library("benchmarkme")## On CRAN

library("benchmarkme")## On CRAN
## Tests based on a script by
## Simon Urbanek & Douglas Bates
res = benchmark_std(runs = 3)

library("benchmarkme")
res = benchmark_std(runs = 3)
# # Programming benchmarks (5 tests):
#     3,500,000 Fibonacci numbers calculation (vector calc): 0.52 (sec).
#     Grand common divisors of 1,000,000 pairs (recursion): 0.965 (sec).
#     Creation of a 3500x3500 Hilbert matrix (matrix calc): 0.306 (sec).
#     Creation of a 3000x3000 Toeplitz matrix (loops): 11.5 (sec).
#     Escoufier's method on a 60x60 matrix (mixed): 1.17 (sec).
# # Matrix calculation benchmarks (5 tests):
#    Creation, transp., deformation of a 5000x5000 matrix: 0.794 (sec).
#    2500x2500 normal distributed random matrix ^1000: 0.522 (sec).
#    Sorting of 7,000,000 random values: 0.598 (sec).
#    2500x2500 cross-product matrix (b = a' * a): 6.56 (sec).
#    Linear regr. over a 3000x3000 matrix (c = a \ b'): 4.5 (sec).
# # Matrix function benchmarks (5 tests):

# Upload results +
# RAM, CPU, 
# OS, byte-compile, BLAS
upload_results(res)

plot(res)

• upload_results takes a five column matrix
  • Columns 1 to 3: system.time output
  • Columns 4 & 5 are benchmark labels
• Easy to add to your own package
  • Results will be automatically incorparated in future benchmarkme releases

• Upgrade hardware
• Byte-compiling and BLAS are easy optimisations
  • No-one byte compiles!
• Network drives are slow

• github page

• CRAN

  install.packages("benchmarkme")
  browseVignettes("benchmarkme")

• Original benchmark scripts

• Efficient R programming
  • Chapter 2: BLAS
  • chapter 7: byte compiling
  • Chapter 8: General hardware advice # About
• Colin Gillespie Associate professor at Newcastle University
  • twitter: csgillespie
  • linkedin
• Running R courses for the last six years