User interface development and software environments : the Chiron-1 system

User interface development systems for software environments have to cope with the broad, extensible and dynamic character of such environments, must support internal and external integration, and should enable various software development strategies. The Chiron-1 system adapts and extends key ideas from current research in user interface development systems to address the particular demands of software environments. Important Chiron-1 concepts are: separation of concerns, dynamism, and open architecture. We discuss the requirements on such user interface development systems, present the Chiron-1 architecture and a scenario of its usage, detail the concepts it embodies, and report on its design and prototype implementation

In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonology

This paper investigates the ability of neural network architectures to effectively learn diachronic phonological generalizations in a multilingual setting. We employ models using three different types of language embedding (dense, sigmoid, and straight-through). We find that the Straight-Through model outperforms the other two in terms of accuracy, but the Sigmoid model's language embeddings show the strongest agreement with the traditional subgrouping of the Slavic languages. We find that the Straight-Through model has learned coherent, semi-interpretable information about sound change, and outline directions for future research

Automatic adaptive approximation for stencil computations

International audienceApproximate computing is necessary to meet deadlines in some compute-intensive applications like simulation. Building them requires a high level of expertise from the application designers as well as a significant development effort. Some application programming interfaces greatly facilitate their conception but they still heavily rely on the developer's domain-specific knowledge and require many modifications to successfully generate an approximate version of the program. In this paper we present new techniques to semi-automatically discover relevant approximate computing parameters. We believe that superior compiler-user interaction is the key to improved productivity. After pinpointing the region of interest to optimize, the developer is guided by the compiler in making the best implementation choices. Static analysis and runtime monitoring are used to infer approximation parameter values for the application. We evaluated these techniques on multiple application kernels that support approximation and show that with the help of our method, we achieve similar performance as non-assisted, hand-tuned version while requiring minimal intervention from the user