu_count(),
+        "parallel_workers": min(mp.cpu_count() - 2, 14),
+        "parallel_backend": "ray" if RAY_AVAILABLE else "process_pool" if mp.cpu_count() > 1 else "sequential",
+        "ray_available": RAY_AVAILABLE,
+        "gpu": GPU_INFO,  # Now includes name, memory, cuda_version
+        "gpu_available": GPU_AVAILABLE,
+    }
+```
+
+---
+
+### B.4: Requirements
+
+**Update:** `backend/requirements.txt`
+
+```
+# ... existing requirements ...
+
+# GPU acceleration (optional)
+# Install with: pip install cupy-cuda12x
+# Or for CUDA 11.x: pip install cupy-cuda11x
+# cupy-cuda12x>=12.0.0
+```
+
+**Note:** CuPy is optional. Code falls back to NumPy if not installed.
+
+---
+
+## 📁 Files to Create/Modify
+
+**New files:**
+- `backend/app/api/routes/terrain.py`
+- `backend/app/services/gpu_service.py`
+- `frontend/src/components/ElevationLayer.tsx`
+
+**Modified files:**
+- `backend/app/main.py` — register terrain router
+- `backend/app/services/coverage_service.py` — GPU integration, cancellation
+- `backend/app/api/routes/system.py` — GPU info
+- `backend/requirements.txt` — cupy optional
+- `desktop/main.js` — fix app close (debug + fix)
+- `frontend/src/App.tsx` — elevation layer toggle
+
+---
+
+## 🧪 Testing
+
+### Test Elevation Layer:
+```bash
+# Start app
+./rfcp-debug.bat
+
+# In browser console or via curl:
+curl "http://localhost:8888/api/terrain/elevation-grid?min_lat=48.5&max_lat=48.7&min_lon=36.0&max_lon=36.2&resolution=100"
+
+# Should return JSON with elevations array
+```
+
+### Test GPU:
+```bash
+# Check system info
+curl http://localhost:8888/api/system/info
+
+# Should show:
+# "gpu_available": true,
+# "gpu": {"name": "NVIDIA GeForce RTX 4060", "memory_mb": 8192, ...}
+```
+
+### Test App Close:
+```
+1. Start app via RFCP.exe (not debug bat)
+2. Click X to close
+3. Check Task Manager - rfcp-server.exe should NOT be running
+4. If still running - check console logs for [KILL] messages
+```
+
+---
+
+## ✅ Success Criteria
+
+- [ ] Elevation layer toggleable on map
+- [ ] Elevation colors match terrain (verify with known locations)
+- [ ] GPU detected and shown in system info (if NVIDIA card present)
+- [ ] Fast preset 2x faster with GPU
+- [ ] App closes completely when clicking X
+- [ ] No orphan processes after timeout
+- [ ] All existing presets still work
+
+---
+
+## 📈 Expected Performance
+
+| Operation | CPU (NumPy) | GPU (CuPy) | Speedup |
+|-----------|-------------|------------|---------|
+| 10k distances | 5ms | 0.1ms | 50x |
+| 10k path losses | 10ms | 0.2ms | 50x |
+| Full calculation* | 10s | 3s | 3x |
+
+*Full calculation limited by CPU-bound terrain/building checks
+
+---
+
+## 🔜 Next Phase
+
+Phase 2.5: Advanced Visualization
+- LOS ray visualization (show blocked paths)
+- 3D terrain view
+- Antenna pattern visualization
+- Multi-site interference view
--- a/backend/app/api/routes/coverage.py
+++ b/backend/app/api/routes/coverage.py
@@ -12,6 +12,7 @@ from app.services.coverage_service import (
    apply_preset,
    PRESETS,
 )
+from app.services.parallel_coverage_service import CancellationToken

 router = APIRouter()

@@ -59,6 +60,7 @@ async def calculate_coverage(request: CoverageRequest) -> CoverageResponse:

    # Time the calculation
    start_time = time.time()
+    cancel_token = CancellationToken()

    try:
        # Calculate with 5-minute timeout
@@ -66,7 +68,8 @@ async def calculate_coverage(request: CoverageRequest) -> CoverageResponse:
            points = await asyncio.wait_for(
                coverage_service.calculate_coverage(
                    request.sites[0],
-                    request.settings
+                    request.settings,
+                    cancel_token,
                ),
                timeout=300.0
            )
@@ -74,12 +77,17 @@ async def calculate_coverage(request: CoverageRequest) -> CoverageResponse:
            points = await asyncio.wait_for(
                coverage_service.calculate_multi_site_coverage(
                    request.sites,
-                    request.settings
+                    request.settings,
+                    cancel_token,
                ),
                timeout=300.0
            )
    except asyncio.TimeoutError:
+        cancel_token.cancel()
        raise HTTPException(408, "Calculation timeout (5 min) — try smaller radius or lower resolution")
+    except asyncio.CancelledError:
+        cancel_token.cancel()
+        raise HTTPException(499, "Client disconnected")

    computation_time = time.time() - start_time

--- a/backend/app/api/routes/system.py
+++ b/backend/app/api/routes/system.py
@@ -21,25 +21,24 @@ async def get_system_info():
    except Exception:
        pass

-    # Check GPU
-    gpu_info = None
-    try:
-        import cupy as cp
-        if cp.cuda.runtime.getDeviceCount() > 0:
-            props = cp.cuda.runtime.getDeviceProperties(0)
-            gpu_info = {
-                "name": props["name"].decode(),
-                "memory_mb": props["totalGlobalMem"] // (1024 * 1024),
-            }
-    except Exception:
-        pass
+    # Check GPU via gpu_service
+    from app.services.gpu_service import gpu_service
+    gpu_info = gpu_service.get_info()
+
+    # Determine parallel backend
+    if ray_available:
+        parallel_backend = "ray"
+    elif cpu_cores > 1:
+        parallel_backend = "process_pool"
+    else:
+        parallel_backend = "sequential"

    return {
        "cpu_cores": cpu_cores,
        "parallel_workers": min(cpu_cores, 14),
-        "parallel_backend": "ray" if ray_available else "sequential",
+        "parallel_backend": parallel_backend,
        "ray_available": ray_available,
        "ray_initialized": ray_initialized,
        "gpu": gpu_info,
-        "gpu_enabled": gpu_info is not None,
+        "gpu_available": gpu_info.get("available", False),
    }
--- a/backend/app/api/routes/terrain.py
+++ b/backend/app/api/routes/terrain.py
@@ -1,4 +1,6 @@
 import os
+import asyncio
+import math

 from fastapi import APIRouter, HTTPException, Query
 from fastapi.responses import FileResponse
@@ -11,6 +13,46 @@ from app.services.los_service import los_service
 router = APIRouter()


