#math #matrix #linear-algebra


Basic linear algebra routines

3 releases (breaking)

Uses new Rust 2021

0.3.0 Nov 24, 2022
0.2.0 Nov 23, 2022
0.0.0 Nov 22, 2022

#151 in Math

Download history 82/week @ 2022-11-19 10/week @ 2022-11-26 6/week @ 2022-12-03

98 downloads per month
Used in faer

MIT license



faer is a collection of crates that implement low level linear algebra routines in pure Rust. The aim is to eventually provide a fully featured library for linear algebra with focus on portability, correctness, and performance.

See the Wiki and the docs.rs documentation for code examples and usage instructions.

Questions about using the library, contributing, and future directions can be discussed in the Discord server.


Documentation Crate

The core module implements matrix structures, as well as BLAS-like matrix operations such as matrix multiplication and solving triangular linear systems.


Documentation Crate

The Cholesky module implements the LLT and LDLT matrix decompositions. These allow for solving symmetric/hermitian (+positive definite for LLT) linear systems.


Documentation Crate

The LU module implements the LU factorization with row pivoting, as well as the version with full pivoting.

faer-qr (WIP)

The QR module implements the QR decomposition with no pivoting, as well as the version with column pivoting.

Coming soon

  • faer-svd
  • faer-eigen


The benchmarks were run on an 11th Gen Intel(R) Core(TM) i5-11400 @ 2.60GHz.

Matrix multiplication

Multiplication of two square matrices of dimension n.

        faer (serial)      faer (parallel)   ndarray (openblas)      nalgebra (matrixmultiply)
   32           2.5µs                1.5µs                1.5µs                          2.8µs
   64          15.2µs                 10µs                8.1µs                         16.8µs
   96          44.2µs               18.2µs               26.2µs                         51.3µs
  128         102.7µs               19.8µs               36.7µs                        117.3µs
  192         334.8µs                 76µs               50.6µs                        381.1µs
  256         708.8µs              171.6µs              153.5µs                        746.3µs
  384           1.8ms                378µs              343.1µs                            2ms
  512           4.2ms              940.7µs                  1ms                          4.8ms
  640           8.7ms                2.3ms                1.9ms                          9.4ms
  768          15.2ms                3.7ms                2.9ms                         16.2ms
  896          24.4ms                6.2ms                5.3ms                           26ms
 1024          38.2ms                  9ms                7.4ms                         39.1ms

Triangular solve

Solving AX = B in place where A and B are two square matrices of dimension n, and A is a triangular matrix.

        faer (serial)      faer (parallel)   ndarray (openblas)      nalgebra (matrixmultiply)
   32           2.9µs                2.7µs               36.4µs                          8.6µs
   64          10.4µs               10.4µs               25.5µs                         50.4µs
   96          29.9µs               30.6µs               44.1µs                        158.6µs
  128            59µs               46.1µs              121.1µs                        375.3µs
  192         204.8µs              113.9µs              209.6µs                          971µs
  256         407.8µs              162.5µs              520.4µs                            2ms
  384           1.2ms              307.8µs                1.2ms                          6.8ms
  512           2.6ms              655.6µs                  3ms                         15.7ms
  640           4.9ms                1.4ms                4.9ms                         30.4ms
  768           8.2ms                2.1ms                8.7ms                         53.6ms
  896          12.7ms                3.6ms               11.3ms                         84.6ms
 1024          19.5ms                5.1ms               21.4ms                        125.9ms

Triangular inverse

Computing A^-1 where A is a square triangular matrix with dimension n.

        faer (serial)      faer (parallel)   ndarray (openblas)      nalgebra (matrixmultiply)
   32           3.2µs               31.3µs                  8µs                          8.4µs
   64           9.8µs                 37µs               23.1µs                         50.4µs
   96          24.2µs               59.2µs               46.6µs                        159.2µs
  128            37µs               62.4µs              134.5µs                        386.6µs
  192          96.5µs                 92µs              217.4µs                        954.2µs
  256           186µs              140.9µs              506.8µs                          1.9ms
  384           534µs              249.6µs                1.2ms                          7.2ms
  512           1.1ms              414.8µs                3.1ms                         17.4ms
  640           1.9ms              567.3µs                5.1ms                         32.6ms
  768           3.2ms              837.2µs                8.5ms                         56.8ms
  896           4.8ms                1.2ms               11.3ms                         88.3ms
 1024           7.2ms                1.8ms               21.5ms                        136.1ms

