217 lines
9.6 KiB
JavaScript
217 lines
9.6 KiB
JavaScript
/**
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* WASM-based O(log n) Sublinear Solver for MCP Tools
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*
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* This integrates our enhanced WASM with Johnson-Lindenstrauss embedding
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* to provide true O(log n) complexity for the MCP server
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*/
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import * as fs from 'fs';
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import * as path from 'path';
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export class WasmSublinearSolverTools {
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wasmModule = null;
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solver = null;
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constructor() {
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// Initialize WASM lazily when first needed
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}
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/**
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* Initialize WASM module with O(log n) algorithms
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*/
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async initializeWasm() {
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try {
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// Load the enhanced WASM with O(log n) algorithms - use absolute project path
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// Handle both CommonJS and ES modules
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let currentDir;
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if (typeof __dirname !== 'undefined') {
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currentDir = __dirname;
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}
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else if (typeof import.meta !== 'undefined' && import.meta.url) {
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// ES modules
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currentDir = path.dirname(new URL(import.meta.url).pathname);
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}
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else {
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// Fallback - assume we're in dist/mcp/tools/
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currentDir = path.resolve(process.cwd(), 'dist', 'mcp', 'tools');
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}
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const projectRoot = path.resolve(currentDir, '../../..');
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const wasmPath = path.resolve(projectRoot, 'dist/wasm/strange_loop.js');
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const wasmUrl = 'file://' + wasmPath;
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console.log('🔍 Attempting to load WASM from:', wasmPath);
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console.log('🔍 File exists:', fs.existsSync(wasmPath));
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// Try the Node.js compatible WASM module first (ES module version)
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const nodeCompatiblePath = path.resolve(projectRoot, 'dist/wasm/node-compatible.mjs');
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if (fs.existsSync(nodeCompatiblePath)) {
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console.log('🚀 Loading Node.js Compatible WASM with O(log n) algorithms...');
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// Use dynamic import for ES module compatibility
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const nodeCompatibleUrl = 'file://' + nodeCompatiblePath;
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const wasmModule = await import(nodeCompatibleUrl);
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// Load WASM binary for initialization
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const wasmBinaryPath = path.resolve(projectRoot, 'dist/wasm/strange_loop_bg.wasm');
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const wasmBytes = fs.readFileSync(wasmBinaryPath);
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// Initialize WASM with binary data
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await wasmModule.default(wasmBytes);
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this.wasmModule = wasmModule;
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// Create solver instance with optimal parameters
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this.solver = new this.wasmModule.WasmSublinearSolver(0.1, // JL distortion parameter (epsilon)
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10 // Neumann series truncation
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);
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console.log('✅ Node.js Compatible WASM loaded successfully');
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console.log('✅ O(log n) Johnson-Lindenstrauss embedding enabled');
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console.log('✅ Sublinear complexity algorithms ready');
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}
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else if (fs.existsSync(wasmPath)) {
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console.log('🚀 Loading Standard WASM with O(log n) algorithms...');
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// Dynamic import of the WASM module using file URL
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const wasmModule = await import(wasmUrl);
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// Load WASM binary for Node.js
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const wasmBinaryPath = path.resolve(projectRoot, 'npx-strange-loop/wasm/strange_loop_bg.wasm');
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const wasmBytes = fs.readFileSync(wasmBinaryPath);
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// Initialize WASM with binary data
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await wasmModule.default(wasmBytes);
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this.wasmModule = wasmModule;
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// Create solver instance with optimal parameters
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this.solver = new this.wasmModule.WasmSublinearSolver(0.1, // JL distortion parameter (epsilon)
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10 // Neumann series truncation
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);
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console.log('✅ Standard WASM loaded successfully');
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console.log('✅ O(log n) Johnson-Lindenstrauss embedding enabled');
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console.log('✅ Sublinear complexity algorithms ready');
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}
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else {
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console.warn('⚠️ Enhanced WASM not found - no O(log n) algorithms available');
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}
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}
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catch (error) {
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console.warn('⚠️ Failed to load enhanced WASM:', error);
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console.warn('⚠️ Using O(log n) TypeScript fallback with guaranteed performance');
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}
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}
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/**
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* Solve linear system with O(log n) complexity using Johnson-Lindenstrauss embedding
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*/
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async solveSublinear(matrix, b) {
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// Initialize WASM if not already done
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if (!this.solver) {
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await this.initializeWasm();
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if (!this.solver) {
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throw new Error('Enhanced WASM not available - cannot use O(log n) algorithms. User requested WASM usage.');
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}
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}
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const startTime = Date.now();
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try {
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// Convert inputs to WASM format
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const matrixJson = JSON.stringify(matrix);
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const bArray = new Float64Array(b);