+def _build_elevation_grid(min_lat, max_lat, min_lon, max_lon, resolution):
+    """Build a 2D elevation grid. Runs in thread executor (CPU-bound)."""
+    import numpy as np
+
+    rows = min(resolution, 200)
+    cols = min(resolution, 200)
+
+    lats = np.linspace(max_lat, min_lat, rows)   # north to south
+    lons = np.linspace(min_lon, max_lon, cols)
+
+    grid = []
+    min_elev = float('inf')
+    max_elev = float('-inf')
+
+    for lat in lats:
+        row = []
+        for lon in lons:
+            elev = terrain_service.get_elevation_sync(float(lat), float(lon))
+            row.append(elev)
+            if elev < min_elev:
+                min_elev = elev
+            if elev > max_elev:
+                max_elev = elev
+        grid.append(row)
+
+    return {
+        "grid": grid,
+        "rows": rows,
+        "cols": cols,
+        "min_elevation": min_elev if min_elev != float('inf') else 0,
+        "max_elevation": max_elev if max_elev != float('-inf') else 0,
+        "bbox": {
+            "min_lat": min_lat,
+            "max_lat": max_lat,
+            "min_lon": min_lon,
+            "max_lon": max_lon,
+        },
+    }
+
+
@router.get("/elevation")
 async def get_elevation(
    lat: float = Query(..., ge=-90, le=90, description="Latitude"),
@@ -26,6 +68,42 @@ async def get_elevation(
    }


+@router.get("/elevation-grid")
+async def get_elevation_grid(
+    min_lat: float = Query(..., ge=-90, le=90, description="South boundary"),
+    max_lat: float = Query(..., ge=-90, le=90, description="North boundary"),
+    min_lon: float = Query(..., ge=-180, le=180, description="West boundary"),
+    max_lon: float = Query(..., ge=-180, le=180, description="East boundary"),
+    resolution: int = Query(100, ge=10, le=200, description="Grid size (rows/cols)"),
+):
+    """Get elevation grid for a bounding box. Returns a 2D array for terrain visualization."""
+    if max_lat <= min_lat or max_lon <= min_lon:
+        raise HTTPException(400, "Invalid bbox: max must be greater than min")
+    if (max_lat - min_lat) > 2.0 or (max_lon - min_lon) > 2.0:
+        raise HTTPException(400, "Bbox too large (max 2 degrees per axis)")
+
+    # Ensure terrain tiles are loaded for this area
+    await terrain_service.ensure_tiles_for_bbox(min_lat, min_lon, max_lat, max_lon)
+
+    # Pre-load all tiles that cover the bbox
+    lat_start = int(math.floor(min_lat))
+    lat_end = int(math.floor(max_lat))
+    lon_start = int(math.floor(min_lon))
+    lon_end = int(math.floor(max_lon))
+    for lat_i in range(lat_start, lat_end + 1):
+        for lon_i in range(lon_start, lon_end + 1):
+            tile_name = terrain_service.get_tile_name(lat_i + 0.5, lon_i + 0.5)
+            terrain_service._load_tile(tile_name)
+
+    # Build grid in thread executor (CPU-bound sync calls)
+    loop = asyncio.get_event_loop()
+    result = await loop.run_in_executor(
+        None, _build_elevation_grid,
+        min_lat, max_lat, min_lon, max_lon, resolution,
+    )
+    return result
+
+
@router.get("/profile")
 async def get_elevation_profile(
    lat1: float = Query(..., description="Start latitude"),
@@ -87,9 +165,9 @@ async def check_fresnel_clearance(
@router.get("/tiles")
 async def list_cached_tiles():
    """List cached SRTM tiles"""
-    tiles = list(terrain_service.cache_dir.glob("*.hgt"))
+    tiles = list(terrain_service.terrain_path.glob("*.hgt"))
    return {
-        "cache_dir": str(terrain_service.cache_dir),
+        "cache_dir": str(terrain_service.terrain_path),
        "tiles": [t.stem for t in tiles],
        "count": len(tiles)
    }
--- a/backend/app/services/coverage_service.py
+++ b/backend/app/services/coverage_service.py
@@ -55,6 +55,7 @@ from app.services.indoor_service import indoor_service
 from app.services.atmospheric_service import atmospheric_service
 from app.services.parallel_coverage_service import (
    calculate_coverage_parallel, get_cpu_count, get_parallel_backend,
+    CancellationToken,
 )


@@ -280,7 +281,8 @@ class CoverageService:
    async def calculate_coverage(
        self,
        site: SiteParams,
-        settings: CoverageSettings
+        settings: CoverageSettings,
+        cancel_token: Optional[CancellationToken] = None,
    ) -> List[CoveragePoint]:
        """
        Calculate coverage grid for a single site
@@ -352,6 +354,32 @@ class CoverageService:
              f"pre-computed {len(grid)} elevations")
        _clog(f"━━━ PHASE 2 done: {terrain_time:.1f}s ━━━")

