Language Constructs for Distributed Real-Time Programming

For many distributed applications, it is not sufficient for programs to be logically correct. In addition, they must satisfy various timing constraints. This paper discusses primitives that support the construction of distributed real-time programs. Our discussion is focused in two areas: timing specification and communication. To allow the specifications of timing constraints, we introduce the language constructs for defining temporal scope and specifying message deadline. We also identify communication primitives needed for real-time programming. The issues underlying the selection of the primitives are explained, including handling of timing exceptions. The primitives will eventually be provided as part of a distributed programming system that will be used to construct distributed multi-sensory systems

Coordination language for distributed clean

The distributed evaluation of functional programs and the communication between computational nodes require high-level process description and coordination mechanism. This paper presents the D-Clean high-level functional language, which supports the distributed computation of Clean functions over a cluster. The lazy functional programming language Clean is extended by new language elements in order to achieve parallel features. The distributed computations of functions are expressed in the form of process-networks. D-Clean introduces language primitives to control the dataflow in a distributed process-network. A process scheme defines a partial computation graph, where the nodes are functions to be evaluated and the edges are communication channels. The computational nodes are implemented as statically typed Clean programs. The schemes are parameterized by functions, types and data for defining process networks. D-Clean is compiled to an intermediate level language called D-Box. The D-Clean generic constructs are instantiated into D-Box expressions. D-Box is designed for the description of the computational nodes. D-Box expressions hide implementation details and enable direct control over the process-network. The asynchronous communication is based on language-independent middleware services. The present paper provides the syntax and the informal semantics of both coordination languages. To illustrate the definition of a distributed functional computational pattern using the D-Clean language a farm skeleton running example is presented

\u3cem\u3eRTC\u3c/em\u3e: Language Support for Real-Time Concurrency

This paper presents language constructs for the expression of timing and concurrency requirements in distributed real-time programs. Our programming paradigm combines an object-based paradigm for the specification of shared resources, and a distributed transaction-based paradigm for the specification of application processes. Resources provide abstract views of shared system entities, such as devices and data structures. Each resource has a state and defines a set of actions that can be invoked by processes to examine or change its state. A resource also specifies scheduling constraints on the execution of its actions to ensure the maintenance of its state\u27s consistency. Processes access resources by invoking actions and express precedence, consistency. Processes access resources by invoking actions and express precedence, consistency and timing constraints on action invocations. The implementation of our language constructs with real-time scheduling and locking for concurrency control is also described

Cologne: A Declarative Distributed Constraint Optimization Platform

This paper presents Cologne, a declarative optimization platform that enables constraint optimization problems (COPs) to be declaratively specified and incrementally executed in distributed systems. Cologne integrates a declarative networking engine with an off-theshelf constraint solver. We have developed the Colog language that combines distributed Datalog used in declarative networking with language constructs for specifying goals and constraints used in COPs. Cologne uses novel query processing strategies for processing Colog programs, by combining the use of bottom-up distributed Datalog evaluation with top-down goal-oriented constraint solving. Using case studies based on cloud and wireless network optimizations, we demonstrate that Cologne (1) can flexibly support a wide range of policy-based optimizations in distributed systems, (2) results in orders of magnitude less code compared to imperative implementations, and (3) is highly efficient with low overhead and fast convergence times

Reliable Synchronization Primitives for Java

Java is an architecture-independent, object-oriented language designed to facilitate code-sharing across the Internet in general, via the Web in particular. Java is multithreaded, providing thread creation and synchronization constructs based on generalized monitors. Although these primitives are appropriate for many windowing applications, they are not necessarily well-suited for the larger class of multithreaded programs that occur as part of distributed systems. We demonstrate how the Java primitives, in conjunction with the object-oriented aspects of the language, can be used to implement a collection of other traditional synchronization paradigms. These paradigms are formally specified, their implementations are rigorously verified, and their use is illustrated with several examples

Flexible language constructs for large parallel programs

The goal of the research described is to develop flexible language constructs for writing large data parallel numerical programs for distributed memory (MIMD) multiprocessors. Previously, several models have been developed to support synchronization and communication. Models for global synchronization include SIMD (Single Instruction Multiple Data), SPMD (Single Program Multiple Data), and sequential programs annotated with data distribution statements. The two primary models for communication include implicit communication based on shared memory and explicit communication based on messages. None of these models by themselves seem sufficient to permit the natural and efficient expression of the variety of algorithms that occur in large scientific computations. An overview of a new language that combines many of these programming models in a clean manner is given. This is done in a modular fashion such that different models can be combined to support large programs. Within a module, the selection of a model depends on the algorithm and its efficiency requirements. An overview of the language and discussion of some of the critical implementation details is given

Porting the Sisal functional language to distributed-memory multiprocessors

Parallel computing is becoming increasingly ubiquitous in recent years. The sizes of application problems continuously increase for solving real-world problems. Distributed-memory multiprocessors have been regarded as a viable architecture of scalable and economical design for building large scale parallel machines. While these parallel machines can provide computational capabilities, programming such large-scale machines is often very difficult due to many practical issues including parallelization, data distribution, workload distribution, and remote memory latency. This thesis proposes to solve the programmability and performance issues of distributed-memory machines using the Sisal functional language. The programs written in Sisal will be automatically parallelized, scheduled and run on distributed-memory multiprocessors with no programmer intervention. Specifically, the proposed approach consists of the following steps. Given a program written in Sisal, the front end Sisal compiler generates a directed acyclic graph(DAG) to expose parallelism in the program. The DAG is partitioned and scheduled based on loop parallelism. The scheduled DAG is then translated to C programs with machine specific parallel constructs. The parallel C programs are finally compiled by the target machine specific compilers to generate executables. A distributed-memory parallel machine, the 80-processor ETL EM-X, has been chosen to perform experiments. The entire procedure has been implemented on the EMX multiprocessor. Four problems are selected for experiments: bitonic sorting, search, dot-product and Fast Fourier Transform. Preliminary execution results indicate that automatic parallelization of the Sisal programs based on loop parallelism is effective. The speedup for these four problems is ranging from 17 to 60 on a 64-processor EM-X. Preliminary experimental results further indicate that programming distributed-memory multiprocessors using a functional language indeed frees the programmers from lowl-evel programming details while allowing them to focus on algorithmic performance improvement