Math MCP Server

# Pull Request: WebWorker Infrastructure for Parallel Mathematical Operations (v3.0.0 Phase 1) ## 🚀 Overview This PR implements **Phase 1** of the v3.0.0 refactoring roadmap: **WebWorker Infrastructure for Parallel Mathematical Operations**. This foundational work enables multi-threaded parallel processing of mathematical operations, targeting **3-4x performance improvements** for large-scale computations. --- ## 📋 What's Included ### 1. Comprehensive Refactoring Plan (`REFACTORING_PLAN.md`) - **741 lines** of detailed planning documentation - 6-phase roadmap for v3.0.0 development - Performance targets and benchmarking methodology - Architecture diagrams and technical specifications - Risk assessment and mitigation strategies ### 2. Complete WebWorker Infrastructure (7 new files, 3,180 lines) #### Core Components: **`src/workers/worker-types.ts`** (466 lines) - TypeScript interfaces and types for worker communication - Enums for operations, worker status, and task states - Type guards for runtime type checking - Comprehensive JSDoc documentation **`src/workers/worker-pool.ts`** (601 lines) - Worker pool manager with dynamic scaling (2-8 workers based on CPU cores) - Automatic worker lifecycle management (creation, reuse, termination) - Graceful shutdown with task completion grace period - Idle worker monitoring and resource cleanup - Performance statistics and monitoring **`src/workers/task-queue.ts`** (444 lines) - Priority-based task scheduling - FIFO ordering within same priority level - Task timeout protection (30s default, configurable) - Queue size limits to prevent DoS - Comprehensive task tracking and statistics **`src/workers/math-worker.ts`** (353 lines) - Worker thread implementation with WASM loading - Processes mathematical operations independently - Supports matrix and statistics operations - Chunked data processing for parallel execution - Error handling and performance tracking **`src/workers/chunk-utils.ts`** (499 lines) - Intelligent data chunking algorithms - Array chunking for statistics - Matrix row-based chunking - Matrix block-based chunking (for tiled operations) - Optimal chunk count calculation - Chunk validation and merging utilities **`src/workers/parallel-matrix.ts`** (417 lines) - Parallel matrix multiply (row-based splitting) - Parallel matrix transpose - Parallel matrix add/subtract - Automatic threshold-based routing **`src/workers/parallel-stats.ts`** (400 lines) - Parallel statistics: mean, sum, min, max - Parallel variance and standard deviation - Automatic threshold-based routing - Support for sample vs population calculations --- ## 🎯 Performance Targets | Operation | Size | Current (v2.1.0) | Target (v3.0.0) | Speedup | |-----------|------|------------------|-----------------|---------| | Matrix Multiply | 1000×1000 | 35,000ms | 8,750ms | **4x** | | Matrix Multiply | 100×100 | 45ms | 12ms | **3.75x** | | Stats Mean | 1M elements | 25ms | 6.5ms | **3.85x** | | Stats Mean | 100K elements | 2.5ms | 0.7ms | **3.5x** | --- ## 🏗️ Architecture ### Intelligent Multi-Tier Routing ``` ┌─────────────────────────────────────────────────┐ │ Operation Request │ └──────────────────┬──────────────────────────────┘ │ ┌─────────▼──────────┐ │ Size Check │ └─────────┬──────────┘ │ ┌──────────────┼──────────────┐ │ │ │ ▼ ▼ ▼ ┌───────┐ ┌──────────┐ ┌─────────────┐ │ Small │ │ Medium │ │ Large │ │mathjs │ │ WASM │ │ Workers + │ │ │ │ (1 core) │ │ WASM (N) │ └───────┘ └──────────┘ └─────────────┘ Fast Faster Fastest <10x10 10x10-100 100x100+ ``` ### Worker Pool Design ``` Main Thread │ ├─ WorkerPool │ │ │ ├─ TaskQueue (priority + timeout) │ │ ├─ Pending Tasks (max 1000) │ │ └─ Active Tasks (timeout tracking) │ │ │ └─ Workers (2-8 threads) │ ├─ Worker 1 [WASM loaded] │ ├─ Worker 2 [WASM loaded] │ ├─ Worker 3 [WASM loaded] │ └─ Worker N [WASM loaded] │ └─ Parallel Operations ├─ parallelMatrixMultiply() ├─ parallelMatrixTranspose() ├─ parallelStatsSum() └─ ... ``` --- ## ✨ Key Features ### 1. **Dynamic Worker Scaling** - Minimum 2 workers (always ready) - Maximum based on CPU cores (typically 4-8) - Automatic scaling based on queue size - Idle worker termination (after 1 min) ### 2. **Robust Task Management** - Priority-based scheduling - 30-second task timeout (configurable) - Queue size limit (1000 tasks max) - Graceful degradation on errors ### 3. **Data Chunking** - **Matrix