+        # ━━━ PHASE 2.5: Vectorized pre-computation (GPU/NumPy) ━━━
+        from app.services.gpu_service import gpu_service
+
+        t_gpu = time.time()
+        grid_lats = np.array([lat for lat, lon in grid])
+        grid_lons = np.array([lon for lat, lon in grid])
+
+        pre_distances = gpu_service.precompute_distances(
+            grid_lats, grid_lons, site.lat, site.lon
+        )
+        pre_path_loss = gpu_service.precompute_path_loss(
+            pre_distances, site.frequency, site.height
+        )
+
+        # Build lookup dict for point loop
+        precomputed = {}
+        for i, (lat, lon) in enumerate(grid):
+            precomputed[(lat, lon)] = {
+                'distance': float(pre_distances[i]),
+                'path_loss': float(pre_path_loss[i]),
+            }
+
+        gpu_time = time.time() - t_gpu
+        _clog(f"━━━ PHASE 2.5: Vectorized pre-computation done: {gpu_time:.3f}s "
+              f"({len(grid)} points, backend={'GPU' if gpu_service.available else 'CPU/NumPy'}) ━━━")
+
        # ━━━ PHASE 3: Point calculation ━━━
        dominant_path_service._log_count = 0  # Reset diagnostic counter
        t_points = time.time()
@@ -368,12 +396,15 @@ class CoverageService:
                loop = asyncio.get_event_loop()
                result_dicts, timing = await loop.run_in_executor(
                    None,
-                    calculate_coverage_parallel,
+                    lambda: calculate_coverage_parallel(
                        grid, point_elevations,
                        site.model_dump(), settings.model_dump(),
                        self.terrain._tile_cache,
                        buildings, streets, water_bodies, vegetation_areas,
                        site_elevation, num_workers, _clog,
+                        cancel_token=cancel_token,
+                        precomputed=precomputed,
+                    ),
                )

                # Convert dicts back to CoveragePoint objects
@@ -389,10 +420,13 @@ class CoverageService:
            loop = asyncio.get_event_loop()
            points, timing = await loop.run_in_executor(
                None,
-                self._run_point_loop,
+                lambda: self._run_point_loop(
                    grid, site, settings, buildings, streets,
                    spatial_idx, water_bodies, vegetation_areas,
-                site_elevation, point_elevations
+                    site_elevation, point_elevations,
+                    cancel_token=cancel_token,
+                    precomputed=precomputed,
+                ),
            )

        points_time = time.time() - t_points
@@ -423,7 +457,8 @@ class CoverageService:
    async def calculate_multi_site_coverage(
        self,
        sites: List[SiteParams],
-        settings: CoverageSettings
+        settings: CoverageSettings,
+        cancel_token: Optional[CancellationToken] = None,
    ) -> List[CoveragePoint]:
        """
        Calculate combined coverage from multiple sites
@@ -437,7 +472,7 @@ class CoverageService:

        # Get all individual coverages
        all_coverages = await asyncio.gather(*[
-            self.calculate_coverage(site, settings)
+            self.calculate_coverage(site, settings, cancel_token)
            for site in sites
        ])

@@ -485,7 +520,8 @@ class CoverageService:
    def _run_point_loop(
        self, grid, site, settings, buildings, streets,
        spatial_idx, water_bodies, vegetation_areas,
-        site_elevation, point_elevations
+        site_elevation, point_elevations,
+        cancel_token=None, precomputed=None,
    ):
        """Sync point loop - runs in ThreadPoolExecutor, bypasses event loop."""
        points = []
@@ -496,14 +532,22 @@ class CoverageService:
        log_interval = max(1, total // 20)

        for i, (lat, lon) in enumerate(grid):
+            if cancel_token and cancel_token.is_cancelled:
+                _clog(f"Cancelled at {i}/{total}")
+                break
+
            if i % log_interval == 0:
                _clog(f"Progress: {i}/{total} ({i*100//total}%)")

+            pre = precomputed.get((lat, lon)) if precomputed else None
+
            point = self._calculate_point_sync(
                site, lat, lon, settings, buildings, streets,
                spatial_idx, water_bodies, vegetation_areas,
                site_elevation, point_elevations.get((lat, lon), 0.0),
-                timing
+                timing,
+                precomputed_distance=pre.get('distance') if pre else None,
+                precomputed_path_loss=pre.get('path_loss') if pre else None,
            )
            if point.rsrp >= settings.min_signal:
                points.append(point)
@@ -523,16 +567,24 @@ class CoverageService:
        vegetation_areas: List[VegetationArea],
        site_elevation: float,
        point_elevation: float,
-        timing: dict
+        timing: dict,
+        precomputed_distance: Optional[float] = None,
+        precomputed_path_loss: Optional[float] = None,
    ) -> CoveragePoint:
        """Fully synchronous point calculation. All terrain tiles must be pre-loaded."""

-        # Distance
+        # Distance (use precomputed if available)
+        if precomputed_distance is not None:
+            distance = precomputed_distance
+        else:
            distance = TerrainService.haversine_distance(site.lat, site.lon, lat, lon)
        if distance < 1:
            distance = 1

-        # Base path loss
+        # Base path loss (use precomputed if available)
+        if precomputed_path_loss is not None:
+            path_loss = precomputed_path_loss
+        else:
            path_loss = self._okumura_hata(distance, site.frequency, site.height, 1.5)

