Evaluating Parallel Logic Programming

Parallel logic programming systems are sophisticated examples of symbolic computing systems. They address problems such as dynamic memory allocation, scheduling irregular execution patterns, and managing diierent types of implicit parallelism. Most parallel logic programming systems have been developed for bus-based shared-memory architectures. The complexity of parallel logic programming systems and the large amount of data they process raises the question of whether logic programming systems can still obtain good performance on scalable architectures, such as distributed shared-memory systems. In this work we use execution-driven simulation to investigate the access patterns and caching behaviour exhibited by a parallel logic programming system, Andorra-I. We show that the system obtains reasonable performance, but that it does not scale well. By studying the behaviour of the major data structures in Andorra-I in detail, we conclude that this result is largely a consequence of the scheduling and work manipulation implementation used in the system. We also show that the Andorra-I's data structures exhibit widely-varying memory access patterns and caching behaviour, which not only depend on the number of processors , but also on the amount and type of parallelism available in the application program. Some of these data structures clearly favour invalidate-based cache coherence protocols , while others favour update-based protocols. Since most of Andorra-I's data structures are common to other parallel logic programming systems, we believe that these systems can greatly beneet from exible coherence schemes where either the compiler can specify the protocol to be used for each data structure or the protocol can adapt to varying memory access patterns.