Structure and Properties of Traces for Functional Programs

The tracer Hat records in a detailed trace the computation of a program written in the lazy functional language Haskell. The trace can then be viewed in various ways to support program comprehension and debugging. The trace was named the augmented redex trail. Its structure was inspired by standard graph rewriting implementations of functional languages. Here we describe a model of the trace that captures its essential properties and allows formal reasoning. The trace is a graph constructed by graph rewriting but goes beyond simple term graphs. Although the trace is a graph whose structure is independent of any rewriting strategy, we define the trace inductively, thus giving us a powerful method for proving its properties

AMaχoS—Abstract Machine for Xcerpt

Web query languages promise convenient and efficient access to Web data such as XML, RDF, or Topic Maps. Xcerpt is one such Web query language with strong emphasis on novel high-level constructs for effective and convenient query authoring, particularly tailored to versatile access to data in different Web formats such as XML or RDF. However, so far it lacks an efficient implementation to supplement the convenient language features. AMaχoS is an abstract machine implementation for Xcerpt that aims at efficiency and ease of deployment. It strictly separates compilation and execution of queries: Queries are compiled once to abstract machine code that consists in (1) a code segment with instructions for evaluating each rule and (2) a hint segment that provides the abstract machine with optimization hints derived by the query compilation. This article summarizes the motivation and principles behind AMaχoS and discusses how its current architecture realizes these principles

Using a functional language and graph reduction to program multiprocessor machines or functional control of imperative programs

Journal ArticleThis paper describes an effective means for programming shared memory multiprocessors whereby a set of sequential activities are linked together for execution in parallel. The glue for this linkage is provided by a functional language implemented via graph reduction and demand evaluation. The full power of functional programming is used to obtain succinct, high level specifications of parallel computations. The imperative procedures that constitute the sequential activities facilitate efficient utilization of individual processing elements, while the mechanisms inherent in graph reduction synchronize and schedule these activities. The main contributions of this paper are: 1) an evaluation of the performance implications of parallel graph reduction; 2) a demonstration that the mechanisms of graph reduction can obtain multiprocessor performance uniformly surpassing the best uni-processor implementation of sequential algorithms running on a single node of the same machine, and 3) an illustration of our method used to program a real world fluid flow simulation problem

An abstract machine for parallel graph reduction

technical reportAn abstract machine suitable for parallel graph reduction on a shared memory multiprocessor is described. Parallel programming is plagued with subtle race conditions resulting in deadlock or fatal system errors. Due to the nondeterministic nature of program execution the utilization of resources may vary from one run to another. The abstract machine has been designed for the efficient execution of normal order functional languages. The instructions proposed related to parallel activity are sensitive to load conditions and the current utilization of resources on the machine. The novel aspect of the architecture is the very simple set of instructions needed to control the complexities of parallel execution. This is an important step towards building a compiler for multiprocessor machines and to further language research in this area. Sample test programs hand coded in this instruction set show good performance on our 18 node BBN Butterfly as compared to a VAX 8600

An abstract machine for the execution of graph grammars

An abstract machine for graph rewriting is the central part of the middle layer of the implementation of a grammar based graph rewriting system. It specifies the interface between a compiler for graph grammars and a system performing actual graph transformations. By the introduction of a middle layer, the analysis of the given graph grammar can be used to optimize its execution. The costs of expensive analysis are thus shifted from run to compile time. Each implementation of the abstract machine can optimize the utilization of available hardware. We give the specification of the state and the instruction set of the abstract machine. For an example grammar we show how compile time analysis can reduce execution time, and we present code generation rules to implement a grammar on the abstract machine. In comparison to abstract machines, well-known from the implementation of functional languages, our machine can execute rewriting specified by graph grammars which is far more general than graph reduction. The abstract machine for graph rewriting is part of a project which addresses the efficient implementation of the execution of graph grammars

A common graphical form

We present the Common Graphical Form, a low level, abstract machine independent structure which provides a basis for implementing graph reduction on distributed processors. A key feature of the structure is its ability to model disparate abstract machines in a uniform manner; this enables us to experiment with different abstract machines without having to recode major parts of the run-time system for each additional machine. Because we are dealing with a uniform data structure it is possible to build a suite of performance measurement tools to examine interprocessor data-flow and to apply these tools to different abstract machines in order to make relative comparisons between them at run-time. As a bonus to our design brief we exploit the unifying characteristics of the Common Graphical Form by using it as an intermediate language at compile-time

Correctness Issues on MARTE/CCSL constraints

International audienceThe UML Profile for Modeling and Analysis of Real-Time and Embedded systems promises a general modeling framework to design and analyze systems. Lots of works have been published on the modeling capabilities offered by MARTE, much less on available verification techniques. The Clock Constraint Specification Language (CCSL), first introduced as a companion language for MARTE, was devised to offer a formal support to conduct causal and temporal analysis on MARTE models.This work relies on a state-based semantics for CCSL to establish correctness properties on MARTE/CCSL specifications. We propose and compare two different techniques to build the state-space of a specification. One is an extension of some previous work and is based on extended finite state machines. It relies on integer linear programming to solve the constraints and reduce the state-space. The other one is based on an intentional representation and uses pure Boolean abstractions but offers no guarantee to terminate when the specification is not safe.The approach is illustrated on one simple example where the architecture plays an important role. We describe a process where the logical description of the application is progressively refined to take into account the execution platform through allocation