Few pointers. Try using GPUArray to store your sequences - it will allow for you to use some more advanced features of PyCUDA.
Dnia 2011-09-28, śro o godzinie 18:04 +0200, nicola.zaur...@virgilio.it
pisze:
> Hi everyone,
> I'll explain my problem. I created the following code in python. This
> code implements the Nussinov's algoritm.
>
>
> from numpy import *
> from matplotlib import *
>
>
> seq='AACUUCUUCAA'
>
>
> def score_bpair(seq,i,j,soglia=2):
> score={('A','U'):1,('U','A'):1,('C','G'):1,('G','C'):1}
> a=seq[i]
> b=seq[j]
> if(abs(i-j)<soglia or((a,b) not in score.keys())):
> return 0
> else:
> return score[(a,b)]
Put above funtion into separate kernel.
>
>
> def nussinov(seq):
>
> L=len(seq);
> smat=zeros((L,L)); #array (L,L)
> for s in xrange(1,L):
> for i in xrange(0,L-s):
> j=i+s
> maxfork=0
> for k in xrange(i,j-1):
> maxfork=max(maxfork,smat[i][k]+smat[k+1][j])
use pycuda.gpuarray.max
> smat[i][j]=max((smat[i
> +1][j-1]+score_bpair(seq,i,j)),maxfork)
First create new array (containing values+score_bpair) and then
again GPUArray.max, or GPUArray.max_subset.
> smat[j][i]=smat[i][j] #completa la matrice in modo
> simmetrico
Check if you can create new GPUArray to get transposed view
into existing one.
Hope it helps,
regards.
--
Tomasz Rybak <bogom...@post.pl> GPG/PGP key ID: 2AD5 9860
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