        # Antenna pattern
--- a/backend/app/services/gpu_service.py
+++ b/backend/app/services/gpu_service.py
@@ -0,0 +1,119 @@
+"""
+GPU-accelerated computation service using CuPy.
+Falls back to NumPy when CuPy/CUDA is not available.
+
+Provides vectorized batch operations for coverage calculation:
+  - Haversine distance (site → all grid points)
+  - Okumura-Hata path loss (all distances at once)
+
+Usage:
+    from app.services.gpu_service import gpu_service, GPU_AVAILABLE
+"""
+
+import numpy as np
+from typing import Dict, Any, Optional
+
+# ── Try CuPy import ──
+
+GPU_AVAILABLE = False
+GPU_INFO: Optional[Dict[str, Any]] = None
+cp = None
+
+try:
+    import cupy as _cp
+    if _cp.cuda.runtime.getDeviceCount() > 0:
+        cp = _cp
+        GPU_AVAILABLE = True
+        props = _cp.cuda.runtime.getDeviceProperties(0)
+        GPU_INFO = {
+            "name": props["name"].decode() if isinstance(props["name"], bytes) else str(props["name"]),
+            "memory_mb": props["totalGlobalMem"] // (1024 * 1024),
+            "cuda_version": _cp.cuda.runtime.runtimeGetVersion(),
+        }
+        print(f"[GPU] CUDA available: {GPU_INFO['name']} ({GPU_INFO['memory_mb']} MB)", flush=True)
+except ImportError:
+    print("[GPU] CuPy not installed — using CPU/NumPy", flush=True)
+except Exception as e:
+    print(f"[GPU] CUDA check failed: {e} — using CPU/NumPy", flush=True)
+
+
+# Array module: cupy on GPU, numpy on CPU
+xp = cp if GPU_AVAILABLE else np
+
+
+def _to_cpu(arr):
+    """Transfer array to CPU numpy if on GPU."""
+    if GPU_AVAILABLE and hasattr(arr, 'get'):
+        return arr.get()
+    return np.asarray(arr)
+
+
+class GPUService:
+    """GPU-accelerated batch operations for coverage calculation."""
+
+    @property
+    def available(self) -> bool:
+        return GPU_AVAILABLE
+
+    def get_info(self) -> Dict[str, Any]:
+        """Return GPU info dict for system endpoint."""
+        if not GPU_AVAILABLE:
+            return {"available": False, "name": None, "memory_mb": None}
+        return {"available": True, **GPU_INFO}
+
+    def precompute_distances(
+        self,
+        grid_lats: np.ndarray,
+        grid_lons: np.ndarray,
+        site_lat: float,
+        site_lon: float,
+    ) -> np.ndarray:
+        """Vectorized haversine distance from site to all grid points.
+
+        Returns distances in meters as a CPU numpy array.
+        """
+        lat1 = xp.radians(xp.asarray(grid_lats, dtype=xp.float64))
+        lon1 = xp.radians(xp.asarray(grid_lons, dtype=xp.float64))
+        lat2 = xp.radians(xp.float64(site_lat))
+        lon2 = xp.radians(xp.float64(site_lon))
+
+        dlat = lat2 - lat1
+        dlon = lon2 - lon1
+
+        a = xp.sin(dlat / 2) ** 2 + xp.cos(lat1) * xp.cos(lat2) * xp.sin(dlon / 2) ** 2
+        c = 2 * xp.arcsin(xp.sqrt(a))
+
+        distances = 6371000.0 * c
+        return _to_cpu(distances)
+
+    def precompute_path_loss(
+        self,
+        distances: np.ndarray,
+        frequency_mhz: float,
+        tx_height: float,
+        rx_height: float = 1.5,
+    ) -> np.ndarray:
+        """Vectorized Okumura-Hata path loss for all distances.
+
+        Returns path loss in dB as a CPU numpy array.
+        """
+        d_arr = xp.asarray(distances, dtype=xp.float64)
+        d_km = xp.maximum(d_arr / 1000.0, 0.1)
+
+        freq = float(frequency_mhz)
+        h_tx = float(tx_height)
+        h_rx = float(rx_height)
+
+        log_f = xp.log10(xp.float64(freq))
+        log_hb = xp.log10(xp.float64(h_tx))
+
+        a_hm = (1.1 * log_f - 0.7) * h_rx - (1.56 * log_f - 0.8)
+
+        L = (69.55 + 26.16 * log_f - 13.82 * log_hb - a_hm
+             + (44.9 - 6.55 * log_hb) * xp.log10(d_km))
+
+        return _to_cpu(L)
+
+
+# Singleton
+gpu_service = GPUService()
--- a/backend/app/services/parallel_coverage_service.py
+++ b/backend/app/services/parallel_coverage_service.py
@@ -24,11 +24,28 @@ Usage:
 import os
 import sys
 import time
+import threading
 import multiprocessing as mp
 from typing import List, Dict, Tuple, Any, Optional, Callable
 import numpy as np


+# ── Cancellation token ──
+
+class CancellationToken:
+    """Thread-safe cancellation token for cooperative cancellation."""
+
+    def __init__(self):
+        self._event = threading.Event()
+
+    def cancel(self):
+        self._event.set()
+
+    @property
+    def is_cancelled(self) -> bool:
+        return self._event.is_set()
+
+
 # ── Try to import Ray ──

 RAY_AVAILABLE = False
@@ -80,14 +97,19 @@ def _ray_process_chunk_impl(chunk, terrain_cache, buildings, osm_data, config):
        "reflection": 0.0, "vegetation": 0.0,
    }

+    precomputed = config.get('precomputed')
+
    results = []
    for lat, lon, point_elev in chunk:
+        pre = precomputed.get((lat, lon)) if precomputed else None
        point = svc._calculate_point_sync(
            site, lat, lon, settings,
            buildings, osm_data.get('streets', []),
            _worker_spatial_idx, osm_data.get('water_bodies', []),
            osm_data.get('vegetation_areas', []),
            config['site_elevation'], point_elev, timing,
+            precomputed_distance=pre.get('distance') if pre else None,
+            precomputed_path_loss=pre.get('path_loss') if pre else None,
        )
        if point.rsrp >= settings.min_signal:
            results.append(point.model_dump())
@@ -162,13 +184,16 @@ def calculate_coverage_parallel(
    site_elevation: float,
    num_workers: Optional[int] = None,
    log_fn: Optional[Callable[[str], None]] = None,
+    cancel_token: Optional[CancellationToken] = None,
+    precomputed: Optional[Dict] = None,
 ) -> Tuple[List[Dict], Dict[str, float]]:
    """Calculate coverage points in parallel.

    Uses Ray if available (shared memory, zero-copy numpy), otherwise
-    falls back to sequential single-threaded calculation.
+    falls back to ProcessPoolExecutor or sequential single-threaded calculation.

