Abstract
Alin Jula, Lawrence Rauchwerger, "Balancing Allocation Speed, Locality and Fragmentation in a Locality Improving Allocator," Technical Report, TR08-002, Department of Computer Science and Engineering, Texas A&M University, Feb 2008.
Technical Report(pdf, abstract)
The performance of memory allocators is a significant contributor to
the overall performance of dynamic applications. A good memory
allocator is fast, maximizes locality of access and minimizes
fragmentation.
In this paper we first introduce two novel memory allocators, TP and Medius,
which can be tuned to optimize the three characteristics of memory
allocation. These allocators can take locality enhancing hints
provided automatically by the C++ STL containers used in our
benchmark applications. Our TP allocator reduces the
execution time of seven significant programs, by an average of 7% and
17%
respectively, when compared to state-of-the-art allocators,
Doug Lea's malloc and FreeBSD's PHKmalloc.
We then compare the capability of various memory allocators to
optimize allocation speed, locality and fragmentation. We experimentally show
that these optimization goals are highly correlated and antagonistic.
This means that the
performance of allocators can only be the result of a trade-off between
the optimization of these three performance goals.
Thus we can improve overall performance by biasing
our optimization towards the characteristic that matters the most
(allocation speed, locality, fragmentation) for the application and computer
system at hand. Our new allocators (TP and Medius) allow such
selective optimization.