Run results for: Solving System of Linear Equations with Matrix

Run details:

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/134.0.0.0 Safari/537.36

Browser: Chrome 134

Operating system: Windows

Device Platform: Desktop

Date tested: one year ago

Benchmark engine: Benchmark.js

jStat

1.5M/s

Numeric JS (LU Decomposed first)

765K/s

Numeric JS (uses LUsolve under the hood)

525K/s

math.js (LU Decomposed first)

505K/s

Sparse - math.js (LU Decomposed first)

484K/s

math.js

279K/s

Sparse - Numeric JS (LU Decomposed first)

116K/s

Sparse - jStat

62K/s

Sparse - Numeric JS (uses LUsolve under the hood)

43K/s

Sparse - math.js

6K/s

View exact numbers

Test name	Executions per second
✓ jStat	1,536,220 Ops/sec
Numeric JS (LU Decomposed first)	764,818 Ops/sec
Numeric JS (uses LUsolve under the hood)	525,146 Ops/sec
math.js (LU Decomposed first)	504,750 Ops/sec
Sparse - math.js (LU Decomposed first)	484,482 Ops/sec
math.js	278,960 Ops/sec
Sparse - Numeric JS (LU Decomposed first)	116,250 Ops/sec
Sparse - jStat	61,697 Ops/sec
Sparse - Numeric JS (uses LUsolve under the hood)	42,696 Ops/sec
Sparse - math.js	5,883 Ops/sec

HTML Preparation code:

<!-- JStat -->
<script src="https://cdn.jsdelivr.net/jstat/latest/jstat.min.js"></script>
<!-- NumericJS -->
<script src="https://cdn.rawgit.com/sloisel/numeric/master/src/numeric.js"></script>
<!-- Math.js -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjs/3.9.0/math.min.js"></script>

Script Preparation code:

var A = [[11, -1, 0], [-1, 12, -1], [0, -1, 11]],
    B = [[87], [12] , [0]];

var Numeric_LUa = numeric.LU(A),
    math_LUa = math.lup(A);

var sparseA = [
  [1,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
  [0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
  [0,0,4,0,0,0,0,6,0,0,0,0,6,0,0,0,0,0,0,0],
  [0,1,0,2,0,0,0,0,0,0,0,0,0,6,0,6,0,0,0,0],
  [0,0,4,0,6,0,0,0,0,0,4,0,0,0,0,0,0,5,0,0],
  [0,0,0,2,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
  [0,0,0,0,6,0,23,4,0,0,0,0,0,0,6,0,0,0,0,0],
  [0,3,0,0,0,5,0,6,5,6,0,0,0,0,0,0,0,0,0,0],
  [0,0,0,0,0,2,6,45,66,0,0,0,0,0,0,0,6,0,0,0],
  [0,0,0,0,0,0,0,9,0,12,6,0,0,0,0,0,0,0,6,0],
  [0,0,3,0,0,0,0,0,23,0,45,0,0,5,0,0,0,0,0,0],
  [0,0,0,0,0,0,0,0,0,13,0,6,0,0,0,0,0,0,0,0],
  [3,0,0,0,3,0,56,0,0,0,5,0,5,0,0,0,0,6,0,0],
  [0,0,0,0,0,0,0,0,0,0,6,6,0,23,0,0,0,0,0,0],
  [0,3,0,0,0,0,0,0,0,0,0,0,8,6,67,0,0,0,0,0],
  [0,0,3,0,0,0,0,0,0,0,0,0,0,1,0,2,0,0,0,0],
  [0,0,0,0,0,0,0,5,0,0,0,4,0,0,5,0,43,6,0,0],
  [0,3,0,0,0,0,0,0,0,0,0,6,0,0,0,45,6,6,6,0],
  [0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,7,0],
  [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
],
sparseB = [[0],[0],[4],[0],[10],[0],[5],[0],[0],[0],[-5],[6],[0],[-6],[0],[0],[0],[10],[20],[4]];

var Numeric_sparse_LUa = numeric.LU(sparseA),
    math_sparse_LUa = math.lup(A);

Tests:

jStat
jStat.gauss_elimination(A, B);
Numeric JS (uses LUsolve under the hood)
numeric.solve(A, B);
Numeric JS (LU Decomposed first)
numeric.LUsolve(Numeric_LUa, B);
math.js
math.lusolve(A, B);
math.js (LU Decomposed first)
math.lusolve(math_LUa, B);
Sparse - jStat
jStat.gauss_elimination(sparseA, sparseB);
Sparse - Numeric JS (uses LUsolve under the hood)
numeric.solve(sparseA, sparseB);
Sparse - Numeric JS (LU Decomposed first)
numeric.LUsolve(Numeric_sparse_LUa, B);
Sparse - math.js
math.lusolve(sparseA, sparseB);
Sparse - math.js (LU Decomposed first)
math.lusolve(math_sparse_LUa, B);