-    Same signature as before — drop-in replacement.
+    cancel_token: cooperative cancellation — checked between chunks.
+    precomputed: dict mapping (lat, lon) -> {distance, path_loss} from GPU pre-computation.
    """
    if log_fn is None:
        log_fn = lambda msg: print(f"[PARALLEL] {msg}", flush=True)
@@ -185,7 +210,7 @@ def calculate_coverage_parallel(
                grid, point_elevations, site_dict, settings_dict,
                terrain_cache, buildings, streets, water_bodies,
                vegetation_areas, site_elevation,
-                num_workers, log_fn,
+                num_workers, log_fn, cancel_token, precomputed,
            )
        except Exception as e:
            log_fn(f"Ray execution failed: {e} — falling back to sequential")
@@ -198,7 +223,7 @@ def calculate_coverage_parallel(
                grid, point_elevations, site_dict, settings_dict,
                terrain_cache, buildings, streets, water_bodies,
                vegetation_areas, site_elevation,
-                pool_workers, log_fn,
+                pool_workers, log_fn, cancel_token, precomputed,
            )
        except Exception as e:
            log_fn(f"ProcessPool failed: {e} — falling back to sequential")
@@ -208,7 +233,7 @@ def calculate_coverage_parallel(
    return _calculate_sequential(
        grid, point_elevations, site_dict, settings_dict,
        buildings, streets, water_bodies, vegetation_areas,
-        site_elevation, log_fn,
+        site_elevation, log_fn, cancel_token, precomputed,
    )


@@ -219,15 +244,13 @@ def _calculate_with_ray(
    grid, point_elevations, site_dict, settings_dict,
    terrain_cache, buildings, streets, water_bodies,
    vegetation_areas, site_elevation,
-    num_workers, log_fn,
+    num_workers, log_fn, cancel_token=None, precomputed=None,
 ):
    """Execute using Ray shared-memory object store."""
    total_points = len(grid)
    log_fn(f"Ray mode: {total_points} points, {num_workers} workers")

    # ── Put large data into Ray object store ──
-    # Numpy arrays (terrain tiles) get zero-copy shared memory.
-    # Python objects (buildings) get serialized once, stored in plasma.
    t_put = time.time()

    terrain_ref = ray.put(terrain_cache)
@@ -239,12 +262,15 @@ def _calculate_with_ray(
    })

    cache_key = f"{site_dict['lat']:.4f},{site_dict['lon']:.4f},{len(buildings)}"
-    config_ref = ray.put({
+    config = {
        'site_dict': site_dict,
        'settings_dict': settings_dict,
        'site_elevation': site_elevation,
        'cache_key': cache_key,
-    })
+    }
+    if precomputed:
+        config['precomputed'] = precomputed
+    config_ref = ray.put(config)

    put_time = time.time() - t_put
    log_fn(f"ray.put() done in {put_time:.1f}s")
@@ -273,9 +299,19 @@ def _calculate_with_ray(
    completed_chunks = 0

    while remaining:
+        # Check cancellation before waiting
+        if cancel_token and cancel_token.is_cancelled:
+            log_fn(f"Cancelled — aborting {len(remaining)} remaining Ray chunks")
+            for ref in remaining:
+                try:
+                    ray.cancel(ref, force=True)
+                except Exception:
+                    pass
+            break
+
        # Wait for at least 1 result, batch up to ~10% for progress logging
        batch = max(1, min(len(remaining), total_chunks // 10 or 1))
-        done, remaining = ray.wait(remaining, num_returns=batch, timeout=600)
+        done, remaining = ray.wait(remaining, num_returns=batch, timeout=30)

        for ref in done:
            try:
@@ -333,14 +369,19 @@ def _pool_worker_process_chunk(args):
        "reflection": 0.0, "vegetation": 0.0,
    }

+    precomputed = config.get('precomputed')
+
    results = []
    for lat, lon, point_elev in chunk:
+        pre = precomputed.get((lat, lon)) if precomputed else None
        point = svc._calculate_point_sync(
            site, lat, lon, settings,
            buildings, osm_data.get('streets', []),
            spatial_idx, osm_data.get('water_bodies', []),
            osm_data.get('vegetation_areas', []),
            config['site_elevation'], point_elev, timing,
+            precomputed_distance=pre.get('distance') if pre else None,
+            precomputed_path_loss=pre.get('path_loss') if pre else None,
        )
        if point.rsrp >= settings.min_signal:
            results.append(point.model_dump())
@@ -352,7 +393,7 @@ def _calculate_with_process_pool(
    grid, point_elevations, site_dict, settings_dict,
    terrain_cache, buildings, streets, water_bodies,
    vegetation_areas, site_elevation,
-    num_workers, log_fn,
+    num_workers, log_fn, cancel_token=None, precomputed=None,
 ):
    """Execute using ProcessPoolExecutor with reduced workers to limit memory."""
    from concurrent.futures import ProcessPoolExecutor, as_completed
@@ -375,6 +416,8 @@ def _calculate_with_process_pool(
        'settings_dict': settings_dict,
        'site_elevation': site_elevation,
    }
+    if precomputed:
+        config['precomputed'] = precomputed
    osm_data = {
        'streets': streets,
        'water_bodies': water_bodies,
@@ -395,6 +438,13 @@ def _calculate_with_process_pool(

        completed_chunks = 0
        for future in as_completed(futures):
+            # Check cancellation between chunks
+            if cancel_token and cancel_token.is_cancelled:
+                log_fn(f"Cancelled — cancelling {len(futures) - completed_chunks - 1} pending futures")
+                for f in futures:
+                    f.cancel()
+                break
+
            try:
                chunk_results = future.result()
                all_results.extend(chunk_results)
@@ -428,7 +478,7 @@ def _calculate_with_process_pool(
 def _calculate_sequential(
    grid, point_elevations, site_dict, settings_dict,
    buildings, streets, water_bodies, vegetation_areas,
-    site_elevation, log_fn,
+    site_elevation, log_fn, cancel_token=None, precomputed=None,
 ):
    """Sequential fallback — no extra dependencies, runs in calling thread."""
    from app.services.coverage_service import CoverageService, SiteParams, CoverageSettings
@@ -453,15 +503,26 @@ def _calculate_sequential(
    t0 = time.time()
    results = []
    for i, (lat, lon) in enumerate(grid):
+        # Check cancellation
+        if cancel_token and cancel_token.is_cancelled:
+            log_fn(f"Sequential cancelled at {i}/{total}")
+            break
+
        if i % log_interval == 0:
            log_fn(f"Sequential: {i}/{total} ({i * 100 // total}%)")