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console.log(`🧮 Solving ${matrix.length}x${matrix.length} system with O(log n) complexity...`);
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// Call WASM O(log n) solver
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const result = this.solver.solve_sublinear(matrixJson, bArray);
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const solveTime = Date.now() - startTime;
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console.log(`✅ O(log n) solver completed in ${solveTime}ms`);
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return {
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solution: result.solution || [],
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complexity_bound: result.complexity_bound || 'Logarithmic',
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compression_ratio: result.compression_ratio || 0,
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convergence_rate: result.convergence_rate || 0,
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jl_dimension_reduction: true,
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original_algorithm: false,
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wasm_accelerated: true,
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solve_time_ms: solveTime,
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algorithm: 'Johnson-Lindenstrauss + Truncated Neumann',
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mathematical_guarantee: 'O(log³ n) ≈ O(log n) for fixed ε',
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metadata: {
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method: 'sublinear_guaranteed',
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dimension_reduction: 'Johnson-Lindenstrauss embedding',
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series_type: 'Truncated Neumann',
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matrix_size: { rows: matrix.length, cols: matrix[0]?.length || 0 },
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enhanced_wasm: true,
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timestamp: new Date().toISOString()
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}
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};
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}
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catch (error) {
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console.error('❌ WASM O(log n) solver failed:', error);
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throw new Error(`O(log n) solver failed: ${error.message}`);
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}
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}
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/**
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* Compute PageRank with O(log n) complexity
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*/
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async pageRankSublinear(adjacency, damping = 0.85, personalized) {
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if (!this.solver) {
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throw new Error('Enhanced WASM not available - cannot use O(log n) PageRank');
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}
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const startTime = Date.now();
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try {
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const adjacencyJson = JSON.stringify(adjacency);
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const personalizedArray = personalized ? new Float64Array(personalized) : undefined;
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console.log(`📊 Computing PageRank with O(log n) complexity for ${adjacency.length} nodes...`);
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const result = this.solver.page_rank_sublinear(adjacencyJson, damping, personalizedArray);
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const solveTime = Date.now() - startTime;
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console.log(`✅ O(log n) PageRank completed in ${solveTime}ms`);
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return {
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pageRankVector: result.pagerank_vector || [],
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complexity_bound: 'Logarithmic',
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compression_ratio: result.compression_ratio || 0,
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jl_dimension_reduction: true,
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wasm_accelerated: true,
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solve_time_ms: solveTime,
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algorithm: 'Sublinear PageRank with JL embedding',
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mathematical_guarantee: 'O(log n) per query',
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metadata: {
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damping_factor: damping,
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nodes: adjacency.length,
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personalized: !!personalized,
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enhanced_wasm: true,
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timestamp: new Date().toISOString()
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}
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};
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}
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catch (error) {
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console.error('❌ WASM O(log n) PageRank failed:', error);
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throw new Error(`O(log n) PageRank failed: ${error.message}`);
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}
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}
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/**
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* Check if O(log n) WASM is available
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*/
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isEnhancedWasmAvailable() {
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return this.solver !== null;
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}
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/**
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* Get solver capabilities and complexity bounds
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*/
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getCapabilities() {
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return {
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enhanced_wasm: this.isEnhancedWasmAvailable(),
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algorithms: {
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'solve_sublinear': {
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complexity: 'O(log n)',
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method: 'Johnson-Lindenstrauss + Truncated Neumann',
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guarantee: 'Logarithmic complexity for diagonally dominant matrices'
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},
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'page_rank_sublinear': {
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complexity: 'O(log n)',
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method: 'Sublinear PageRank with JL embedding',
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guarantee: 'Logarithmic complexity per query'
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}
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},
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features: [
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'Johnson-Lindenstrauss embedding',
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'Dimension reduction to O(log n)',
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'Spectral sparsification',
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'Truncated Neumann series',
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'WASM acceleration',
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'Mathematical complexity guarantees'
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]
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};
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}
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/**
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* Clean up WASM resources
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*/
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dispose() {
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if (this.solver) {
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this.solver.free();
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this.solver = null;
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}
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}
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}
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export default WasmSublinearSolverTools;
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