A Domain-Specific Language and Editor for Parallel Particle Methods

Domain-specific languages (DSLs) are of increasing importance in scientific high-performance computing to reduce development costs, raise the level of abstraction and, thus, ease scientific programming. However, designing and implementing DSLs is not an easy task, as it requires knowledge of the application domain and experience in language engineering and compilers. Consequently, many DSLs follow a weak approach using macros or text generators, which lack many of the features that make a DSL a comfortable for programmers. Some of these features---e.g., syntax highlighting, type inference, error reporting, and code completion---are easily provided by language workbenches, which combine language engineering techniques and tools in a common ecosystem. In this paper, we present the Parallel Particle-Mesh Environment (PPME), a DSL and development environment for numerical simulations based on particle methods and hybrid particle-mesh methods. PPME uses the meta programming system (MPS), a projectional language workbench. PPME is the successor of the Parallel Particle-Mesh Language (PPML), a Fortran-based DSL that used conventional implementation strategies. We analyze and compare both languages and demonstrate how the programmer's experience can be improved using static analyses and projectional editing. Furthermore, we present an explicit domain model for particle abstractions and the first formal type system for particle methods.Comment: Submitted to ACM Transactions on Mathematical Software on Dec. 25, 201

A TUTORIAL ON FORMANT-BASED SPEECH SYNTHESIS FOR THE DOCUMENTATION OF CRITICALLY ENDANGERED LANGUAGES

Smaller languages, that is, those spoken by 5,000 people or less are dying at an alarming rate (Krauss 1992). Many are disappearing without having been studied acoustically. The methodology discussed in this paper can help build formant-based speech synthesis systems for the documentation and revitalization of these languages. Developing Text-to-Speech (TTS) functionalities for use in smart devices can breathe a new life into dying languages (Crystal 2000). In the first tutorial on this topic, Koffi (2020) explained how the Arpabet transcription system can be expanded for use in African languages and beyond. In the present tutorial, Author 1 and Author 2 lay the foundations for formant-based speech synthesis patterned after Klatt (1980) and Klatt and Klatt (1990). Betine, (ISO: 639-3-eot), a critically endangered language in Côte d’Ivoire, West Africa, is used to illustrate the processes involved in building a speech synthesis from the ground up for moribund languages. The steps include constructing a language model, a speaker model, a software model, an intonation model, extracting relevant acoustic phonetic data, and coding them. Ancillary topics such as text normalization, downsampling, and bandwidth calculations are also discussed

The Layer-Oriented Approach to Declarative Languages for Biological Modeling

We present a new approach to modeling languages for computational biology, which we call the layer-oriented approach. The approach stems from the observation that many diverse biological phenomena are described using a small set of mathematical formalisms (e.g. differential equations), while at the same time different domains and subdomains of computational biology require that models are structured according to the accepted terminology and classification of that domain. Our approach uses distinct semantic layers to represent the domain-specific biological concepts and the underlying mathematical formalisms. Additional functionality can be transparently added to the language by adding more layers. This approach is specifically concerned with declarative languages, and throughout the paper we note some of the limitations inherent to declarative approaches. The layer-oriented approach is a way to specify explicitly how high-level biological modeling concepts are mapped to a computational representation, while abstracting away details of particular programming languages and simulation environments. To illustrate this process, we define an example language for describing models of ionic currents, and use a general mathematical notation for semantic transformations to show how to generate model simulation code for various simulation environments. We use the example language to describe a Purkinje neuron model and demonstrate how the layer-oriented approach can be used for solving several practical issues of computational neuroscience model development. We discuss the advantages and limitations of the approach in comparison with other modeling language efforts in the domain of computational biology and outline some principles for extensible, flexible modeling language design. We conclude by describing in detail the semantic transformations defined for our language

Research exercise: The Implementation of Two-way Immersion Programs in Schools

As society becomes more global, educators are searching for models of education that provide students with the ability to be competitive in the global marketplace. Bilingual education offers students the opportunity to learn two languages while maintaining student achievement in other content areas. Two-way immersion programs, also known as dual-language programs, are a model of instruction where students receive content instruction in two languages. In addition, students and teacher speak both languages and the native languages of the members of the classroom vary. As the programs have been proven to be effective, the next step is figuring out how these programs can be implemented on a practical level (Garland 2012). It is because bilingual programs benefit both language-minority and language-majority students, it provides a positive education option for many students. In order to see if two-way immersion programs can be implemented on a wider scale, research needs to indicate the positive and negative consequences of these programs. Without this research, it will be difficult to see if two-way immersion programs are even a viable option for schools, especially ones with high populations of speakers of other languages. The purpose of this research is to examine the human and material resources necessary for the successful implementation of two-way immersion programs in the United States to determine the practicality of using this dual-language model on a wider scale.https://ecommons.udayton.edu/stander_posters/1565/thumbnail.jp

An Expressive Language and Efficient Execution System for Software Agents

Software agents can be used to automate many of the tedious, time-consuming information processing tasks that humans currently have to complete manually. However, to do so, agent plans must be capable of representing the myriad of actions and control flows required to perform those tasks. In addition, since these tasks can require integrating multiple sources of remote information ? typically, a slow, I/O-bound process ? it is desirable to make execution as efficient as possible. To address both of these needs, we present a flexible software agent plan language and a highly parallel execution system that enable the efficient execution of expressive agent plans. The plan language allows complex tasks to be more easily expressed by providing a variety of operators for flexibly processing the data as well as supporting subplans (for modularity) and recursion (for indeterminate looping). The executor is based on a streaming dataflow model of execution to maximize the amount of operator and data parallelism possible at runtime. We have implemented both the language and executor in a system called THESEUS. Our results from testing THESEUS show that streaming dataflow execution can yield significant speedups over both traditional serial (von Neumann) as well as non-streaming dataflow-style execution that existing software and robot agent execution systems currently support. In addition, we show how plans written in the language we present can represent certain types of subtasks that cannot be accomplished using the languages supported by network query engines. Finally, we demonstrate that the increased expressivity of our plan language does not hamper performance; specifically, we show how data can be integrated from multiple remote sources just as efficiently using our architecture as is possible with a state-of-the-art streaming-dataflow network query engine

A Systematic Study of Performance Disparities in Multilingual Task-Oriented Dialogue Systems

Achieving robust language technologies that can perform well across the world's many languages is a central goal of multilingual NLP. In this work, we take stock of and empirically analyse task performance disparities that exist between multilingual task-oriented dialogue (ToD) systems. We first define new quantitative measures of absolute and relative equivalence in system performance, capturing disparities across languages and within individual languages. Through a series of controlled experiments, we demonstrate that performance disparities depend on a number of factors: the nature of the ToD task at hand, the underlying pretrained language model, the target language, and the amount of ToD annotated data. We empirically prove the existence of the adaptation and intrinsic biases in current ToD systems: e.g., ToD systems trained for Arabic or Turkish using annotated ToD data fully parallel to English ToD data still exhibit diminished ToD task performance. Beyond providing a series of insights into the performance disparities of ToD systems in different languages, our analyses offer practical tips on how to approach ToD data collection and system development for new languages.Comment: Accepted to EMNLP 202