        point_elev = point_elevations.get((lat, lon), 0.0)
+
+        # Use precomputed values if available
+        pre = precomputed.get((lat, lon)) if precomputed else None
+
        point = svc._calculate_point_sync(
            site, lat, lon, settings,
            buildings, streets, spatial_idx,
            water_bodies, vegetation_areas,
            site_elevation, point_elev, timing,
+            precomputed_distance=pre.get('distance') if pre else None,
+            precomputed_path_loss=pre.get('path_loss') if pre else None,
        )
        if point.rsrp >= settings.min_signal:
            results.append(point.model_dump())
--- a/backend/requirements.txt
+++ b/backend/requirements.txt
@@ -12,3 +12,5 @@ httpx==0.27.0
 aiosqlite>=0.19.0
 sqlalchemy>=2.0.0
 ray[default]>=2.9.0
+# GPU acceleration (optional — install cupy-cuda12x for NVIDIA GPU support)
+# cupy-cuda12x>=13.0.0
--- a/desktop/main.js
+++ b/desktop/main.js
@@ -270,11 +270,11 @@ function createMainWindow() {

  // Save window state on close and trigger shutdown
  mainWindow.on('close', () => {
+    log('[CLOSE] Window close event fired, isQuitting=' + isQuitting);
    try {
      const bounds = mainWindow.getBounds();
      store.set('windowState', bounds);
    } catch (_e) {}
-    log('Main window closing — killing backend');
    isQuitting = true;
    killBackend();
  });
@@ -321,34 +321,43 @@ function createMainWindow() {

 function killBackend() {
  const pid = backendPid || backendProcess?.pid;
-  if (!pid) return;
+  if (!pid) {
+    log('[KILL] killBackend() called — no backend PID to kill');
+    return;
+  }

-  log(`Killing backend (PID ${pid})...`);
+  log(`[KILL] killBackend() called, platform=${process.platform}, PID=${pid}`);

  try {
    if (process.platform === 'win32') {
      // Windows: taskkill with /F (force) /T (tree — kills child processes too)
+      log(`[KILL] Running: taskkill /F /T /PID ${pid}`);
      execSync(`taskkill /F /T /PID ${pid}`, { stdio: 'ignore' });
+      log('[KILL] taskkill completed successfully');
    } else {
      // Unix: kill process group
      try {
+        log(`[KILL] Sending SIGTERM to process group -${pid}`);
        process.kill(-pid, 'SIGTERM');
      } catch (_e) {
+        log(`[KILL] Process group kill failed, sending SIGTERM to PID ${pid}`);
        process.kill(pid, 'SIGTERM');
      }
    }
  } catch (e) {
+    log(`[KILL] Primary kill failed: ${e.message}, trying SIGKILL fallback`);
    // Fallback: try normal kill via process handle
    try {
      backendProcess?.kill('SIGKILL');
+      log('[KILL] Fallback SIGKILL sent via process handle');
    } catch (_e2) {
-      // Already dead — that's fine
+      log('[KILL] Fallback also failed — process likely already dead');
    }
  }

  backendPid = null;
  backendProcess = null;
-  log('Backend killed');
+  log(`[KILL] Backend cleanup complete (PID was ${pid})`);
 }

 // ── App lifecycle ──────────────────────────────────────────────────
@@ -381,7 +390,7 @@ app.whenReady().then(async () => {
 });

 app.on('window-all-closed', () => {
-  log('Event: window-all-closed');
+  log('[CLOSE] window-all-closed fired');
  isQuitting = true;
  killBackend();

@@ -397,13 +406,13 @@ app.on('activate', () => {
 });

 app.on('before-quit', () => {
-  log('Event: before-quit');
+  log('[CLOSE] before-quit fired');
  isQuitting = true;
  killBackend();
 });

 app.on('will-quit', () => {
-  log('Event: will-quit');
+  log('[CLOSE] will-quit fired');
  killBackend();

  if (backendLogStream) {
@@ -414,6 +423,10 @@ app.on('will-quit', () => {

 // Last resort: ensure backend is killed when Node process exits
 process.on('exit', () => {
+  try {
+    console.log(`[KILL] process.exit handler, backendPid=${backendPid}`);
+  } catch (_e) { /* log stream may be closed */ }
+
  if (backendPid) {
    try {
      if (process.platform === 'win32') {
--- a/docs/RFCP-ARCHITECTURE.md
+++ b/docs/RFCP-ARCHITECTURE.md
--- a/docs/RFCP-Project-Roadmap-Complete.md
+++ b/docs/RFCP-Project-Roadmap-Complete.md
--- a/docs/devlog/installer/RFCP-Phase-2.1-Desktop-Complete.md
+++ b/docs/devlog/installer/RFCP-Phase-2.1-Desktop-Complete.md
--- a/docs/devlog/installer/RFCP-Phase-2.2-Offline-Data-Caching.md
+++ b/docs/devlog/installer/RFCP-Phase-2.2-Offline-Data-Caching.md
--- a/docs/devlog/installer/RFCP-Phase-2.3-Performance-Optimization.md
+++ b/docs/devlog/installer/RFCP-Phase-2.3-Performance-Optimization.md
--- a/frontend/src/App.tsx
+++ b/frontend/src/App.tsx
@@ -102,6 +102,8 @@ export default function App() {
  const setShowElevationInfo = useSettingsStore((s) => s.setShowElevationInfo);
  const showElevationOverlay = useSettingsStore((s) => s.showElevationOverlay);
  const setShowElevationOverlay = useSettingsStore((s) => s.setShowElevationOverlay);
+  const elevationOpacity = useSettingsStore((s) => s.elevationOpacity);
+  const setElevationOpacity = useSettingsStore((s) => s.setElevationOpacity);

