bm_matrix_fun_fft: Matrix function benchmarks

In benchmarkme: Crowd Sourced System Benchmarks

Matrix function benchmarks

Description

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.

Usage

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

benchmarkme documentation built on June 12, 2022, 5:06 p.m.