If I compute a Gröbner basis using libSingular, it is much slower than 
using the Singular interface. Could this be related to the memory leaks or 
is it a different issue?

sage: I = sage.rings.ideal.Katsura(PolynomialRing(QQ, 'x', 9))
sage: %time gb1 = I.groebner_basis(algorithm='singular')
CPU times: user 1.34 s, sys: 47.5 ms, total: 1.38 s
Wall time: 13 s
sage: I = sage.rings.ideal.Katsura(PolynomialRing(QQ, 'x', 9))
sage: %time gb2 = I.groebner_basis(algorithm='libsingular')
CPU times: user 49.2 s, sys: 122 ms, total: 49.4 s
Wall time: 49.4 s
sage: gb1 == gb2
True

This defaults to the Singular function `groebner`, but choosing others like 
`std` or `slimgb` gives similar timings.

Over finite fields, the above issue does not seem to occur – the 
libSingular computation is slightly faster than Singular, as expected. 
However, there seems to be a different issue with the Singular interface: 
repeating the same computation causes a significant slowdown. This does not 
happen using libSingular.

sage: I = sage.rings.ideal.Katsura(PolynomialRing(GF(2^31-1), 'x', 10))
sage: %time gb1 = I.groebner_basis(algorithm='singular')
CPU times: user 1.86 s, sys: 110 ms, total: 1.97 s
Wall time: 18.4 s
sage: I = sage.rings.ideal.Katsura(PolynomialRing(GF(2^31-1), 'x', 10))
sage: %time gb2 = I.groebner_basis(algorithm='singular')
CPU times: user 1.89 s, sys: 117 ms, total: 2 s
Wall time: 1min 13s
sage: gb1 == gb2
True

This was tested using Sage 8.7 on a MBP 8,1 with OS X 10.13.6. I observed 
similar results on other machines as well.

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