  // History (undo/redo)
  const canUndo = useHistoryStore((s) => s.canUndo);
@@ -1059,6 +1061,19 @@ export default function App() {
                  />
                  Elevation Colors
                </label>
+                {showElevationOverlay && (
+                  <div className="pl-6">
+                    <NumberInput
+                      label="Opacity"
+                      value={Math.round(elevationOpacity * 100)}
+                      onChange={(v) => setElevationOpacity(v / 100)}
+                      min={10}
+                      max={100}
+                      step={10}
+                      unit="%"
+                    />
+                  </div>
+                )}
              </div>
            </div>

--- a/frontend/src/components/map/ElevationLayer.tsx
+++ b/frontend/src/components/map/ElevationLayer.tsx
@@ -0,0 +1,176 @@
+import { useEffect, useRef, useCallback } from 'react';
+import { useMap } from 'react-leaflet';
+import L from 'leaflet';
+import { api } from '@/services/api.ts';
+
+interface ElevationLayerProps {
+  visible: boolean;
+  opacity: number;
+}
+
+// Terrain color gradient: low = green, mid = yellow/tan, high = brown/white
+const COLOR_STOPS = [
+  { elev: 0, r: 20, g: 100, b: 40 },      // dark green
+  { elev: 100, r: 50, g: 160, b: 60 },     // green
+  { elev: 200, r: 130, g: 200, b: 80 },    // yellow-green
+  { elev: 350, r: 210, g: 190, b: 100 },   // tan
+  { elev: 500, r: 180, g: 140, b: 80 },    // brown
+  { elev: 800, r: 160, g: 120, b: 90 },    // dark brown
+  { elev: 1200, r: 200, g: 190, b: 180 },  // light grey
+  { elev: 2000, r: 240, g: 240, b: 240 },  // near white
+];
+
+function getColorForElevation(elev: number): [number, number, number] {
+  if (elev <= COLOR_STOPS[0].elev) {
+    return [COLOR_STOPS[0].r, COLOR_STOPS[0].g, COLOR_STOPS[0].b];
+  }
+
+  for (let i = 1; i < COLOR_STOPS.length; i++) {
+    if (elev <= COLOR_STOPS[i].elev) {
+      const low = COLOR_STOPS[i - 1];
+      const high = COLOR_STOPS[i];
+      const t = (elev - low.elev) / (high.elev - low.elev);
+      return [
+        Math.round(low.r + t * (high.r - low.r)),
+        Math.round(low.g + t * (high.g - low.g)),
+        Math.round(low.b + t * (high.b - low.b)),
+      ];
+    }
+  }
+
+  const last = COLOR_STOPS[COLOR_STOPS.length - 1];
+  return [last.r, last.g, last.b];
+}
+
+export default function ElevationLayer({ visible, opacity }: ElevationLayerProps) {
+  const map = useMap();
+  const overlayRef = useRef<L.ImageOverlay | null>(null);
+  const debounceRef = useRef<ReturnType<typeof setTimeout> | null>(null);
+  const abortRef = useRef<AbortController | null>(null);
+  const lastBoundsRef = useRef<string>('');
+
+  const removeOverlay = useCallback(() => {
+    if (overlayRef.current) {
+      map.removeLayer(overlayRef.current);
+      overlayRef.current = null;
+    }
+  }, [map]);
+
+  const fetchAndRender = useCallback(async () => {
+    // Abort previous request
+    if (abortRef.current) {
+      abortRef.current.abort();
+    }
+    abortRef.current = new AbortController();
+
+    const bounds = map.getBounds();
+    const minLat = bounds.getSouth();
+    const maxLat = bounds.getNorth();
+    const minLon = bounds.getWest();
+    const maxLon = bounds.getEast();
+
+    // Skip if bbox is too large (zoomed out too far)
+    if ((maxLat - minLat) > 2.0 || (maxLon - minLon) > 2.0) {
+      removeOverlay();
+      return;
+    }
+
+    // Skip if bounds haven't changed significantly
+    const boundsKey = `${minLat.toFixed(3)},${maxLat.toFixed(3)},${minLon.toFixed(3)},${maxLon.toFixed(3)}`;
+    if (boundsKey === lastBoundsRef.current) return;
+    lastBoundsRef.current = boundsKey;
+
+    // Choose resolution based on viewport size
+    const zoom = map.getZoom();
+    const resolution = zoom >= 13 ? 150 : zoom >= 10 ? 100 : 60;
+
+    try {
+      const data = await api.getElevationGrid(minLat, maxLat, minLon, maxLon, resolution);
+
+      // Check if component was unmounted or request was superseded
+      if (abortRef.current?.signal.aborted) return;
+
+      // Render to canvas
+      const canvas = document.createElement('canvas');
+      canvas.width = data.cols;
+      canvas.height = data.rows;
+      const ctx = canvas.getContext('2d');
+      if (!ctx) return;
+
+      const imageData = ctx.createImageData(data.cols, data.rows);
+      const pixels = imageData.data;
+
+      for (let row = 0; row < data.rows; row++) {
+        for (let col = 0; col < data.cols; col++) {
+          const elev = data.grid[row][col];
+          const [r, g, b] = getColorForElevation(elev);
+          const idx = (row * data.cols + col) * 4;
+          pixels[idx] = r;
+          pixels[idx + 1] = g;
+          pixels[idx + 2] = b;
+          pixels[idx + 3] = 255;
+        }
+      }
+      ctx.putImageData(imageData, 0, 0);
+
+      // Remove old overlay
+      removeOverlay();
+
+      // Add new overlay
+      const leafletBounds = L.latLngBounds(
+        [data.bbox.min_lat, data.bbox.min_lon],
+        [data.bbox.max_lat, data.bbox.max_lon],
+      );
+      overlayRef.current = L.imageOverlay(canvas.toDataURL(), leafletBounds, {
+        opacity,
+        interactive: false,
+        zIndex: 97,
+      });
+      overlayRef.current.addTo(map);
+    } catch (_e) {
+      // Silently ignore fetch errors (network issues, aborts, etc.)
+    }
+  }, [map, opacity, removeOverlay]);
+
+  // Update opacity on existing overlay
+  useEffect(() => {
+    if (overlayRef.current) {
+      overlayRef.current.setOpacity(opacity);
+    }
+  }, [opacity]);
+
+  // Main effect: toggle visibility and listen to map moves
+  useEffect(() => {
+    if (!visible) {
+      removeOverlay();
+      lastBoundsRef.current = '';
+      return;
+    }
+
+    const onMoveEnd = () => {
+      if (debounceRef.current) {
+        clearTimeout(debounceRef.current);
+      }
+      debounceRef.current = setTimeout(() => {
+        fetchAndRender();
+      }, 500);
+    };
+
+    map.on('moveend', onMoveEnd);
+    // Initial fetch
+    fetchAndRender();
+
+    return () => {
+      map.off('moveend', onMoveEnd);
+      if (debounceRef.current) {
+        clearTimeout(debounceRef.current);
+      }
+      if (abortRef.current) {
+        abortRef.current.abort();
+      }
+      removeOverlay();
+    };
+  }, [map, visible, fetchAndRender, removeOverlay]);
+
+  return null;
+}
--- a/frontend/src/components/map/Map.tsx
+++ b/frontend/src/components/map/Map.tsx
@@ -11,6 +11,7 @@ import MapExtras from './MapExtras.tsx';
 import CoordinateGrid from './CoordinateGrid.tsx';
 import MeasurementTool from './MeasurementTool.tsx';
 import ElevationDisplay from './ElevationDisplay.tsx';
+import ElevationLayer from './ElevationLayer.tsx';

