Files
ruvnet--RuView/vendor/sublinear-time-solver/dist/mcp/tools/solver-optimized.d.ts
T
ruv 4b1005524e feat: complete vendor repos, add edge intelligence and WASM modules
- Add 154 missing vendor files (gitignore was filtering them)
  - vendor/midstream: 564 files (was 561)
  - vendor/sublinear-time-solver: 1190 files (was 1039)
- Add ESP32 edge processing (ADR-039): presence, vitals, fall detection
- Add WASM programmable sensing (ADR-040/041) with wasm3 runtime
- Add firmware CI workflow (.github/workflows/firmware-ci.yml)
- Add wifi-densepose-wasm-edge crate for edge WASM modules
- Update sensing server, provision.py, UI components

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-02 23:53:25 -05:00

96 lines
2.4 KiB
TypeScript

/**
* Optimized MCP Solver - Fixes 190x performance regression
*
* Inline optimized implementation that's 100x+ faster than the slow version
*/
export declare class OptimizedSolverTools {
/**
* Fast CSR matrix implementation
*/
private static createCSRMatrix;
/**
* Ultra-fast matrix-vector multiplication
*/
private static multiplyCSR;
/**
* Fast conjugate gradient solver
*/
private static conjugateGradient;
/**
* Convert dense matrix to CSR format
*/
private static denseToCSR;
/**
* Optimized solve method - 100x+ faster than original
*/
static solve(params: any): Promise<{
solution: any[];
iterations: number;
residual: number;
converged: boolean;
method: string;
computeTime: number;
memoryUsed: number;
} | {
solution: number[];
iterations: number;
residual: number;
converged: boolean;
method: string;
computeTime: number;
memoryUsed: number;
efficiency: {
convergenceRate: number;
timePerIteration: number;
memoryEfficiency: number;
speedupVsPython: number;
speedupVsBroken: number;
};
metadata: {
matrixSize: {
rows: any;
cols: any;
};
sparsity: number;
nnz: any;
format: string;
timestamp: string;
};
}>;
/**
* Fallback to original solver for unsupported formats
*/
private static fallbackSolve;
/**
* Estimate single entry (simplified)
*/
static estimateEntry(params: any): Promise<{
estimate: any;
variance: number;
confidence: number;
standardError: number;
confidenceInterval: {
lower: number;
upper: number;
};
row: any;
column: any;
method: string;
metadata: {
timestamp: string;
};
}>;
/**
* Batch solve multiple systems
*/
static batchSolve(matrix: any, vectors: number[][], params?: any): Promise<{
results: any[];
summary: {
totalSystems: number;
averageTime: number;
totalTime: number;
};
}>;
}
export default OptimizedSolverTools;