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How to get rid of a memory-leak when solving equations modulo an integer with sage?

asked 2024-04-09 20:07:32 +0200

Bern gravatar image

updated 2024-04-10 14:14:51 +0200

FrédéricC gravatar image

Hi,

I am running into a memory-leak if I execute the following sage code. I tried to get rid of the problem by using the garbage collector, but - after some time - my computer crashes anyway. I'd be thankful for any help.

p=3
r=2
n=7

import gc
gc.enable()

R=Integers(p^r)
elts=list(R)
elts

StrTotal=''
for i in [1..n-1]:
    StrTotal=StrTotal+'a_'+str(i)+','

StrTotal=StrTotal+'a_'+str(n)
StrTotal=var(StrTotal)
m=matrix([[1,0],[0,1]])
for i in [1..n]:
    m=matrix([[eval('a_'+str(i)),-1],[1,0]])*m

m_new = m + matrix([[1,0],[0,1]])
m_new

temp=[]
for t in [0..p^r-1]:
    for u in [0..p^r-1]:
        lll=solve_mod([a_1==t, a_2==u, m_new[0][0]==0, m_new[0][1]==0, m_new[1][0]==0, m_new[1][1]==0],p^r)
        LL=len(lll)
        temp.append(LL)
        print('LL ist gerade gleich: ')
        print(LL)
        print('t ist gerade gleich: ')
        print(t)
        lll=0
        #print("memory usage: " + str(get_memory_usage()))
        gc.collect()

temp

TEMP=sum(temp)
TEMP
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answered 2024-04-09 21:57:18 +0200

Max Alekseyev gravatar image

updated 2024-04-09 22:00:16 +0200

I'd suggest to report this issue to https://github.com/sagemath/sage/issues

A surprising workaround for memory leak issues is using multiprocessing, which thanks to spawning processes can force memory release in a hard way. As a positive side effect, it can also give code a noticeable speed-up.

Here is a rewrite of your loops using multiprocessing:

import multiprocessing

def my_solve_mod(tu):
    t,u = tu
    return t, solve_mod([a_1==t, a_2==u, m_new[0][0]==0, m_new[0][1]==0, m_new[1][0]==0, m_new[1][1]==0], p^r)

temp=[]
with multiprocessing.Pool() as pool:
    for t,lll in pool.imap( my_solve_mod, Tuples((0..p^r-1),2) ):
        LL=len(lll)
        temp.append(LL)
        print('LL ist gerade gleich: ')
        print(LL)
        print('t ist gerade gleich: ')
        print(t)

You may like to check documentation on multiprocessing for fine-tuning of this computation (e.g. forming bigger chunks of data for parallel processing).

PS. On a side note, you don't need to form lists like [A..B] in your loops, using generators (A..B) instead is faster and memory-savvy.

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Asked: 2024-04-09 20:07:32 +0200

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Last updated: Apr 10