I am working with a package provided by a university-affiliated organization. I keep hitting an arithmetic exception on a particular line of code, and there seems to be no reason. I am wondering what actions I can take. I am already running with -debug and no optimization. Below is the code snippet, with the "offending" line indicated in bold:
dzp = zp(i,j,k+1)-zp(i,j,k)
IF( runmod == 1 ) THEN
grdscl(i,j,k) = dxdy3rd * dzp**one3rd
ELSE IF( runmod == 2 ) THEN
grdscl(i,j,k) = SQRT(dx*dzp)
ELSE IF( runmod == 3 ) THEN
grdscl(i,j,k) = SQRT(dy*dzp)
ELSE IF( runmod == 4 ) THEN
grdscl(i,j,k) = dzp
All variables on this line are REAL (including the 3-dimensional array). The values are:
one3rd = 1.0/3.0 (so 0.3333333...)
dzp = -16.666626
dxdy3rd = 9.65489483
so basically the expression is taking a negative real number, raising it to a real fraction (should be fine), and the multiplying it by a positive real number.
Regarding the loop through the arrays, the indexes and the variable runmod are all correctly INTEGER. nx is 100, ny is 400, and nz is 10.
I am running on Ubuntu 16.04.
Here is the compilation command; my only contribution was replacing -O3 wth -O0 -debug:
ifort -w -convert big_endian -fp-model source -I/home/braun/arps/include -I/usr/local/hdf/include -module /home/braun/arps/modules -O0 -debug -fpe0 -check bounds -traceback -c tmix3d.f90
I'm starting to suspect a compiler option. I tried a small test case with no options, and the result was correct.
Funny, I was so intent on creating a small test case, I did not consider the basic math. My "should be fine" comment came from first getting a result on my computer's calculator and then this little program:
real :: dzp, one3rd, result
one3rd = 1.0 / 3.0
dzp = -16.666626
result = dzp**one3rd
print *, result
end program j
So I compile and run it:
braun@audrey-00:~$ ifort -c j.f90
braun@audrey-00:~$ ifort -o j j.o
In any case, my task is to find out why dzp is negative. Maybe the real "bug" is the apparently reasonable result in the small test case.
Thanks as always, Steve.
I added an additional step to the test case, multiplying that result by a real number, and got NaN.
OK, on to the next step: where did that negative number come from?
Just to close this discussion -- the negative values resulted from a mismatch of parametric data. By changing one setting that was inconsistent with the dimensions chosen for my particular data set, I eliminated the issue. This was consistent with some documentation that I later found.