On 10/05/16 23:32, Andrew wrote:
On Wednesday, 11 May 2016 14:00:20 UTC+10, William wrote:
It depends on what you are trying to do. For some computations,
@parallel is the best possible way to do them, and for others it is
the worst possible way.
Is there a good to learn about how best to do this (in sage/python/...)?
The first example that I care about looks something like this:
mat=[[0 for s in xrange(tabs)] for t in xrange(tabs)]
for s in xrange(tabs):
for t in xrange(s,tabs):
mat[s][t]=self._inner_product_st(s,t)
mat[t][s]=mat[s][t]
The `_inner_product_st` method computes certain structure constants in a
module. This method is time consuming and slightly recursive with "basic"
cases being cached. Parallelising this loop seemed like the right place to
me but, to be honest, I have no idea what I am doing!
At this point it is not clear to me whether you need shared memory or
not between the processes. This can be an important overhead of
parallelization.
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