refactor: move legacy migration examples to docs/archive subdirectory

Legacy Content Organization:
✅ MIGRATION EXAMPLES ARCHIVED: Moved legacy migration examples to documentation archive
- docs/archive/migration_examples/: Moved from root directory for better organization
- Contains GPU acceleration migration examples from CUDA to abstraction layer
- Educational/reference material for historical context and migration procedures

✅ LEGACY CONTENT IDENTIFIED:
- GPU Acceleration Migration: From CUDA-specific to backend-agnostic abstraction layer
- Migration Patterns: BEFORE/AFTER code examples showing evolution
- Legacy Import Paths: high_performance_cuda_accelerator, fastapi_cuda_zk_api
- Deprecated Classes: HighPerformanceCUDAZKAccelerator, ProductionCUDAZKAPI

✅ DOCUMENTATION ARCHIVE CONTENTS:
- MIGRATION_CHECKLIST.md: Step-by-step migration procedures
- basic_migration.py: Direct CUDA calls to abstraction layer examples
- api_migration.py: FastAPI endpoint migration examples
- config_migration.py: Configuration migration examples

✅ ROOT DIRECTORY CLEANUP: Removed legacy examples from production directory
- migration_examples/ moved to docs/archive/migration_examples/
- Root directory now contains only active production components
- Legacy migration examples preserved for historical reference

DIRECTORY STRUCTURE IMPROVEMENT:
📁 docs/archive/migration_examples/: Historical migration documentation
🏗️ Root Directory: Clean production structure with only active components
📚 Documentation Archive: Legacy content properly organized for reference

BENEFITS:
✅ Clean Production Directory: No legacy examples in root
✅ Historical Preservation: Migration examples preserved for reference
✅ Better Organization: Legacy content grouped in documentation archive
✅ Clear Separation: Active vs legacy content clearly distinguished

RESULT: Successfully moved legacy migration examples to docs/archive/migration_examples/ subdirectory, cleaning up the root directory while preserving historical migration documentation for future reference.

docs/archive/migration_examples/basic_migration.py

@@ -0,0 +1,40 @@
+#!/usr/bin/env python3
+"""
+Basic Migration Example
+
+Shows how to migrate from direct CUDA calls to the new abstraction layer.
+"""
+
+# BEFORE (Direct CUDA)
+# from high_performance_cuda_accelerator import HighPerformanceCUDAZKAccelerator
+# 
+# accelerator = HighPerformanceCUDAZKAccelerator()
+# if accelerator.initialized:
+#     result = accelerator.field_add_cuda(a, b)
+
+# AFTER (Abstraction Layer)
+import numpy as np
+from gpu_acceleration import GPUAccelerationManager, create_gpu_manager
+
+# Method 1: Auto-detect backend
+gpu = create_gpu_manager()
+gpu.initialize()
+
+a = np.array([1, 2, 3, 4], dtype=np.uint64)
+b = np.array([5, 6, 7, 8], dtype=np.uint64)
+
+result = gpu.field_add(a, b)
+print(f"Field addition result: {result}")
+
+# Method 2: Context manager (recommended)
+from gpu_acceleration import GPUAccelerationContext
+
+with GPUAccelerationContext() as gpu:
+    result = gpu.field_mul(a, b)
+    print(f"Field multiplication result: {result}")
+
+# Method 3: Quick functions
+from gpu_acceleration import quick_field_add
+
+result = quick_field_add(a, b)
+print(f"Quick field addition: {result}")