Cholesky decomposition

Factorizing a square matrix with dimension n as L×L.T, where L is lower triangular.

        faer (serial)      faer (parallel)   ndarray (openblas)      nalgebra (matrixmultiply)
   32           3.9µs                3.9µs                3.3µs                          3.4µs
   64            11µs               11.1µs                 38µs                         14.5µs
   96          28.6µs               28.6µs               72.2µs                         32.9µs
  128            38µs               38.2µs                121µs                         79.3µs
  192         113.3µs              122.1µs              222.4µs                        256.3µs
  256         180.4µs                174µs              544.5µs                        605.7µs
  384         496.4µs              476.4µs              942.1µs                            2ms
  512           1.2ms              689.3µs                  3ms                          5.4ms
  640             2ms                1.4ms                2.6ms                         10.3ms
  768           3.5ms                  2ms                4.6ms                         17.9ms
  896           5.4ms                3.1ms                5.5ms                         28.1ms
 1024           8.4ms                3.5ms                 12ms                         42.6ms

LU decomposition with partial pivoting

Factorizing a square matrix with dimension n as P×L×U, where P is a permutation matrix, L is unit lower triangular and U is upper triangular.

        faer (serial)      faer (parallel)   ndarray (openblas)      nalgebra (matrixmultiply)
   32           6.2µs                5.1µs                9.5µs                          7.1µs
   64          18.2µs               18.1µs               19.3µs                         37.1µs
   96          40.6µs               40.4µs               37.9µs                        109.3µs
  128          78.7µs               83.1µs                1.3ms                        250.4µs
  192         196.4µs                312µs                210µs                        821.2µs
  256           399µs              466.5µs              324.3µs                            2ms
  384           1.1ms              986.6µs              676.7µs                          6.7ms
  512           2.4ms                1.7ms                1.2ms                         11.4ms
  640           4.2ms                2.8ms                1.8ms                         21.2ms
  768             7ms                  4ms                2.7ms                         36.5ms
  896          10.4ms                5.5ms                4.2ms                         57.9ms
 1024          15.6ms                8.2ms                5.4ms                         91.2ms

LU decomposition with full pivoting

Factorizing a square matrix with dimension n as P×L×U×Q.T, where P and Q are permutation matrices, L is unit lower triangular and U is upper triangular.

        faer (serial)      faer (parallel)   ndarray (openblas)      nalgebra (matrixmultiply)
   32          13.3µs              733.4µs          UNAVAILABLE                         15.9µs
   64          44.1µs              595.8µs          UNAVAILABLE                        111.3µs
   96         109.7µs              682.3µs          UNAVAILABLE                        367.5µs
  128           229µs              974.1µs          UNAVAILABLE                        831.2µs
  192         578.9µs                1.7ms          UNAVAILABLE                          2.8ms
  256           1.3ms                2.6ms          UNAVAILABLE                          6.5ms
  384           4.3ms                4.9ms          UNAVAILABLE                         22.1ms
  512          10.8ms                8.1ms          UNAVAILABLE                         53.4ms
  640          18.9ms                 13ms          UNAVAILABLE                        102.7ms
  768          32.2ms               18.3ms          UNAVAILABLE                        177.2ms
  896          49.3ms               26.1ms          UNAVAILABLE                        281.6ms
 1024          78.6ms               35.7ms          UNAVAILABLE                        430.1ms

Matrix inverse

Computing the inverse of a square matrix with dimension n.

        faer (serial)      faer (parallel)   ndarray (openblas)      nalgebra (matrixmultiply)
   32          29.4µs              147.8µs              264.2µs                         26.3µs
   64          85.2µs               68.2µs               41.9µs                        148.3µs
   96         211.4µs              131.6µs              174.7µs                        436.7µs
  128         339.3µs              217.2µs              368.4µs                        993.1µs
  192         874.1µs              449.4µs              465.9µs                          3.4ms
  256           1.6ms              819.4µs              858.2µs                          7.5ms
  384           5.2ms                1.8ms                1.7ms                         19.1ms
  512           7.6ms                  4ms                3.3ms                         44.9ms
  640            13ms                6.8ms                5.4ms                         88.5ms
  768            22ms               11.3ms                8.5ms                        144.7ms
  896          33.2ms               17.1ms                 13ms                        231.6ms
 1024          49.5ms               23.6ms               19.3ms                        368.2ms


~76K SLoC