On the scalability of an automatically parallelized irregular application

M Burtscher, M Kulkarni, D Prountzos… - Languages and Compilers …, 2008 - Springer
Languages and Compilers for Parallel Computing: 21th International Workshop …, 2008Springer
Irregular applications, ie, programs that manipulate pointer-based data structures such as
graphs and trees, constitute a challenging target for parallelization because the amount of
parallelism is input dependent and changes dynamically. Traditional dependence analysis
techniques are too conservative to expose this parallelism. Even manual parallelization is
difficult, time consuming, and error prone. The Galois system parallelizes such applications
using an optimistic approach that exploits higher-level semantics of abstract data types. In …
Abstract
Irregular applications, i.e., programs that manipulate pointer-based data structures such as graphs and trees, constitute a challenging target for parallelization because the amount of parallelism is input dependent and changes dynamically. Traditional dependence analysis techniques are too conservative to expose this parallelism. Even manual parallelization is difficult, time consuming, and error prone. The Galois system parallelizes such applications using an optimistic approach that exploits higher-level semantics of abstract data types.
In this paper, we study the performance and scalability of a Galoised, that is, automatically parallelized, version of Delaunay mesh refinement (DR) on a shared-memory system with 128 CPUs. DR is an important irregular application that is used, e.g., in graphics and finite-element codes. The parallelized program scales to 64 threads, where it reaches a speedup of 25.8. For large numbers of threads, the performance is hampered by the load imbalance and the nonuniform memory latency, both of which grow as the number of threads increases. While these two issues will have to be addressed in future work, we believe our results already show the Galois approach to be very promising.
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