 interface MapViewProps {
  onMapClick: (lat: number, lon: number) => void;
@@ -60,6 +61,7 @@ export default function MapView({ onMapClick, onEditSite, children }: MapViewPro
  const showElevationInfo = useSettingsStore((s) => s.showElevationInfo);
  const showElevationOverlay = useSettingsStore((s) => s.showElevationOverlay);
  const setShowElevationOverlay = useSettingsStore((s) => s.setShowElevationOverlay);
+  const elevationOpacity = useSettingsStore((s) => s.elevationOpacity);
  const addToast = useToastStore((s) => s.addToast);
  const mapRef = useRef<LeafletMap | null>(null);

@@ -95,16 +97,8 @@ export default function MapView({ onMapClick, onEditSite, children }: MapViewPro
            zIndex={100}
          />
        )}
-        {/* Elevation color overlay (OpenTopoMap — no API key required) */}
-        {showElevationOverlay && (
-          <TileLayer
-            attribution='Map data: &copy; <a href="https://openstreetmap.org">OpenStreetMap</a>, SRTM | Style: &copy; <a href="https://opentopomap.org">OpenTopoMap</a> (<a href="https://creativecommons.org/licenses/by-sa/3.0/">CC-BY-SA</a>)'
-            url="https://{s}.tile.opentopomap.org/{z}/{x}/{y}.png"
-            opacity={0.5}
-            maxZoom={17}
-            zIndex={97}
-          />
-        )}
+        {/* Elevation color overlay from SRTM terrain data */}
+        <ElevationLayer visible={showElevationOverlay} opacity={elevationOpacity} />
        <MapClickHandler onMapClick={onMapClick} />
        <MapExtras />
        {showElevationInfo && <ElevationDisplay />}
--- a/frontend/src/services/api.ts
+++ b/frontend/src/services/api.ts
@@ -97,6 +97,22 @@ export interface Preset {
  estimated_speed: string;
 }

+// === Elevation grid types ===
+
+export interface ElevationGridResponse {
+  grid: number[][];
+  rows: number;
+  cols: number;
+  min_elevation: number;
+  max_elevation: number;
+  bbox: {
+    min_lat: number;
+    max_lat: number;
+    min_lon: number;
+    max_lon: number;
+  };
+}
+
 // === API Client ===

 class ApiService {
@@ -148,6 +164,27 @@ class ApiService {
    return data.elevation;
  }

+  async getElevationGrid(
+    minLat: number,
+    maxLat: number,
+    minLon: number,
+    maxLon: number,
+    resolution: number = 100,
+  ): Promise<ElevationGridResponse> {
+    const params = new URLSearchParams({
+      min_lat: minLat.toString(),
+      max_lat: maxLat.toString(),
+      min_lon: minLon.toString(),
+      max_lon: maxLon.toString(),
+      resolution: resolution.toString(),
+    });
+    const response = await fetch(
+      `${API_BASE}/api/terrain/elevation-grid?${params}`
+    );
+    if (!response.ok) throw new Error('Failed to fetch elevation grid');
+    return response.json();
+  }
+
  // === Region / Caching API ===

  async getRegions(): Promise<RegionInfo[]> {
--- a/frontend/src/store/settings.ts
+++ b/frontend/src/store/settings.ts
@@ -11,6 +11,7 @@ interface SettingsState {
  measurementMode: boolean;
  showElevationInfo: boolean;
  showElevationOverlay: boolean;
+  elevationOpacity: number;
  setTheme: (theme: Theme) => void;
  setShowTerrain: (show: boolean) => void;
  setTerrainOpacity: (opacity: number) => void;
@@ -18,6 +19,7 @@ interface SettingsState {
  setMeasurementMode: (mode: boolean) => void;
  setShowElevationInfo: (show: boolean) => void;
  setShowElevationOverlay: (show: boolean) => void;
+  setElevationOpacity: (opacity: number) => void;
 }

 function applyTheme(theme: Theme) {
@@ -41,6 +43,7 @@ export const useSettingsStore = create<SettingsState>()(
      measurementMode: false,
      showElevationInfo: false,
      showElevationOverlay: false,
+      elevationOpacity: 0.5,
      setTheme: (theme: Theme) => {
        set({ theme });
        applyTheme(theme);
@@ -51,6 +54,7 @@ export const useSettingsStore = create<SettingsState>()(
      setMeasurementMode: (mode: boolean) => set({ measurementMode: mode }),
      setShowElevationInfo: (show: boolean) => set({ showElevationInfo: show }),
      setShowElevationOverlay: (show: boolean) => set({ showElevationOverlay: show }),
+      setElevationOpacity: (opacity: number) => set({ elevationOpacity: opacity }),
    }),
    {
      name: 'rfcp-settings',