Abstract

Abstract

Abstract
Linear Meld is a concurrent forward-chaining linear logic programming language where logical facts can be asserted and retracted in a structured way. The database of facts is partitioned by the nodes of a graph structure which leads to parallelism if nodes are executed simultaneously. Communication arises whenever nodes send facts to other nodes by fact derivation. We present an overview of the virtual machine that we implemented to run Linear Meld on multicores, including code organization, thread management, rule execution and database organization for efficient fact insertion, lookup and deletion. Although our virtual machine is a work-in-progress, our results already show that Linear Meld is not only capable of scaling graph and machine learning programs but it also exhibits some interesting performance results when compared against other programming languages.

Abstract
This special issue of Theory and Practice of Logic Programming (TPLP) contains the regular papers accepted for presentation at the 33rd International Conference on Logic Programming (ICLP 2017), held in Melbourne, Australia from the 28th of August to the 1st of September, 2017. ICLP 2017 was colocated with the 23rd International Conference on Principles and Practice of Constraint Programming (CP 2017) and the 20th International Conference on Theory and Applications of Satisfiability Testing (SAT 2017). Since the first conference held in Marseille in 1982, ICLP has been the premier international event for presenting research in logic programming.

Abstract
Linear logic programs are challenging to implement efficiently because facts are asserted and retracted frequently. Implementation is made more difficult with the introduction of useful features such as rule priorities, which are used to specify the order of rule inference, and comprehensions or aggregates, which are mechanisms that make data iteration and gathering more intuitive. In this paper, we describe a compilation scheme for transforming linear logic programs enhanced with those features into efficient C++ code. Our experimental results show that compiled logic programs are less than one order of magnitude slower than hand-written C programs and much faster than interpreted languages such as Python.

Abstract
Linear Meld is a concurrent forward-chaining linear logic programming language where logical facts can be asserted and retracted in a structured way. In Linear Meld, a program is seen as a database of logical facts and a set of derivation rules. The database of facts is partitioned by the nodes of a graph structure which leads to parallelism when nodes are executed simultaneously. Due to the foundations on linear logic, rules can retract facts in a declarative and structured fashion, leading to more expressive programs. We present the design and implementation of the virtual machine that we implemented to run Linear Meld on multicores, with particular focus on thread management, code organization, fact indexing, rule execution, and database organization for efficient fact insertion, lookup and deletion. Our results show that the virtual machine is capable of scaling programs with up to 16 threads and also exhibits interesting scalar performance results due to our indexing optimizations.