Performance and evaluation of LISP systems
Performance and evaluation of LISP systems
Can logic programming execute as fast as imperative programming?
Can logic programming execute as fast as imperative programming?
Fast Prolog with an extended general purpose architecture
ISCA '90 Proceedings of the 17th annual international symposium on Computer Architecture
Understanding Memory Management in Prolog Systems
Proceedings of the 17th International Conference on Logic Programming
Optimising Bytecode Emulation for Prolog
PPDP '99 Proceedings of the International Conference PPDP'99 on Principles and Practice of Declarative Programming
Instruction merging and specialization in the SICStus Prolog virtual machine
Proceedings of the 3rd ACM SIGPLAN international conference on Principles and practice of declarative programming
An efficient easily adaptable system for interpreting natural language queries
Computational Linguistics
Improving memory usage in the BEAM
PADL'05 Proceedings of the 7th international conference on Practical Aspects of Declarative Languages
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Progress in Prolog applications requires ever better performance and scalability from Prolog implementation technology. Most modern Prolog systems are emulator-based. Best performance thus requires both good emulator design and good memory performance. Indeed, Prolog applications can often spend hundreds of megabytes of data, but there is little work on understanding and quantifying the interactions between Prolog programs and the memory architecture of modern computers.In a previous study of Prolog systems we have shown through simulation that Prolog applications usually, but not always, have good locality, both for deterministic and non-deterministic applications. We also showed that performance may strongly depend on garbage collection and on database operations. Our analysis left two questions unanswered: how well do our simulated results holds on actual hardware, and how much did our results depend on a specific configuration? In this work we use several simulation parameters and profiling counters to improve understanding of Prolog applications. We believe that our analysis is of interest to any system implementor who wants to understand his or her own system's memory performance.