operations**: Split by rows - Worker 1: Rows 0-249 - Worker 2: Rows 250-499 - Worker 3: Rows 500-749 - Worker 4: Rows 750-999 - **Statistics**: Split into equal chunks - Optimal chunk size calculation ### 4. **Safety & Reliability** - ✅ 100% TypeScript type safety - ✅ Comprehensive error handling - ✅ Graceful fallback to WASM/mathjs - ✅ Worker crash recovery - ✅ Memory leak prevention - ✅ Proper resource cleanup --- ## 📊 Supported Operations ### Matrix Operations (Parallel) - ✅ Matrix multiplication - ✅ Matrix transpose - ✅ Matrix addition - ✅ Matrix subtraction - ⏳ Matrix determinant (future - full matrix required) - ⏳ Matrix inverse (Phase 3) ### Statistics Operations (Parallel) - ✅ Mean - ✅ Sum - ✅ Min - ✅ Max - ✅ Variance - ✅ Standard deviation - ⚠️ Median (requires sorted data - challenging to parallelize) --- ## 🧪 Testing Status - ✅ **TypeScript compilation**: Passes - ✅ **Type checking**: No errors - ✅ **Build**: Successful - ⏳ **Unit tests**: Phase 5 (Week 6) - ⏳ **Integration tests**: Phase 5 (Week 6) - ⏳ **Performance benchmarks**: Phase 5 (Week 6) --- ## 🔄 Next Steps (Not in This PR) This PR contains **foundational infrastructure only**. The following phases will integrate and extend this work: **Phase 2 (Week 2):** Integration - Integrate worker pool into `wasm-wrapper.ts` - Update `tool-handlers.ts` to use parallel operations - Add configuration options - Update existing tests **Phase 3 (Week 4):** Advanced WASM - Matrix inverse (Gauss-Jordan) - LU decomposition (Doolittle) - QR decomposition (Householder) **Phase 4 (Week 5):** TypeScript Optimizations - Optimized small matrix operations - Streaming statistics - Memoization layer **Phase 5 (Week 6):** Testing & Benchmarking - Comprehensive unit tests - Integration tests - Performance regression tests - Benchmarking suite **Phase 6:** Documentation & Release - Update README - Performance charts - Migration guide - v3.0.0 release --- ## 🔍 Code Quality ### Metrics - **Total new code**: 3,921 lines (plan + implementation) - **Files created**: 8 - **TypeScript errors**: 0 - **Test coverage**: Will be added in Phase 5 ### Standards - ✅ 100% TypeScript (no `any` types) - ✅ Comprehensive JSDoc on all exports - ✅ Consistent error handling - ✅ Follows v2.1.0 code quality standards - ✅ ESLint compliant (when rules updated for new files) --- ## 📝 Breaking Changes **None.** This PR is purely additive: - No changes to existing APIs - No changes to existing files - All new code in `src/workers/` directory - Infrastructure is built but not yet activated --- ## 🎓 Documentation ### Added - `REFACTORING_PLAN.md` - Complete v3.0.0 roadmap ### JSDoc Coverage - All public functions: ✅ 100% - All interfaces: ✅ 100% - All classes: ✅ 100% - Usage examples: ✅ Included --- ## 🔐 Security Considerations ### Implemented - ✅ Task queue size limits (prevent DoS) - ✅ Task timeout protection - ✅ Worker crash isolation - ✅ Safe worker termination - ✅ Input validation in workers ### Future (Phase 2) - Memory usage limits per worker - CPU throttling options - Sandboxing for untrusted operations --- ## 🚦 Checklist - [x] TypeScript compilation passes - [x] No type errors - [x] Comprehensive JSDoc documentation - [x] Follows existing code style - [x] No breaking changes - [x] Refactoring plan documented - [x] Commits are clear and descriptive - [x] Branch pushed to remote - [ ] Integration tests (Phase 5) - [ ] Performance benchmarks (Phase 5) --- ## 💡 Reviewer Notes ### What to Review 1. **Architecture** - Is the worker pool design sound? 2. **Type Safety** - Are all types properly defined? 3. **Error Handling** - Are edge cases covered? 4. **Documentation** - Is JSDoc clear and helpful? 5. **Code Quality** - Does it meet project standards? ### What NOT to Review (Yet) - Integration with existing code (Phase 2) - Test coverage (Phase 5) - Performance metrics (Phase 5) - End-to-end functionality (Phase 2+) --- ## 📚 Related Issues - Relates to: Performance optimization roadmap - Part of: v3.0.0 milestone - Follows: v2.1.0 code quality improvements --- ## 🙏 Acknowledgments This work builds on the excellent foundation of: - v2.1.0 code quality improvements - v2.0.0 WASM integration - mathjs library --- **Ready for Review!** 🎉 This PR represents **Phase 1** of a 6-phase enhancement that will deliver significant performance improvements for mathematical operations through parallel processing.