RANTAI
BETA
Numerical Computing Lab
Σ

RANTAI KomNumLab

BETA

Laboratorium komputasi numerik untuk analisis performa algoritma: scaling, runtime, memory, dan error analysis. Eksplorasi kompleksitas, stabilitas, dan trade-offs dengan visualisasi yang kaya.

Experiment Configuration

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Algorithm Recommender

Choose numerical algorithms to benchmark. Different algorithms have different computational complexities.

Gaussian Elimination
O(n³)

Direct method for solving linear systems

LU Decomposition
O(n³)

Factorization-based solver

Cholesky Decomposition
O(n³/3)

For positive definite matrices

Jacobi Method
O(kn²)

Iterative solver (k iterations)

Gauss-Seidel
O(kn²)

Faster iterative convergence

Conjugate Gradient
O(kn²)

For symmetric positive definite

GMRES
O(kn²)

General minimal residual method

QR Decomposition
O(n³)

Orthogonal factorization

SVD
O(n³)

Singular value decomposition

Power Method
O(kn²)

Dominant eigenvalue computation

FFT
O(n log n)

Fast Fourier Transform

Gradient Descent
O(kn)

Optimization algorithm

Please select at least one algorithm

Comma-separated list of matrix dimensions

Number of runs per configuration

For reproducible results

~0 seconds
0 algorithms × 5 sizes × 5 reps