On 12/3/06, [EMAIL PROTECTED] <[EMAIL PROTECTED]> wrote:
Hello,
I'm taking a CFD class, one of the codes I wrote runs very slow. When I
look at hotshot is says the function below is the problem. Since this is an
explicit step, the for loops are only traversed once, so I think it's caused
by memory usage, but I'm not sure if it's the local variables or the loop? I
can vectorize the inner loop, would declaring the data structures in the
calling routine and passing them in be a better idea than using local
storage?
I'm new at python and numpy, I need to look at how to get profiling
information for the lines within a function.
Thank you,
Frank
PS
I tried to post this via google groups, but it didn't seem to go through,
sorry if it ends up as multiple postings
def findw(wnext,wprior,phiprior,uprior,vprior):
#format here is x[i,j] where i's are rows, j's columns, use flipud() to
get the
#print out consistent with the spacial up-down directions
#assign local names that are more
#inline with the class notation
w = wprior
phi = phiprior
u = uprior
v = vprior
#three of the BC are known so just set them
#symetry plane
wnext[0,0:gcols] = 0.0
#upper wall
wnext[gN,0:gcols] = 2.0/gdy**2 * (phi[gN,0:gcols] - phi[gN-1,0:gcols])
#inlet, off the walls
wnext[1:grows-1,0] = 0.0
upos = where(u>0)
vpos = where(v>0)
Sx = ones_like(u)
Sx[upos] = 0.0
Sy = ones_like(v)
Sy[vpos] = 0.0
uw = u*w
vw = v*w
#interior nodes
for j in range(1,gasizej-1):
for i in range(1,gasizei-1):
wnext[i,j] =( w[i,j] + gnu*gdt/gdx**2 * (w[i,j-1] - 2.0*w[i,j]
+ w[i,j+1]) +
gnu*gdt/gdy**2 * (w[i-1,j] - 2.0*w[i,j] +
w[i+1,j]) -
(1.0 - Sx[i,j]) * gdt/gdx * (uw[i,j] - uw[i,j-1])
-
Sx[i,j] * gdt/gdx * (uw[i,j+1] - uw[i,j]) -
(1.0 - Sy[i,j]) * gdt/gdy * (vw[i,j] - vw[i-1,j])
-
Sy[i,j] * gdt/gdy * (vw[i+1,j] - vw[i,j]) )
## print "***wnext****"
## print "i: ", i, "j: ", j, "wnext[i,j]: ", wnext[i,j]
#final BC at outlet, off walls
wnext[1:grows-1,gM] = wnext[1:grows-1,gM-1]
_
Explicit indexing tends to be very slow. I note what looks to be a lot of
differencing in the code, so I suspect what you have here is a PDE. Your
best bet in the short term is to vectorize as many of these operations as
possible, but because the expression is so complicated it is a bit of a
chore to see just how. It your CFD class allows it, there are probably
tools in scipy that are adapted to this sort of problem, and in particular
to CFD. Sandia also puts out PyTrilinos,
http://software.sandia.gov/trilinos/packages/pytrilinos/, which provides
interfaces to distributed and parallel PDE solvers. It's big iron software
for serious problems, so might be a bit of overkill for your applications.
Chuck
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