Region-based memory management (RBMM) is a form of compile time memory management, well-known from the functional programming world. In this paper we describe our work on implementing RBMM for the logic programming language Mercury. One interesting point about Mercury is that it is designed with strong type, mode, and determinism systems. These systems not only provide Mercury programmers with several direct software engineering benefits, such as self-documenting code and clear program logic, but also give language implementors a large amount of information that is useful for program analyses. In this work, we make use of this information to develop program analyses that determine the distribution of data into regions and transform Mercury programs by inserting into them the necessary region operations. We prove the correctness of our program analyses and transformation. To execute the annotated programs, we have implemented runtime support that tackles the two main challenges posed by backtracking. First, backtracking can require regions removed during forward execution to be "resurrected"; and second, any memory allocated during a computation that has been backtracked over must be recovered promptly and without waiting for the regions involved to come to the end of their life. We describe in detail our solution of both these problems. We study in detail how our RBMM system performs on a selection of benchmark programs, including some well-known difficult cases for RBMM. Even with these difficult cases, our RBMM-enabled Mercury system obtains clearly faster runtimes for 15 out of 18 benchmarks compared to the base Mercury system with its Boehm runtime garbage collector, with an average runtime speedup of 24 , and an average reduction in memory requirements of 95 . In fact, our system achieves optimal memory consumption in some programs.
We extend Tofte and Talpin's region-based model for memory management to support backtracking and cuts, which makes it suitable for use with Prolog and other logic programming languages. We describe how the extended model can be implemented and report on the performance of a prototype implementation. The prototype implementation performs well when compared to a garbage-collecting Prolog implementation using comparable technology for non-memory-management issues. Region-based memory management is an attractive alternative to garbage collection. It relies on a compile-time analysis to annotate the program with explicit allocation and deallocation instructions, where lifetimes of memory objects are grouped together in regions. This paper investigates how to adapt the runtime part of region-based memory management to the WAM setting.We present additions to the memory architecture and instruction set of the WAM that are necessary to implement regions. We extend an optimized WAM-based Prolog implementation with a region-based memory manager which supports backtracking with instant reclamation, and cuts. The performance of region-based execution is compared with that of the baseline garbage-collected implementation on several benchmark programs. A region-enabled WAM performs competitively and often results in time and or space improvements. 