Matrix function benchmarks

Source: R/benchmark_matrix_functions.R, R/benchmarks.R

A collection of matrix benchmark functions

  • FFT over 2,500,000 random values.

  • Eigenvalues of a 640x640 random matrix.

  • Determinant of a 2500x2500 random matrix.

  • Cholesky decomposition of a 3000x3000 matrix.

  • Inverse of a 1600x1600 random matrix.

These benchmarks have been developed by many authors. See http://r.research.att.com/benchmarks/R-benchmark-25.R for a complete history. The function benchmark_matrix_fun() runs the five bm functions.

bm_matrix_fun_fft(runs = 3, verbose = TRUE)

bm_matrix_fun_eigen(runs = 3, verbose = TRUE)

bm_matrix_fun_determinant(runs = 3, verbose = TRUE)

bm_matrix_fun_cholesky(runs = 3, verbose = TRUE)

bm_matrix_fun_inverse(runs = 3, verbose = TRUE)

benchmark_matrix_fun(runs = 3, verbose = TRUE, cores = 0L)

Arguments

runs

Number of times to run the test. Default 3.

verbose

Default TRUE.

cores

Default 0 (serial). When cores > 0, the benchmark is run in parallel.

References

http://r.research.att.com/benchmarks/R-benchmark-25.R