Granularity Analysis for Exploiting Adaptive Parallelism of Declarative Programs on Multiprocessors

1IntroductionAutomaticparallelexecutionofdeclarativelanguageprograms(e.g.functionprogramsandlogicprograms)isattractive,asitmakestheuseofparallelcomputersveryeasy,andtheprogrammerneednotbeconcernedwiththespecificsoftheunderlyingparallelarchitecture.However,ifseveralprocessorsareexecutingconcurrently,exploitingadaptiveparallelismishardduetonon-determinismoftaskgranularityanddatadependenciesamongtasks.TheearlysolutionproposedbyConeryandKibler[2]usesanorderingalgorithmtodeterminedependenciesatrun…     

可信编译器L2C的核心翻译步骤及其设计与实现

同步数据流语言（如Lustre）近年来在航空、高铁、核电等安全攸关领域得到广泛应用.这些领域对相关开发工具本身的安全性有着相当高的要求.为尽力解决好”误编译”问题,近期人们借助reliable-by-construction辅助定理证明器实现常规命令式语言编译器的构造和验证取得了很大的成功,如CompCert C编译器.L2C是基于这种方法开发的可信编译器,它以扩展的Lustre语言为源语言,以Clight （CompCert中的C语言子集）为目标语言.就我们所知,L2C是同类工作中唯一面向实际工业应用的同步数据流语言编译器.本文重点介绍L2C编译器的核心翻译步骤及其设计与实现过程中考虑的主要问题和相关经验.     

并行面向对象语言综述

近年来,面向对象语言的并行化技术取得了许多重要进展.以Mentat,CC++,pC++,HPC++和ICC++等几个典型系统为代表,从并行执行模型、语言并行设施、优化技术和运行时支持等几个方面归纳、总结了近年来这些语言和编译器支持并行的新技术.同时,还给出了对这些技术的分析和评价,总结了需要进一步研究和解决的问题.     

并行程序设计模型和语言

并行计算技术的发展已有20多年的历史了.时至今日,高性能并行计算仍然缺乏有效的并行程序设计方法和工具,使得编写并行程序、理解并行程序的行为、调试和优化并行程序的性能都很困难.从分析并行程序设计困难的原因入手,指出了当前各种高性能并行机系统支持的并行程序设计方法存在的诸多问题,综述了并行程序设计模型和语言的研究现状,给出了并行程序设计模型的评价标准,并提出了这一研究领域所面临的挑战性问题,指出了一些未来可能的发展方向.     

程序设计语言的形式语义研究进展

程序设计语言形式语义描述方法的产生与发展,对程序设计语言的设计和标准化,编译程序的设计和优化,程序推理,以及协议形式化描述、分析验证与设计等都有着重要的意义。回顾形式语义描述方法的研究发展史,介绍当前主要的语义形式描述方法,并给出这些方法的评价标准和比较结果;指出最有发展潜力的语义描述方法以及将来的发展方向。     

Improving workflow modularity using a concern-specific layer on top of Unify

Workflows are a popular means of automating processes in many domains, ranging from high-level business process modeling to lower-level web service orchestration. However, state-of-the-art workflow languages offer a limited set of modularization mechanisms. This results in monolithic workflow specifications, in which different concerns are scattered across the workflow and tangled with one another. This hinders the design, evolution, and reusability of workflows expressed in these languages. We address this problem through the Unify framework. This framework enables uniform modularization of workflows by supporting the specification of all workflow concerns – including crosscutting ones – in isolation of each other. These independently specified workflow concerns are connected to each other using workflow-specific connectors. In order to further facilitate the development of workflows, we enable the definition of concern-specific languages (CSLs) on top of the Unify framework. A CSL facilitates the expression of a family of workflow concerns by offering abstractions that map well to the concerns' domain. Thus, domain experts can add concerns to a workflow using concern-specific language constructs. We exemplify the specification of a workflow in Unify, and show the definition and application of two concern-specific languages built on top of Unify.     

Remeshing‐assisted Optimization for Locally Injective Mappings

Constructing locally injective mappings for 2D triangular meshes is vital in applications such as deformations. In such a highly constrained optimization, the prescribed tessellation may impose strong restriction on the solution. As a consequence, the feasible region may be too small to contain an ideal solution, which leads to problems of slow convergence, poor solution, or even that no solution can be found. We propose to integrate adaptive remeshing into interior point method to solve this issue. We update the vertex positions via a parameter‐free relaxation enhanced geometry optimization, and then use edge‐flip operations to reduce the residual and keep a reasonable condition number for better convergence. For more robustness, when the iteration of interior point method terminates but leaves the positional constraints unsatisfied, we estimate the edges in the current tessellation that block vertices moving based on the convergence information of the optimization, and then split neighboring edges to break the restriction. The results show that our method has better performance than the solely geometric optimization approaches, especially for extreme deformations.     

Image Space Rendering of Point Clouds Using the HPR Operator

The hidden point removal (HPR) operator introduced by Katz et al. [KTB07] provides an elegant solution for the problem of estimating the visibility of points in point samplings of surfaces. Since the method requires computing the three‐dimensional convex hull of a set with the same cardinality as the original cloud, the method has been largely viewed as impractical for real‐time rendering of medium to large clouds. In this paper we examine how the HPR operator can be used more efficiently by combining several image space techniques, including an approximate convex hull algorithm, cloud sampling, and GPU programming. Experiments show that this combination permits faster renderings without overly compromising the accuracy.     

Synthesizing interpreted domain-specific models to manage smart microgrids

The increase in prominence of model-driven software development (MDSD) has placed emphasis on the use of domain-specific modeling languages (DSMLs) during the development process. DSMLs allow for domain concepts to be conceptualized and represented at a high level of abstraction. Currently, most DSML models are converted into high-level languages (HLLs) through a series of model-to-model and/or model-to-text transformations before they are executed. An alternative approach for model execution is the interpretation of models directly without converting them into an HLL. These models are created using interpreted DSMLs (i-DSMLs) and realized using a semantic-rich execution engine or domain-specific virtual machine (DSVM).In this article we present an approach for model synthesis, the first stage of model interpretation, that separates the domain-specific knowledge (DSK) from the model of execution (MoE). Previous work on model synthesis tightly couples the DSK and MoE reducing the ability for implementations of the DSVM to be easily reused in other domains. To illustrate how our approach to model synthesis works for i-DSMLs, we have created MGridML, an i-DSML for energy management in smart microgrids, and an MGridVM prototype, the DSVM for MGridML. We evaluated our approach by performing experiments on the model synthesis aspect of MGridVM and comparing the results to a DSVM from the user-centric communication domain.     

Iconic languages: Towards end-user programming of mobile applications

After tracing the steps that led to the current generation of iconic languages starting from the original idea of S.K. Chang, we describe an iconic language, named MicroApp, for modeling pervasive mobile applications directly on the mobile device. MicroApp exploits generalized icons for composing mobile applications: services are represented by icons and are composed of adopting colors for representing data-flow. We also qualitatively evaluate the visual environment that implements this iconic language.