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2 implementation of min function and 1 inbuilt min function

benchmark using hyperfine

might use perf for cpp, timeit for py for benchmarking

first generate input data from ip.jl or ip.py and then feed into minbench.cpp or minbench.cpp


todo

Function Mean [ms] Min [ms] Max [ms] Relative
inbuilt min inp1 378.3 ± 4.4 372.6 399.2 2.86 ± 0.10
inbuilt min inp2 132.1 ± 4.3 128.5 153.5 1.00
numpy min inp1 625.5 ± 85.8 458.7 828.1 3.78 ± 0.52
numpy min inp2 165.4 ± 3.3 159.4 173.8 1.00
akd min inp1 409.3 ± 6.6 396.5 437.6 3.07 ± 0.06
akd min inp2 133.2 ± 1.2 130.9 135.3 1.00
boobi min inp1 420.9 ± 5.3 411.5 443.9 3.09 ± 0.09
boobi min inp2 136.2 ± 3.3 133.1 147.9 1.00

conclusion:

  • In DonaldKnuth's paper "StructuredProgrammingWithGoToStatements", he wrote: "Programmers waste enormous amounts of time thinking about, or worrying about, the speed of noncritical parts of their programs, and these attempts at efficiency actually have a strong negative impact when debugging and maintenance are considered. We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil. Yet we should not pass up our opportunities in that critical 3%."
  • https://en.wikipedia.org/wiki/Program_optimization

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