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Fortran-String-to-Real

When we discovered that Fortran is very slow at converting strings to reals using its read statement, I had an idea: Fortran isn't that fast with strings but with numbers and especially with number arrays. So I tried to convert a string problem into an int problem.

How it works

  1. Convert the string (which actually is an character array) into an integer array using equivalence (transfer was much slower`).
  2. Determine the positions of the period and exponent chars
  3. Multiply the coefficient part of the integer array with "base-ten"
  4. Calculate the sum of the integer array
  5. Do the same for the exponent and combine factor with exponent

Example "12.34E10"

  1. character -> integer (1 byte) -> -48 (ichar('0'))

    ['1','2','.','3','4','E','1','0']

    [ 1 , 2 ,-2 , 3 , 4 ,21 , 1 , 0 ]

  2. findloc for the period (faster than scan for one char)

    scan for E or e (faster than 2 times findloc)

  3. [1, 2, -2, 3, 4] *

    [10., 1., 0., 0.1, 0.01]

  4. coefficient = sum(10., 2., 0., 0.3, 0.04)

  5. exponent = sum([1, 0] * [10., 1.]) result = coefficient * 10 ** exponent

Input

This routine is still experimental! It cannot handle NaN or Inf values and there is no error checking. The input string has to end with the last digit of the number. If the number is negative, the first character has to be the - sign. Positive numbers don't have to start with digits: Technically all characters except of ., e, E or digits can be in front of the number, because they will be hidden by a mask.

Performance

This library comes with a test for correctness and a benchmark for execution time. The benchmark only contains one format, the speedup will be different for shorter/other formats. All tests are a comparison between formatted read and str2real

test correctness:

fpm test test

benchmark execution time:

fpm test bench --profile release --flag "-flto"

Footnote

There is an ongoing discussion on this topic in the Fortran-Discourse Parts of the code in this repository are written/edited by Jacob Williams and Beliavsky